Silicon Investor - Disruption Innovation

[Julius Wong] This New Shock-Absorbing Gel Can Withstand Supersonic Impacts Made from a res...

Julius Wong — 12/21/2022 12:33:45 PM

This New Shock-Absorbing Gel Can Withstand Supersonic Impacts

Made from a resilient protein in human cells, the technology could improve body armor, space gear and even cell phone cases

The new hydrogel might someday lead to shock-absorbing smartphone cases, as well as better bullet-proof vests and space equipment. Marco Verch Professional Photographer via Flickr under CC BY 2.0

Existing body armor can stop shrapnel and bullets from reaching the person wearing it. But it doesn’t absorb a projectile’s kinetic energy, meaning the wearer can still get injured from the force of the blow. Beyond that, most body armor—made from heavy, bulky layers of ceramic and fibers—is only good once, as a strike from a projectile can compromise its structural integrity.

Now, researchers at the University of Kent in England may have developed a promising new solution to these problems, providing a potential path forward for improved bullet-proof clothing and more resilient space exploration equipment. Using a protein called talin, which is found in human cells, scientists have created a novel material that can absorb the impact of projectiles—even those flying faster than the speed of sound.

Talin helps cells get around inside the body and may also play a role in memory storage. But notably, it acts as a “natural shock absorber,” says lead researcher Benjamin Goult, a biochemist at the University of Kent, in a statement.

Talin molecules contain structures that, when put under tension, unfold and stretch out. Once the tension is released, they fold back up again. They can do this shock-absorbing maneuver over and over without harming the cell.

By adapting the talin molecule and linking large numbers of them together, the researchers created a gel-like material called a hydrogel that maintained the natural protein’s shock-absorbing properties.

“Mother Nature is an amazing designer, and it’s always interesting when scientists and engineers can find new applications for structures that are everywhere around us,” Eric S. Hintz, a historian at the Lemelson Center for the Study of Invention and Innovation at Smithsonian’s National Museum of American History who was not involved in the project, tells Smithsonian magazine in an email. The new hydrogel, he says, “sounds very promising.”

To test the technology’s effectiveness, scientists placed the gel atop an aluminum plate and fired tiny basalt particles and larger bits of aluminum at it. These small projectiles traveled at speeds of more than 3,350 miles per hour—three times faster than a bullet fired from a handgun, as Andrew Liszewski notes for Gizmodo. The hydrogel absorbed the shock of the projectiles, successfully protected the aluminum plate and captured the particles without destroying them.

The team ran the same experiment with a control gel. When pelted with a supersonic particle, the control gel allowed it to pass through and bore a crater in the aluminum plate behind the gel. The projectile was also destroyed in the process. The researchers published their findings on the preprint server bioRxiv; the paper has not yet been peer-reviewed.

“Our material perfectly caught and ‘cuddled’ with the projectile … keeping it beautifully preserved,” says paper co-author Jennifer Hiscock, a supramolecular chemist at the University of Kent, to New Scientist’s Carissa Wong.

The researchers patented the material and are now conducting even more tests with partners in the aerospace and defense industries. Talin may someday help protect soldiers heading into battle and spacecraft traveling through fast-moving dust and debris in space.

In the realm of body armor, one of the talin gel’s strengths is that it can stop a bullet without destroying it, Hintz says. “You can imagine how important this would be for law enforcement officers, who could remove the preserved bullet from a [talin] vest, then run forensics to match the bullet to the shooter’s gun,” he says. “In addition, the … material reforms after initial impact, meaning you could potentially reuse a [talin] vest after it was hit.”

As for aerospace, the industry currently uses aerogels, or low-density gels that had the liquid removed from them, to capture flying projectiles. Aerogels achieve this, in part, by turning the projectile’s energy into heat. “This can melt the aerogel itself, rendering it useless for the next impact,” Hintz says. “It appears that the [talin materials] do not heat up as much. So … a [talin]-based outer layer on a spaceship would potentially remain intact, even after multiple high-speed strikes from micro-meteorites or space debris. That would make astronauts feel more confident in the structural integrity of their spacecraft.”

The new material may also be useful for capturing space debris—without destroying it—for further study.

Consumers may also one day reap the shock-absorbing benefits of talin in their running shoes, vehicle bumpers and cell phone cases, reports IFLScience’s Laura Simmons.

smithsonianmag.com

[Julius Wong] Engineers solve a mystery on the path to smaller, lighter batteries techxplore....

Julius Wong — 11/20/2022 7:38:55 AM

Engineers solve a mystery on the path to smaller, lighter batteries

techxplore.com

[Julius Wong] Tapping into the million-year energy source below our feet MIT spinout Quaise En...

Julius Wong — 11/20/2022 7:37:24 AM

Tapping into the million-year energy source below our feet
MIT spinout Quaise Energy is working to create geothermal wells made from the deepest holes in the world.

news.mit.edu

[Julius Wong] Engineers created a safe micro-nuclear reactor that fits in the back of a truck ...

Julius Wong — 10/12/2022 12:07:01 PM

Engineers created a safe micro-nuclear reactor that fits in the back of a truck

BYU chemical engineering professor Matthew Memmott works in his lab on campus. Photo by Brooklyn Jarvis Kelson/BYU Photo

New solution provides safer nuclear powerNuclear reactors in the U.S. usually fall under the category of Light-Water Reactor. These split uranium atoms to create energy, with leftover materials and heat stored in solid fuel rods that require running water to keep them cool. If the rods don't receive enough water and overheat, the entire facility is at risk of a meltdown.

The new solution proposed by the BYU scientists will store the leftover radioactive elements in molten salts instead of fuel rods. "Nuclear energy can be extremely safe and extremely affordable, if done the right way," Memmott explained. "It’s a very good solution to the energy situation we're in because there are no emissions or pollution from it."

The new micro-reactor proposal would dissolve all of the radioactive byproducts in molten salt. Salt has an incredibly high melting temperature of about 550°C, meaning it doesn't take long for these byproducts to drop below the melting point. The radiated heat is absorbed into the salt, which doesn't remelt, removing the risk of a meltdown.

The products of the reaction are also safely stored within the molten salts, meaning nuclear waste is eliminated. Some of the products can also be extracted and resold. Valuable elements such as cobalt-60, gold, platinum, and neodymium can all be removed from the salt. Molten salt reactors date back to the 1960s, and recent developments have lead to a new surge in experiments, such as the ones at BYU.

interestingengineering.com

[Julius Wong] This Startup Builds Houses by Pumping Concrete Into Inflatable Forms singularit...

Julius Wong — 10/8/2022 3:47:31 PM

This Startup Builds Houses by Pumping Concrete Into Inflatable Forms

singularityhub.com

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automatic-construction.com

[Frank Sully] Robot Video Friday: Agility CEO Damion Shelton and CTO Jonathan Hurst discuss ar...

Frank Sully — 9/30/2022 12:05:08 PM

Robot Video Friday: Agility CEO Damion Shelton and CTO Jonathan Hurst discuss artificial intelligence and its role in robot control. They also discuss the capability of robot learning paired with physics-based locomotion, Cassie setting a new world record using learned policies for control, and an exploration of the future of robotics through Dall-E.

That new version of Digit is looking slick!

Cheers,
Frank

[Frank Sully] [graphic] Tech / Tech War Tech war: China chip start-ups clamour to tout AI ch...

Frank Sully — 9/29/2022 5:41:17 PM

Tech / Tech War

Tech war: China chip start-ups clamour to tout AI chip breakthroughs after Nvidia sales ban, prompting analyst skepticism.

Chongqing-based Xiangdixian Computing Technology has unveiled Tianjun No. 1, a GPU with 12-nanometre node technology

Analysts say that Chinese chip companies still lag far behind Nvidia, which has a near monopoly on GPUs used to train AI models

Ann Cao in Shanghai

Chinese semiconductor start-ups are rushing to claim breakthroughs in artificial intelligence (AI) chips after the US restricted the export of advanced chips from Nvidia Corp and Advanced Micro Devices (AMD) to China, prompting scepticism from many industry analysts.

Chongqing-based Xiangdixian Computing Technology, which designs microprocessors, this week unveiled Tianjun No. 1, a graphics processing unit (GPU) with 12-nanometre node technology. The company claimed it has “reached an internationally advanced level” and will “effectively fill the gap in the domestic market”, according to an official post on its WeChat account on Wednesday.

Xiangdixian, a chip design start-up founded in Chongqing, southwestern Sichuan Province in 2020, is headed by chip veteran Tang Zhimin who previously worked for Loongson Technology and Hygon Information Tech, two Chinese chip companies that make microprocessors.

Tang said the launch of the new 12-nm chip, which took one and a half years to come to fruition, was due to “the support of the Chongqing government and other parties in society”. “China currently lacks mature and advanced domestic products in the field of GPU chips,” said Tang, adding that the new chip was now entering mass production and would help address the country’s strategic “choke points”.

The announcement came a few weeks after Shenzhen-based AI chip design start-up Moffett AI revealed a new AI inference accelerator, called S30, which it said has stronger computing power than Nvidia GPUs. It said the computing power of the S30 is twice and 1.2 times stronger than the Nvidia A100 and H100 respectively, the two chips that have been banned for export to China by the US as of September.

Moffett AI, which was established in 2018 by Wang Wei, a former chip architect at Qualcomm and Intel, said it was a “victory of 12-nm chips over 4-nm chips”, according to a post on the company’s official WeChat account on September 9.

The moves by these chip start-ups to promote their achievements comes after Washington imposed export restrictions on certain advanced AI chips from Nvidia and AMD on August 31, which sparked calls in Beijing for the country to double down on efforts to find domestic substitutes.

Shanghai-based GPU start-up Biren Technology, which released a new 7-nm chip called BR100 in August, made a splash at the World Artificial Intelligence Conference in Shanghai in early September, when it said the BR100 had “set a global record” in computing power, with peak performance three times better than equivalent products on the market.

However, analysts and industry insiders have said that Chinese chip companies still lag far behind Nvidia, which has a near monopoly on GPUs used to train AI models.

Lu Jianping, chief technology officer at Shanghai-based Iluvatar Corex, said Nvidia controls 95 per cent of the market for general purpose GPUs used to train AI models. Lu said that he was unable to find any mature “rival products” from Chinese GPU start-ups for assessment against Nvidia chips.

“So far we can’t get any, probably because everyone is still in the development stage,” he said in a recent online session organised by chip industry consultancy ICwise.

“There are certain domestic alternative GPUs in mainland China, but they have a gap of 3-5 years with Nvidia’s advanced chips,” said Zhang Xiaorong, director of Beijing-based research institute Shendu Technology. However, domestic GPU firms now have more room for development after the US sales ban, he added.

Ann Cao

Ann Cao is a Shanghai-based technology reporter for the Post, covering technology start-ups and policies in the city and eastern China. She graduated from the University of Hong Kong with a master's degree in journalism.

scmp.com

[Julius Wong] Prototype electric airplane takes first flight apnews.com

Julius Wong — 9/27/2022 7:57:24 PM

[caleean] That is really interesting

caleean — 9/27/2022 4:03:33 AM

[Julius Wong] The Wild Plan to Export Sun From the Sahara to the UK [graphic] By the time S...

Julius Wong — 9/24/2022 9:13:26 PM

The Wild Plan to Export Sun From the Sahara to the UK

By the time Scotland’s Hunterston B nuclear power station closed in January of this year, its dual reactors had produced enough energy to power 1.8 million British homes for 46 years. It also provided over 500 jobs to people living in one of the country’s most deprived areas. Now, a project borne on the tide of a new era of energy production will take its place.

The new XLCC factory, to be built at Hunterston in 2023, will not generate electricity. Instead, the site’s 900 workers plan to create four high-voltage, direct current (HVDC) electricity cables that will stretch 3,800 km from Britain’s south coast, beneath the sea, to a patch of desert at ??Guelmim Oued Noun in central Morocco. From there, they’ll provide enough energy to power 7 million British homes and 8 percent of the UK’s total electricity requirement with 10.5 gigawatts of Saharan sun and wind by 2030.

Richard Hardy, project director at Xlinks, which developed the proposal, says people were “taken aback” by its scale. “But when you really step back, it almost becomes obvious that so long as you can get the power back, the project makes sense,” he says.

HVDC technology has existed since 1954, when Sweden connected the Island of Gotland to its mainland grid. HVDC cables experience low energy losses of around 2 percent, making them suitable for transporting electricity over long distances, compared to the 30 percent lost by alternating-current (AC) systems, which most energy grids operate on.

Until a few decades ago, HVDC only worked well when supported by strong, consistent energy-generating sources, like nuclear power plants. They also require converter stations the size of football fields to change the electricity back to AC at a cable’s terminus. The cables and current converter stations meant HVDC cost hundreds of millions of pounds. Installation can take decades. Then, in the 90s, a new system that used insulated gate bipolar transistors (IGBTs), or electronic switches, emerged. These allowed operators to mimic the voltage waveform of a strong energy source with that of weak sources, like solar and wind farms. HVDC projects still require enormous budgets, but the IGBTs allow them to use renewable energy sources. Operators were able to connect national grids with remote solar farms, and their popularity boomed.

HVDC systems can solve one of renewable energy’s biggest challenges: consistent supply. Wind farms generate too much energy when the wind blows and too little when it is still. Countries can access energy around the clock by connecting their grids to distant lands with different weather patterns.

The concept of connecting different countries’ grids also presents an economic opportunity. HVDC connectors give people access to the lowest prices. That provides an enormous benefit when regional events, like Russia’s invasion of Ukraine, prompt a rise in energy prices.

That’s one of the reasons the UK, where residential energy prices are now the second highest in Europe, has been among the fastest to adopt HVDC technology. Existing cables connect its grid with Ireland, France, Belgium, the Netherlands, and Norway. A new project to connect with Germany reached its funding target in July. And the Energy Security Bill now passing through parliament will accelerate the creation of HVDC projects by providing them with official licenses.

wired.com

[Julius Wong] Structure-inflating construction tech could give 3D printing a run for its money...

Julius Wong — 9/17/2022 9:04:38 PM

Structure-inflating construction tech could give 3D printing a run for its money

Automatic Construction CEO Alex Bell stands atop a prototype building which was constructed using his company's Flexible Factory Formwork system
Automatic Construction

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Automatic Construction CEO Alex Bell stands atop a prototype building which was constructed using his company's Flexible Factory Formwork system
Automatic Construction

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Bell tells us that he ultimately hopes to have the rebar, tension cables and other reinforcing elements preinstalled within the forms
Automatic Construction

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The PVC form stays in place on the finished structure, forming a waterproof and airtight barrier
Automatic Construction

We've heard how 3D-printed concrete buildings can be constructed quickly and easily, but could there be an even faster and simpler method? According to American inventor Alex Bell, there most certainly is – and it involves inflating buildings, then pumping concrete into them.

When we last heard from Bell, he had created a quirky front-wheel-drive bike with under-the-seat steering, known as the Bellcycle.

His new construction technique, called Inflatable Flexible Factory Formwork (IFFF), has been commercialized via his New York City-based startup, Automatic Construction. Here's a quick explanation of how it works …

The process begins with a truck delivering a rolled-up PVC (polyvinyl chloride) fabric "form" to the construction site. That flexible form is not unlike a giant version of a rolled up, deflated camping mattress.

After the form has been laid in place, air pumps are used to inflate its walls and roof. This causes it to pop up, taking on the three-dimensional shape of the finished structure. Next, locally sourced wet concrete is pumped into the walls and roof of the form, displacing the air inside.

Once that concrete has set, the result is a solid concrete building shell. The form is not removed from that shell, since it now serves as a waterproof, airtight, and thus energy-saving barrier. Features such as doors, windows, interior drywall and exterior siding are then added.

The PVC form stays in place on the finished structure, forming a waterproof and airtight barrier
Automatic Construction

In the prototype structures created so far, rebar reinforcements have also been added onsite. However, Bell tells us that he ultimately hopes to have the rebar, tension cables and other reinforcing elements preinstalled within the forms.

But just how quickly do the buildings go up?

"For our 100 square foot [9.3 sq m] and 200 square foot [18.6 sq m] prototypes, the inflation took seven to 10 minutes with air," he said. "Then the concrete pump filled them in 1.5 hours. Including labor, our prototypes only cost $20 per square foot. This is significantly cheaper than anything else."

Bell's team is now selling homes direct to customers in New York's Hudson Valley, with one project currently underway and another two signed. He tells us that his company has also signed one contract with a "large commercial contractor" to deliver a structure, and signed another contract to deliver a box culvert to an infrastructure contractor.

Along with homes, commercial buildings and infrastructure-related projects, other envisioned applications of the IFFF technology include swimming pool foundations, rapid-deploy military structures and perhaps even one day skyscrapers, or structures on Mars for use by astronauts.

Source: Automatic Construction

newatlas.com

[Frank Sully] 10 years later, deep learning ‘revolution’ rages on, say AI pioneers Hinton, LeC...

Frank Sully — 9/14/2022 7:10:50 PM

10 years later, deep learning ‘revolution’ rages on, say AI pioneers Hinton, LeCun and Li

Sharon Goldman @sharongoldman

September 14, 2022

Artificial intelligence (AI) pioneer Geoffrey Hinton, one of the trailblazers of the deep learning “revolution” that began a decade ago, says that the rapid progress in AI will continue to accelerate.
In an interview before the 10-year anniversary of key neural network research that led to a major AI breakthrough in 2012, Hinton and other leading AI luminaries fired back at some critics who say deep learning has “hit a wall.”

“We’re going to see big advances in robotics — dexterous, agile, more compliant robots that do things more efficiently and gently like we do,” Hinton said.

Other AI pathbreakers, including Yann LeCun, head of AI and chief scientist at Meta and Stanford University professor Fei-Fei Li, agree with Hinton that the results from the groundbreaking 2012 research on the ImageNet database — which was built on previous work to unlock significant advancements in computer vision specifically and deep learning overall — pushed deep learning into the mainstream and have sparked a massive momentum that will be hard to stop.

In an interview with VentureBeat, LeCun said that obstacles are being cleared at an incredible and accelerating speed. “The progress over just the last four or five years has been astonishing,” he added.

And Li, who in 2006 invented ImageNet, a large-scale dataset of human-annotated photos for developing computer vision algorithms, told VentureBeat that the evolution of deep learning since 2012 has been “a phenomenal revolution that I could not have dreamed of.”

Success tends to draw critics, however. And there are strong voices who call out the limitations of deep learning and say its success is extremely narrow in scope. They also maintain the hype that neural nets have created is just that, and is not close to being the fundamental breakthrough that some supporters say it is: that it is the groundwork that will eventually help us get to the anticipated “artificial general intelligence” (AGI), where AI is truly human-like in its reasoning power.

Looking back on a booming AI decade

Gary Marcus, professor emeritus at NYU and the founder and CEO of Robust.AI, wrote this past March about deep learning “ hitting a wall” and says that while there has certainly been progress, “we are fairly stuck on common sense knowledge and reasoning about the physical world.”

And Emily Bender, professor of computational linguistics at the University of Washington and a regular critic of what she calls the “ deep learning bubble,” said she doesn’t think that today’s natural language processing (NLP) and computer vision models add up to “substantial steps” toward “what other people mean by AI and AGI.”

Regardless, what the critics can’t take away is that huge progress has already been made in some key applications like computer vision and language that have set thousands of companies off on a scramble to harness the power of deep learning, power that has already yielded impressive results in recommendation engines, translation software, chatbots and much more.

However, there are also serious deep learning debates that can’t be ignored. There are essential issues to be addressed around AI ethics and bias, for example, as well as questions about how AI regulation can protect the public from being discriminated against in areas such as employment, medical care and surveillance.

In 2022, as we look back on a booming AI decade, VentureBeat wanted to know the following: What lessons can we learn from the past decade of deep learning progress? And what does the future hold for this revolutionary technology that’s changing the world, for better or worse?

Geoffrey Hinton

AI pioneers knew a revolution was comingHinton says he always knew the deep learning “revolution” was coming.

“A bunch of us were convinced this had to be the future [of artificial intelligence],” said Hinton, whose 1986 paper popularized the backpropagation algorithm for training multilayer neural networks. “We managed to show that what we had believed all along was correct.”

LeCun, who pioneered the use of backpropagation and convolutional neural networks in 1989, agrees. “I had very little doubt that eventually, techniques similar to the ones we had developed in the 80s and 90s” would be adopted, he said.

What Hinton and LeCun, among others, believed was a contrarian view that deep learning architectures such as multilayered neural networks could be applied to fields such as computer vision, speech recognition, NLP and machine translation to produce results as good or better than those of human experts. Pushing back against critics who often refused to even consider their research, they maintained that algorithmic techniques such as backpropagation and convolutional neural networks were key to jumpstarting AI progress, which had stalled since a series of setbacks in the 1980s and 1990s.

Meanwhile, Li, who is also codirector of the Stanford Institute for Human-Centered AI and former chief scientist of AI and machine learning at Google, had also been confident that her hypothesis — that with the right algorithms, the ImageNet database held the key to advancing computer vision and deep learning research — was correct.

“It was a very out-of-the-box way of thinking about machine learning and a high-risk move,” she said, but “we believed scientifically that our hypothesis was right.”

However, all of these theories, developed over several decades of AI research, didn’t fully prove themselves until the autumn of 2012. That was when a breakthrough occurred that many say sparked a new deep learning revolution.

In October 2012, Alex Krizhevsky and Ilya Sutskever, along with Hinton as their Ph.D. advisor, entered the ImageNet competition, which was founded by Li to evaluate algorithms designed for large-scale object detection and image classification. The trio won with their paper ImageNet Classification with Deep Convolutional Neural Networks, which used the ImageNet database to create a pioneering neural network known as AlexNet. It proved to be far more accurate at classifying different images than anything that had come before.

The paper, which wowed the AI research community, built on earlier breakthroughs and, thanks to the ImageNet dataset and more powerful GPU hardware, directly led to the next decade’s major AI success stories — everything from Google Photos, Google Translate and Uber to Alexa, DALL-E and AlphaFold.

Since then, investment in AI has grown exponentially: The global startup funding of AI grew from $670 million in 2011 to $36 billion U.S. dollars in 2020, and then doubled again to $77 billion in 2021.

The year neural nets went mainstream

After the 2012 ImageNet competition, media outlets quickly picked up on the deep learning trend. A New York Timesarticle the following month, Scientists See Promise in Deep-Learning Programs[subscription required], said: “Using an artificial intelligence technique inspired by theories about how the brain recognizes patterns, technology companies are reporting startling gains in fields as diverse as computer vision, speech recognition and the identification of promising new molecules for designing drugs.” What is new, the article continued, “is the growing speed and accuracy of deep-learning programs, often called artificial neural networks or just ‘neural nets’ for their resemblance to the neural connections in the brain.”

AlexNet was not alone in making big deep learning news that year: In June 2012, researchers at Google’s X lab built a neural network made up of 16,000 computer processors with one billion connections that, over time, began to identify “cat-like” features until it could recognize cat videos on YouTube with a high degree of accuracy. At the same time, Jeffrey Dean and Andrew Ngwere doing breakthrough work on large-scale image recognition at Google Brain. And at 2012’s IEEE Conference on Computer Vision and Pattern Recognition, researchers Dan Ciregan et al. significantly improved upon the best performance for convolutional neural networks on multiple image databases.

All told, by 2013, “pretty much all the computer vision research had switched to neural nets,” said Hinton, who since then has divided his time between Google Research and the University of Toronto. It was a nearly total AI change of heart from as recently as 2007, he added, when “it wasn’t appropriate to have two papers on deep learning at a conference.”

Fei-Fei Li

A decade of deep learning progressLi said her intimate involvement in the deep learning breakthroughs – she personally announced the ImageNet competition winner at the 2012 conference in Florence, Italy – meant it comes as no surprise that people recognize the importance of that moment.

“[ImageNet] was a vision started back in 2006 that hardly anybody supported,” said Li. But, she added, it “really paid off in such a historical, momentous way.”

Since 2012, the progress in deep learning has been both strikingly fast and impressively deep.

“There are obstacles that are being cleared at an incredible speed,” said LeCun, citing progress in natural language understanding, translation in text generation and image synthesis.

Some areas have even progressed more quickly than expected. For Hinton, that includes using neural networks in machine translation, which saw great strides in 2014. “I thought that would be many more years,” he said. And Li admitted that advances in computer vision — such as DALL-E — “have moved faster than I thought.”

Dismissing deep learning critics

However, not everyone agrees that deep learning progress has been jaw-dropping. In November 2012, Gary Marcus, professor emeritus at NYU and the founder and CEO of Robust.AI, wrote an article for the New Yorker [subscription required] in which he said ,“To paraphrase an old parable, Hinton has built a better ladder; but a better ladder doesn’t necessarily get you to the moon.”

Today, Marcus says he doesn’t think deep learning has brought AI any closer to the “moon” — the moon being artificial general intelligence, or human-level AI — than it was a decade ago.

“Of course there’s been progress, but in order to get to the moon, you would have to solve causal understanding and natural language understanding and reasoning,” he said. “There’s not been a lot of progress on those things.”

Marcus said he believes that hybrid modelsthat combine neural networks with symbolic artificial intelligence, the branch of AI that dominated the field before the rise of deep learning, is the way forward to combat the limits of neural networks.

For their part, both Hinton and LeCun dismiss Marcus’ criticisms.

“[Deep learning] hasn’t hit a wall – if you look at the progress recently, it’s been amazing,” said Hinton, though he has acknowledged in the past that deep learning is limited in the scope of problems it can solve.

There are “no walls being hit,” added LeCun. “I think there are obstacles to clear and solutions to those obstacles that are not entirely known,” he said. “But I don’t see progress slowing down at all … progress is accelerating, if anything.”

Still, Bender isn’t convinced. “To the extent that they’re talking about simply progress towards classifying images according to labels provided in benchmarks like ImageNet, it seems like 2012 had some qualitative breakthroughs,” she told VentureBeat by email. “If they are talking about anything grander than that, it’s all hype.”

Issues of AI bias and ethics loom large

In other ways, Bender also maintains that the field of AI and deep learning has gone too far. “I do think that the ability (compute power + effective algorithms) to process very large datasets into systems that can generate synthetic text and images has led to us getting way out over our skis in several ways,” she said. For example, “we seem to be stuck in a cycle of people ‘discovering’ that models are biased and proposing trying to debias them, despite well-established results that there is no such thing as a fully debiased dataset or model.”

In addition, she said that she would “like to see the field be held to real standards of accountability, both for empirical claims made actually being tested and for product safety – for that to happen, we will need the public at large to understand what is at stake as well as how to see through AI hype claims and we will need effective regulation.”

However, LeCun pointed out that “these are complicated, important questions that people tend to simplify,” and a lot of people “have assumptions of ill intent.” Most companies, he maintained, “actually want to do the right thing.”

In addition, he complained about those not involved in the science and technology and research of AI.

“You have a whole ecosystem of people kind of shooting from the bleachers,” he said, “and basically are just attracting attention.”

Deep learning debates will certainly continue

As fierce as these debates can seem, Li emphasizes that they are what science is all about. “Science is not the truth, science is a journey to seek the truth,” she said. “It’s the journey to discover and to improve — so the debates, the criticisms, the celebration is all part of it.”

Yet, some of the debates and criticism strike her as “a bit contrived,” with extremes on either side, whether it’s saying AI is all wrong or that AGI is around the corner. “I think it’s a relatively popularized version of a deeper, much more subtle, more nuanced, more multidimensional scientific debate,” she said.

Certainly, Li pointed out, there have been disappointments in AI progress over the past decade –- and not always about technology. “I think the most disappointing thing is back in 2014 when, together with my former student, I cofounded AI4ALL and started to bring young women, students of color and students from underserved communities into the world of AI,” she said. “We wanted to see a future that is much more diverse in the AI world.”

While it has only been eight years, she insisted the change is still too slow. “I would love to see faster, deeper changes and I don’t see enough effort in helping the pipeline, especially in the middle and high school age group,” she said. “We have already lost so many talented students.”

“I would say that other people underestimated the complexity of it,” he said, adding that he doesn’t put himself in that category. “I knew it was hard and would take a long time,” he claimed. “I disagree with some people who say that we basically have it all figured out … [that] it’s just a matter of making those models bigger.”

In fact, LeCun recently published a blueprintfor creating “autonomous machine intelligence” that also shows how he thinks current approaches to AI will not get us to human-level AI.

But he also still sees vast potential for the future of deep learning: What he is most personally excited about and actively working on, he says, is getting machines to learn more efficiently — more like animals and humans.

“The big question for me is what is the underlying principle on which animal learning is based — that’s one reason I’ve been advocating for things like self-supervised learning,” he said. “That progress would allow us to build things that we are currently completely out of reach, like intelligent systems that can help us in our daily lives as if they were human assistants, which is something that we’re going to need because we’re all going to wear augmented reality glasses and we’re going to have to interact with them.”

Hinton agrees that there is much more deep learning progress on the way. In addition to advances in robotics, he also believes there will be another breakthrough in the basic computational infrastructure for neural nets, because “currently it’s just digital computing done with accelerators that are very good at doing matrix multipliers.” For backpropagation, he said, analog signals need to be converted to digital.

“I think we will find alternatives to backpropagation that work in analog hardware,” he said. “I’m pretty convinced that in the longer run we’ll have almost all the computation done in analog.”

Li says that what is most important for the future of deep learning is communication and education. “[At Stanford HAI], we actually spend an excessive amount of effort to educate business leaders, government, policymakers, media and reporters and journalists and just society at large, and create symposiums, conferences, workshops, issuing policy briefs, industry briefs,” she said.

With technology that is so new, she added, “I’m personally very concerned that the lack of background knowledge doesn’t help in transmitting a more nuanced and more thoughtful description of what this time is about.”

How 10 years of deep learning will be remembered

For Hinton, the past decade has offered deep learning success “beyond my wildest dreams.”

But, he emphasizes that while deep learning has made huge gains, it should be also remembered as an era of computer hardware advances. “It’s all on the back of the progress in computer hardware,” he said.

Critics like Marcus say that while some progress has been made with deep learning, “I think it might be seen in hindsight as a bit of a misadventure,” he said. “I think people in 2050 will look at the systems from 2022 and be like, yeah, they were brave, but they didn’t really work.”

But Li hopes that the last decade will be remembered as the beginning of a “great digital revolution that is making all humans, not just a few humans, or segments of humans, live and work better.”

As a scientist, she added, “I will never want to think that today’s deep learning is the end of AI exploration.” And societally, she said she wants to see AI as “an incredible technological tool that’s being developed and used in the most human-centered way – it’s imperative that we recognize the profound impact of this tool and we embrace the human-centered framework of thinking and designing and deploying AI.”

After all, she pointed out: “How we’re going to be remembered depends on what we’re doing now.”

venturebeat.com

[Frank Sully] Concept Designer Ben Mauro Delivers Epic 3D Trailer ‘Huxley’ This Week ‘In the N...

Frank Sully — 9/14/2022 1:00:16 AM

Concept Designer Ben Mauro Delivers Epic 3D Trailer ‘Huxley’ This Week ‘In the NVIDIA Studio’

Learn how the sci-fi comic was transformed into a gripping trailer, enabled by close artist collaboration and NVIDIA GeForce RTX GPUs.

September 13, 2022 by GERARDO DELGADO

3D artist, concept designer and storyteller Ben Mauro has contributed to some of the world’s biggest entertainment franchises. He’s worked on movies like Elysium, Valerian and Metal Gear Solid, as well as video games such as Halo Infinite and Call of Duty: Black Ops III.

Mauro has met many inspirational artists throughout his storied career, and he collaborated with a few of them to bring Huxley to life. He called the 3D trailer a year’s worth of work, worth every minute spent — following his decade-long process of creating the comic itself.

“Huxley” introduces a vibrant, futuristic world.

In Mauro’s fantastical, fictional world, two post-apocalyptic scavengers stumble upon a forgotten treasure map in the form of an ancient sentient robot, finding themselves amidst a mystery of galactic scale.In designing Huxley the comic, Mauro worked old-school magic with a pad and pencil, sketching characters and environments before importing visuals into Adobe Photoshop. His NVIDIA GeForce RTX 3090 GPU provided fast performance and AI features to speed up his creative workflow.

Early concept art of “Huxley.”

“What has become of me?” it thought.

The artist used Photoshop’s “Artboards” to quickly view reference artwork for inspiration, as well as “Image Size” to preserve critical details — both features accelerated by his GPU. To finish up the comic, Mauro turned to Blender software to create mockups and block out scenes with the intention of later converting back to 3D from 2D.

Camera shots were matched in Blender.

With 3D trailer production in progress, matte painter and environment artist Steve Cormann used Mauro’s Blender models as a convenient starting point, virtually a one-to-one match to the desired 3D outcome.

Advanced modeling in ZBrush.

Cormann, who specializes in Autodesk 3ds Max software, applied advanced modeling techniques in building the scene. 3ds Max has a GPU-accelerated viewport that guarantees fast and interactive 3D modeling. It also lets artists choose their preferred 3D renderer — which in Cormann’s case is Maxon’s Redshift, where combining GPU acceleration and AI-powered OptiX denoising resulted in lightning-fast final-frame rendering.

Applying textures in Adobe Substance 3D Painter.

This proved useful as Cormann exported scenes into Adobe Substance 3D Painter to apply various textures and colors. RTX-accelerated light- and ambient-occlusion features baked and optimized assets within the scenes in mere seconds, giving Cormann the option to experiment with different visual aesthetics quickly and easily.

All of the hero characters were textured from scratch by artist Antonio Esparza and team.

Enter more of Mauro’s collaborators: lead character artist Antonio Esparza and his team, who spent significant time in 3ds Max to refine individual scenes and generate the staggering number of hero characters. This included uniquely texturing each of the characters and props. Esparza said his GeForce RTX 2080 SUPER GPU allowed him to modify characters and export renders dramatically faster than his previous hardware.Esparza joked that before his hardware upgrade, “Most of the last hours of the day, it was me here, you know, like, waiting.” Director Sava Živkovic would say to Esparza, “Turn the lights off Antonio, we don’t want to see that progress bar.”

Meanwhile, Živkovic turned his focus to lighting in 3ds Max. His trusty GeForce RTX 2080 Ti GPU enabled RTX-accelerated AI denoising with Maxon’s Redshift, resulting in photorealistic visuals while remaining highly interactive. This let the director tweak and modify scenes freely and easily.

City scenes were brought to life using Anima, a simple crowd-simulation software with off-the-shelf character assets.

With renders and textures in a good place, rigging and modeling artist Lucas Salmon began building meshes and rigging in 3ds Max to prepare for animation. Motion capture work was then outsourced to the well-regarded Belgrade-based studio, Take One. With 54 Vicon cameras and one of the biggest capture stages in Europe, it’s no surprise the animation quality in Huxley is world class.

Visual effects were added in Adobe After Effects.

Živkovic then deployed Adobe After Effects to composite the piece. Roughly 90% of the visual effects (VFX) were accomplished with built-in tools, stock footage and various plugins. Key 3D VFX such as ship smoke trails were simulated in Blender and then added in comp. The ability to move between multiple apps quickly is a testament to the power of the RTX GPU, Živkovic said.

“I love the RTX 3090 GPU for the extra VRAM, especially for increasingly bigger scenes where I want everything to look really nice and have quality texture sizes,” he said.

Photorealistic details create an immersive experience for the trailer’s viewers.

Satisfied with the trailer, Mauro reflected on artistry. “As creatives, if we don’t see the film, game, or universe we want to experience in our entertainment, we’re in the position to create it with our hard-earned skills. I feel this is our duty as artists and creators to leave behind more imagined worlds than existed before we got there, to inspire the world and the next generation of artists/creators to push things even further than we did.” he said.

Concept designer and storyteller Ben Mauro.Access Mauro’s impressive portfolio on his website.

“Huxley” the movie is in development.

Huxley is an entire world rich in history and intrigue, currently being developed into a feature film and TV series.

Onwards and Upwards

Many of the techniques Mauro deployed can be learned by viewing free Studio Session tutorials on the NVIDIA Studio YouTube channel.

Learn core foundational warm-up exercises to inspire and ignite creative thinking, discover how to design sci-fi objects such as props, and transform 2D sketches into 3D models.

Cheers,
Frank Sully

[Frank Sully] Google Gave Its Helper Robots AI Language Skills to Better Work With Humans Edd...

Frank Sully — 9/13/2022 1:26:20 PM

Google Gave Its Helper Robots AI Language Skills to Better Work With Humans

Edd Gent

People have been dreaming of robot butlers for decades, but one of the biggest barriers has been getting machines to understand our instructions. Google has started to close the gap by marrying the latest language AI with state-of-the-art robots.

Human language is often ambiguous. How we talk about things is highly context-dependent, and it typically requires an innate understanding of how the world works to decipher what we’re talkingabout. So while robots can be trained to carry out actions on our behalf, conveying our intentions to them can be tricky.

If they have any ability to understand language at all, robots are typically designed to respond to short, specific instructions. More opaque directions like “I need something to wash these chips down” are likely to go over their heads, as are complicated multi-step requests like “Can you put this apple back in the fridge and fetch the chocolate?”

In contrast, a new breed of massive language models inspired by Open AI’s groundbreaking GPT-3 are capable of some impressive linguistic feats. By training on enormous amounts of written material scraped from the web, these AI systems are able to generate high-quality prose, power convincing chatbots, and answer complicated questions about text.

Google has attempted to combine the two in a new project aimed at boosting robots’ ability to understand us. By combining its PaLM large language modelwith robots made by Ever yday Robots—a spinoff from Alphabet’s “moonshot factory,” X—they’ve built prototype mechanized butlers that can do a human’s bidding around the house.

The robots, which roll around on wheels and feature a single robotic arm and a sensor-packed head, were first trained to carry out a variety of basic actions by human operators who remotely controlled them through a series of tasks.

Engineers then created new control software that taps into PaLM’s language skills to translate spoken or written commands from a human into the actions required to achieve it. The software takes advantage of an approach called “chain of thought prompting” that Google unveiled earlier this year, which enables models to break down problems into a series of intermediate steps.

It uses this to divide requests into smaller sub-problems that it can solve with its pre-trained suite of actions. For instance, “get me a Coke” might be converted into “go to the kitchen, open the fridge, pick up a Coke, and return to the living room.”

The robots were given 101 instructions by human users and were able to come up with a sensible response 84 percent of the time, and actually pull them off seamlessly 74 percent of the time.

That represented a 14 percent and 13 percent improvement, respectively, when compared to robots using a less powerful language model than PaLM, Google’s head of robotics Vincent Vanhoucke said in a blog post. The robots powered by PaLM also saw a 26 percent boost in their ability to carry out complicated multi-step requests.

This is still very much a work in progress, though, and the robots can still be thrown off by things as simple as a change in lighting or moving objects out of their familiar positions, according to Wired.It’s not clear whether the language comprehension problem is really more pressing than actually getting robots to successfully carry out tasks in the ever-changing real world.

But the researchers hope the benefits could run in the other direction too, by giving large language models a way to interact with the physical world. While it isn’t yet clear how this project could be used to actually retrain these models, it could be one way to start grounding AI’s language skills in the real world.

So whether or not this line of research ever leads to robotic butlers becoming a reality, it seems likely to push the fields of both robotics and AI towards new and powerful capabilities.

Image Credit: Everyday Robots

singularityhub.com

[Frank Sully] Amazon Is Using ‘Acquisition’ Of Robotic Companies for Autonomous Growth by ...

Frank Sully — 9/13/2022 1:11:31 PM

Amazon Is Using ‘Acquisition’ Of Robotic Companies for Autonomous Growth

by Market Trends

September 13, 2022

Amazon is attempting to scale up with initiatives such as salary hikes, mergers and acquisitions, and partnerships with third partiesAmazon, the eCommerce giant and a warehouse company, is not new to acquiring robotic companies. Starting with the acquisition of Kiva Systems in 2012 for $775 million has come a long way with the recent acquisition of iRobots for a whopping $1.7 billion. And recently it acquired Cloostermans, a Belgian Robotics company, it has been using the services since 2019 for eCommerce operations and scaling up its R&D and deployment operations. “We’re thrilled to be joining the Amazon family and extending the impact we can have at a global scale. Amazon has raised the bar for how supply chain technologies can benefit employees and customers, and we’re looking forward to being part of the next chapter of this innovation”, said Frederik Berckmoes-Joos, CEO of Cloostermans, in a statement for a blog post published by Amazon. Around 200 Cloostermans’ employees would join Amazon’s workforce. Without disclosing the financial terms of the deal, it revealed that operations for the acquired Belgium-based company will continue from its base, located in Hamme after the deal concludes.

Prima facie, might seem like a normal business merger and acquisition initiative which probably is for very valid reasons, but reports point out that it has been ramping up robotics acquisitions to meet the demands that arise out of its ever-expanding business operations. A leaked internal memo, reported by Recode, warns of severe staff shortage, which may put Amazon’s service quality, reputation, and growth plans at risk. Since the last decade, it has been expanding its operations, including in Europe, all while ramping up its hiring initiative all over the world. Experts are of opinion that Amazon’s workplace culture which is focused on “customer obsession” – which made Amazon a convenient work model the world has not seen before – is responsible for the surge in expansion and hence the acquisitions.

Cloostermans, going by its antecedents, strikes as a well-established company. Set up in 1884, it was largely a privately run family business held by the last six generations. Given the fact that Amazon is one of Cloostermans’ biggest customers, the deal might have gone through seamlessly. Apparently, Amazon is attempting to scale up its operations using a mixed bag of initiatives such as salary hikes, mergers and acquisitions, and partnerships with third parties, which Cloosterman was part of, providing robots for packaging and moving operations. “We have more than 5,20,000 robotic drive units, and have added over a million jobs, worldwide. We have more than a dozen other types of robotic systems in our facilities around the world, including sort centers and air hubs. From the early days of the Kiva acquisition, our vision was never tied to a binary decision of people or technology. Instead, it was about people and technology working safely and harmoniously together to deliver for our customers. That vision remains today”, asserts Amazon in one of its blog posts. Clearly, Amazon is turning adversity into an opportunity to not only expand its operations but become self-dependent, and it reflects in its statement to TechCrunch, “We have a vision for a future where people work alongside robotics to further improve safety and the workplace experience” when it acquired Canvas Tech in 2019.

analyticsinsight.net

[Frank Sully] Truck Platooning Market to Hit USD 13 Billion by 2030: Global Market Insights In...

Frank Sully — 9/13/2022 12:49:40 PM

Truck Platooning Market to Hit USD 13 Billion by 2030: Global Market Insights Inc.

Global Market Insights Inc.

Sep 13, 2022

Major truck platooning market players include AB Volvo, Bendix Commercial Vehicle Systems LLC, Continental AG, Daimler AG, Hino Motors, Ltd., IVECO S.p.A, NVIDIA Corporation, Omnitracs, Peloton Technology, ZF Friedrichshafen AG, and others.

SELBYVILLE, Del., Sept. 13, 2022 /PRNewswire/ -- The truck platooning market is expected to record a valuation of USD 13 billion by 2030, according to the latest research study by Global Market Insights Inc.

A growing demand for advanced automotive solutions to reduce operating costs and fuel consumption will boost the industry trends. Platooning systems utilize autonomous driving support and networking technologies to operate two or more commercial vehicles together as convoys, which allows for maintaining a predefined distance between each other on highways.

Truck Platooning Market

The technology has gained recognition across vehicle manufacturers and transportation service providers that are seeking new cost-effective solutions. With proximity as close as 12 meters apart, platooning services enable effective airflow around the fleet, thereby reducing overall fuel consumption.

Increasing dependence on next-generation technology is a key factor that could restrain truck platooning market growth. Truck platooning heavily relies on intelligent transportation, which consists of IoT-connected apps, smart mobility, and a fully equipped infrastructure of transportation networks. Current road systems in most countries fail to support the construction of potential routes that can accommodate long-haul truck platoons.

The fully autonomous segment in the truck platooning market is poised to witness a more than 35% growth rate through 2030. This advanced platooning technology involves the integration of a wide range of sensors and complex communication systems which together form a fully autonomous convoy of trucks that can effectively communicate and control vehicles. The technology enables smooth operation of larger fleets, whilst ensuring higher fuel and operational efficiency.

The vehicle-to-vehicle (V to V) communication technology segment is anticipated to reach USD 5 billion by 2030. With the growing use of adaptive cruise control systems which help enhance truck speed autonomously, V to V communication technology is likely to gain momentum in the coming years. This form of communication allows sharing of messages between vehicles to deliver information associated with speed and traffic conditions.

In 2021, the truck platooning market from the blind spot warning (BSW) segment surpassed USD 125 million. There is a high demand for BSW systems in customized luxury vehicles and heavy-duty trucks. These systems monitor the areas along the full length of the truck trailer and can detect vehicles in the blind spot and show a warning in the side-view mirror. Industry players are increasingly focusing on technological development and innovation of blind spot detection systems. The technology can be used to capture the rear view of large commercial vehicles to mitigate collisions while reversing.

Latin America truck platooning market is projected to register USD 490 million by 2030. The region has a solid footprint of automotive component manufacturers that are signing long-term partnerships with the original equipment manufacturers (OEMs). There is an imposition of stringent regulations and frameworks with respect to the automotive and freight industries in recent years. The growing focus on enhancing the safety of domestic consumers will benefit truck platooning solution providers in the region.

Key companies operating in the truck platooning market are Daimler AG, Hino Motors, Ltd., IVECO S.p.A, NVIDIA Corporation, Omnitracs, AB Volvo, Bendix Commercial Vehicle Systems LLC, Continental AG, Peloton Technology, Robert Bosch GmbH, Scania, TomTom International BV., TuSimple, and ZF Friedrichshafen AG. These leaders are seeking to add advanced features to enhance product portfolio and drive innovation.

prnewswire.com

[Frank Sully] The Countdown Begins! Humans Have 30 Years to be Overrun by AI by Jayanti Se...

Frank Sully — 9/13/2022 10:15:04 AM

The Countdown Begins! Humans Have 30 Years to be Overrun by AI

by Jayanti

September 13, 2022

Super-powered AI

Humans risk being overrun by artificial superintelligence in 30 years

While AI experts don’t concur on many things, they all accord on one thing AI and MLtechnology is going to have gigantic effects on society and business. Google CEO Sundar Pichai comments artificial intelligence is “one of the overriding things humanities is working on,” and is more profound than our development of electricity or fire.

AI is when we provide machines (software and hardware) with human-like abilities. It means we offer machines the ability to mimic human intelligence. Machine learning (ML) means machines are trained to see, hear, speak, move, and make decisions. The dissimilarity between artificial intelligence and traditional technology is that AI has the potential to make predictions and learn on its own. Humans configure AI to achieve a goal. After that, they are taught data so it learns how best to achieve that goal. Once it grasps well enough, we turn artificial intelligence loose on fresh data, which it can then use to achieve goals on its own without any direct instruction from a human. AI carries out all this by making predictions. Artificial intelligence analyzes data, then uses that data to make (nearly) accurate predictions. The benefit of using AI is that it can perform the same tasks as humans but at a much faster rate, with lesser mistakes. There are generally three forms of modern AI: Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Super Intelligence (ASI). There are many potential benefits of more advanced artificial intelligence and machine learning. The medical field, for example, would widely benefit from having robotic doctors as proficient as humans.

But, as every coin has two faces, there are risks involved in AI and ML. Namely, if an AI program infinitely smarter than us became malevolent, there would be virtually no plan to stop it. While it could provide societal benefits, a malevolent Artificial Super Intelligence (ASI) program keeps the potential to terminate mankind and should not be created or developed. AI researchers and technology executives like Elon Musk openly expressed their deep concern about human extinction caused by machine learning. Some other experts also believe “a machine with human-level intelligence could be generated in the coming 30 years and could represent a threat to life on Earth.”

Present and future threats

According to Dr. Lewis Liu, CEO of an AI-driven company called Eigen Technologies, some artificial have already “gone dark” by this time. “Even the ‘dumb, non-conscious models we have presented may contain ethical issues around inclusion,” Dr. Liu conveyed to The US Sun. “That kind of mischief stuff is already happening today. “Research from Johns Hopkins University thinks that artificial intelligence algorithms tend to show biases that could discriminate against targeting people of color and women while executing their operations. The American Civil Liberties Union also expressed their concern that AI could “deepen racial inequality” as huge selective processes like hiring and housing are automated. “General AI or AI Superintelligence is just going to perform at a much broader scale, larger propagation of these problems,” Dr. Liu showed his concern. The all-out, Terminator-style war of man versus machine does not seem to be an impossibility either. A poll in futurist Nick Bostrom’s book Superintelligence reveals that almost 10% of experts believe a computer with human-level artificial Super Intelligence strives for a life-threatening crisis for humanity. A giant misconception about AI is that it’s restricted to its black box that can just be unplugged if it intends to hurt us. Some experts accept that the threat landscape should be taking sentient artificial intelligence into account because we are not sure when it will come online, or how it will react to humans.

Preventing Judgement Day

Dr. Liu sadly conveyed “it’s going to be a pretty s***y world” if we achieve artificial superintelligence with the existing lax style of technology regulation. He commented that the development of oversight where the data that powers AI models is scoured for partiality. If the data training a model is sourced from the public, then programmers should have to achieve users’ consent to apply it. Regulation in the US is short of emphasizing “a human check on the outputs” but current developments in China have begun to highlight keeping artificial intelligence under human control.

analyticsinsight.net

[Frank Sully] Metaverse Market Size is Projected to Grow at a CAGR of 40.07% During 2022-2027 ...

Frank Sully — 9/13/2022 8:32:19 AM

Metaverse Market Size is Projected to Grow at a CAGR of 40.07% During 2022-2027 | Nvidia Corporation, Facebook Inc.

Metaverse Market Size Report

The rising number of gaming zones in commercial areas is also bolstering the global metaverse market.

SHERIDAN, WY, USA, September 13, 2022 / EINPresswire.com/ -- According to IMARC Group’s latest report, “Metaverse Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2022-2027”, offers a comprehensive analysis of the industry, which comprises insights on the metaverse market size. The report also includes competitor and regional analysis, and contemporary advancements in the market. The global metaverse market is expected to exhibit a CAGR of 40.07% during 2022-2027.

What is the metaverse market?

A metaverse refers to a digital reality that usually incorporates social media platforms, online gaming, augmented reality (AR), virtual reality (VR), and cryptocurrencies to enable users to interact virtually. It is self-sufficient, infinite, persistent, interoperable, and provides real-time live experiences. Consequently, the metaverse is gaining extensive traction across various countries.

COVID-19 Impact:

We are regularly tracking the direct effect of COVID-19 on the market, along with the indirect influence of associated industries. These observations will be integrated into the report.

Request to Get the Sample Report: imarcgroup.com

Market Trends and Drivers:

The escalating demand for online games, on account of the emerging trend of digitization, the increasing penetration of high-speed internet connectivity, the growing sales of smartphones, etc., is primarily driving the metaverse market. Additionally, the rising number of gaming zones in commercial areas is also bolstering the global market. Besides this, the inflating popularity of virtual goods and digital currencies is propelling the utilization of the metaverse in non-fungible tokens (NFTs), which is acting as another significant growth-inducing factor.

Moreover, the widespread adoption of the metaverse in small and medium-scale enterprises (SMEs) that allows individuals to have real-time interactions and experiences, owing to the introduction of numerous cloud-based solutions and remote working models, is further catalyzing the market growth.

Apart from this, the metaverse is used in the banking, financial services and insurance (BFSI) industry to minimize the interaction between agents and customers as well as streamline operations. Furthermore, the elevating consumer inclination towards online shopping apps is expected to fuel the metaverse market in the coming years.

Competitive Landscape with Key Players:

The competitive landscape of the global metaverse market has been studied in the report with the detailed profiles of the key players operating in the market.

Key Players Included in Global Metaverse Market Research Report:

• Alibaba Group Holding Limited
• Decentraland, Electronic Arts Inc.
• Facebook Inc.
• Nextech AR Solutions Inc.
• Nvidia Corporation
• Roblox Corporation
• The Sandbox and Unity Technologies

Key Highlights of the Market Segmentation:

The report has segmented the global metaverse market on the basis of material, application and region.

Breakup by Component:

• Hardware
• Software
• Service

Breakup by Technology:

• Blockchain
• Virtual Reality and Augmented Reality
• Mixed Reality
• Others

Breakup by Application:

• Gaming
• Online Shopping
• Content Creation and Social Media
• Events and Conference
• Digital Marketing
• Testing and Inspection
• Others

Breakup by Industry Vertical:

• BFSI
• Retail
• Media and Entertainment
• Education
• Aerospace and Defense
• Automotive
• Others

Breakup by Region:

• North America
o United States
o Canada

• Asia-Pacific
o China
o Japan
o India
o South Korea
o Australia
o Indonesia
o Others

• Europe
o Germany
o France
o United Kingdom
o Italy
o Spain
o Russia
o Others

• Latin America
o Brazil
o Mexico
o Others

• Middle East and Africa

einnews.com

[Julius Wong] A breakthrough discovery in carbon capture conversion for ethylene production ...

Julius Wong — 9/12/2022 9:13:41 AM

A breakthrough discovery in carbon capture conversion for ethylene production

Abstract illustration of atoms passing through water and an electrified membrane under a shining sun. Credit: Meenesh Singh

A team of researchers led by Meenesh Singh at University of Illinois Chicago has discovered a way to convert 100% of carbon dioxide captured from industrial exhaust into ethylene, a key building block for plastic products.

Their findings are published in Cell Reports Physical Science.

While researchers have been exploring the possibility of converting carbon dioxide to ethylene for more than a decade, the UIC team's approach is the first to achieve nearly 100% utilization of carbon dioxide to produce hydrocarbons. Their system uses electrolysis to transform captured carbon dioxide gas into high purity ethylene, with other carbon-based fuels and oxygen as byproducts.

The process can convert up to 6 metric tons of carbon dioxide into 1 metric ton of ethylene, recycling almost all carbon dioxide captured. Because the system runs on electricity, the use of renewable energy can make the process carbon negative.

According to Singh, his team's approach surpasses the net-zero carbon goal of other carbon capture and conversion technologies by actually reducing the total carbon dioxide output from industry. "It's a net negative," he said. "For every 1 ton of ethylene produced, you're taking 6 tons of CO2 from point sources that otherwise would be released to the atmosphere."

Previous attempts at converting carbon dioxide into ethylene have relied on reactors that produce ethylene within the source carbon dioxide emission stream. In these cases, as little as 10% of CO2 emissions typically converts to ethylene. The ethylene must later be separated from the carbon dioxide in an energy-intensive process often involving fossil fuels.

In UIC's approach, an electric current is passed through a cell, half of which is filled with captured carbon dioxide, the other half with a water-based solution. An electrified catalyst draws charged hydrogen atoms from the water molecules into the other half of the unit separated by a membrane, where they combine with charged carbon atoms from the carbon dioxide molecules to form ethylene.

Among manufactured chemicals worldwide, ethylene ranks third for carbon emissions after ammonia and cement. Ethylene is used not only to create plastic products for the packaging, agricultural and automotive industries, but also to produce chemicals used in antifreeze, medical sterilizers and vinyl siding for houses.

Ethylene is usually made in a process called steam cracking that requires enormous amounts of heat. Cracking generates about 1.5 metric tons of carbon emissions per ton of ethylene created. On average, manufacturers produce around 160 million tons of ethylene each year, which results in more than 260 million tons of carbon dioxide emissions worldwide.

In addition to ethylene, the UIC scientists were able to produce other carbon-rich products useful to industry with their electrolysis approach. They also achieved a very high solar energy conversion efficiency, converting 10% of energy from the solar panels directly to carbon product output. This is well above the state-of-the-art standard of 2%. For all the ethylene they produced, the solar energy conversion efficiency was around 4%, approximately the same rate as photosynthesis.

phys.org

[Cogito Ergo Sum] The Grand Banks are a continuation of the NA Continental Shelf They do not appe...

Cogito Ergo Sum — 9/5/2022 6:49:14 PM

The Grand Banks are a continuation of the NA Continental Shelf

They do not appear out of nowhere like Atlantis :)

U R being arcane

[stuffbug] That's where the Grand Banks are. Maybe you were thinking offshore Newfoundland...

stuffbug — 9/5/2022 6:35:13 PM

That's where the Grand Banks are.

Maybe you were thinking offshore Newfoundland.

[Cogito Ergo Sum] Do not need be that far off shore fishing is shot anyway [youtube video] th...

Cogito Ergo Sum — 9/5/2022 6:31:44 PM

Do not need be that far off shore

fishing is shot anyway

the tech is just a dream still ...

[stuffbug] Grand Banks ??? iceberg alley, up to 40 ft waves, 200 miles offshore ..... How ...

stuffbug — 9/5/2022 6:29:52 PM

Grand Banks ???
iceberg alley, up to 40 ft waves, 200 miles offshore .....

How many more challenges do you want to overcome with expensive engineering design?

[Cogito Ergo Sum] Yep.... Had this saying when I played ping pong ... Good shot but missed :)

Cogito Ergo Sum — 9/5/2022 4:57:40 PM

[Julius Wong] << need a working prototype >> A good idea may not work.

Julius Wong — 9/5/2022 4:54:52 PM

[Cogito Ergo Sum] interesting ... read it through.. lots of questions .. seems like the Grand Bank...

Cogito Ergo Sum — 9/5/2022 2:18:11 PM

interesting ... read it through.. lots of questions .. seems like the Grand Banks might be a good candidate ...

need a working prototype .. as yet the answers are all Blowin' in the Wind :)

[Frank Sully] Launched in 1977, the twin Voyager probes are NASA’s longest-operating mission a...

Frank Sully — 9/5/2022 9:25:21 AM

Launched in 1977, the twin Voyager probes are NASA’s longest-operating mission and the only spacecraft ever to explore interstellar space. For two decades after launch, the spacecraft were planetary explorers, giving us up-close views of the gas giants Jupiter, Saturn, Uranus, and Neptune. Now, as they reach distances far beyond the hopes of their original designers, the aging spacecraft challenge their team in new ways, requiring creative solutions to keep them operating and sending back science data from the space between the stars. As we celebrate the 45th anniversary of these epic explorers, join Voyager deputy project scientist Linda Spilker and propulsion engineer Todd Barber for a live Q&A. (30 Minutes)

[Frank Sully] In this second episode of #MeetAGoogleResearcher, Drew Calcagno speaks with Kani...

Frank Sully — 9/5/2022 9:23:18 AM

In this second episode of #MeetAGoogleResearcher, Drew Calcagno speaks with Kanishka Rao of Google Research and Daniel Ho of Everyday Robots, researchers who helped combine the PaLM-SayCan robotics algorithm with the advanced capabilities of a helper robot. (14 Minutes)

[Frank Sully] Speaker John Enright, Principal Engineer, Amazon Robotics, tells the story of de...

Frank Sully — 9/5/2022 9:19:55 AM

Speaker John Enright, Principal Engineer, Amazon Robotics, tells the story of developing precision autonomy on Proteus, the new cost-effective autonomous mobile robot designed to work safely and efficiently alongside humans in shared, collaborative spaces. (Ten Minutes)

[Frank Sully] Spot News: When you put the Lockheed Martin Missiles and Fire Control Operations...

Frank Sully — 9/5/2022 9:18:43 AM

Spot News: When you put the Lockheed Martin Missiles and Fire Control Operations Team together with Boston Dynamics, you get something not nearly as exciting as you were probably expecting. (1 Minute)

[Julius Wong] Contra-rotating floating turbines promise unprecedented scale and power [graph...

Julius Wong — 9/4/2022 9:38:27 AM

Contra-rotating floating turbines promise unprecedented scale and power

Contra-rotating vertical turbines could radically improve yield and reduce LCoE for floating offshore wind projects, according to World Wide Wind
World Wide Wind

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The top turbine, mounted to a central blade, spins in one direction, while the bottom, and the tower's exterior, spins in the other, with the generator at the bottom
World Wide Wind

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The company says this design leaves much less turbulence behind it, allowing a much higher density of towers per given site
World Wide Wind

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WWW claims its bottom-heavy, tilting, contra-rotating coaxial turbines solve offshore wind's scale limitations, and will grow to 400 m high, with a 40 MW capacity
World Wide Wind

Norway's World Wide Wind has a radically different take on offshore wind power. These floating, vertical-axis wind turbines (VAWTs) feature two sets of blades, tuned to contra-rotate – and they promise more than double the output of today's biggest turbines.

Taking wind farms way offshore can certainly help make them less obtrusive, and open up a lot more opportunities – but as the ocean gets deeper, conventional horizontal-axis wind turbines (HAWTs) begin making less and less sense. HAWTs need to hold a lot of heavy components – drivetrains, gearboxes, generators and their colossal blades – right up the top of a long pole, so mounting them on floating platforms that don't want to tip over is a huge challenge – not to mention maintaining the business end of a turbine so far above the ground.

Some engineers and operators believe this could be a niche where VAWTs could shine instead. Their blades reach upward, but all their other heavy bits are at the bottom, so their natural tendency is to sit upright. Also, they can accept wind energy from any direction, rather than needing to turn to face into the wind, cutting down on some more heavy gear you'd find up high on a HAWT. They're typically far less efficient than a regular three-blade HAWT, sucking less energy out of a given breeze, but on the other hand, you can place them closer together without a drop in performance, meaning they could potentially suck more energy out of a given patch of ocean.

The top turbine, mounted to a central blade, spins in one direction, while the bottom, and the tower's exterior, spins in the other, with the generator at the bottom
World Wide Wind

And so to the device at hand. World Wide Wind has proposed an entirely new type of floating VAWT specifically designed for offshore deployment and massive scalability. Indeed, it's two VAWTs in one; the lower one is fixed to the outer casing of the tower, and set to rotate one way, and the upper one is mounted to a shaft running right up the middle of the tower, and it's set to rotate the other way.

Under the surface, one turbine is fixed to the rotor, the other to the "stator," doubling the relative speed of rotation as compared to a static stator, and generating a whole bunch of electricity we can burn our toast with. The company calls this a contra-rotating vertical turbine, or CRVT.

Again, the heaviest parts and the ones requiring most maintenance are at the bottom, below the buoyant pontoon, right down near where the tethers and power cable attach. But the whole thing isn't designed to sit perfectly upright; these enormous towers will tilt with the wind. World Wide Wind says this, and the blade designs, which sweep a conical area, helps to reduce the turbulent wake downstream of each floating tower, allowing operators to cram even more of these things into a given site. The ability to tilt will also help these things resist sudden, violent wind gusts and damaging vibrations.

The company says this design leaves much less turbulence behind it, allowing a much higher density of towers per given site
World Wide Wind

You need serious scale to get the best out of wind energy, and these guys aren't holding anything back on that front. The world's largest wind turbine as it stands is the mammoth MingYang Smart Energy 16.0-242. Standing 242 m (794 ft) tall, it has a rated capacity of 16 MW.

World Wide Wind plans to absolutely dwarf that piddly windmill. This design, says the company, is far easier to scale than any HAWT, and could grow up to a ridiculous 400 m (1,312 ft) in height, with a monster 40-megawatt capacity per unit. In an interview with Recharge , company representatives appear to have suggested a projected Levelized Cost of Energy (LCoE) of less than US$50 per megawatt – less than half the LCoE the US Energy Information Administration projects for the average offshore wind project going to market in 2027.

The company tells Recharge it's working to accelerate development of the CRVT through rapid prototyping. The targets are to have a 3-MW model up and running by 2026, and the big mama 40-MW machine as soon as 2029.

WWW claims its bottom-heavy, tilting, contra-rotating coaxial turbines solve offshore wind's scale limitations, and will grow to 400 m high, with a 40 MW capacity
World Wide Wind

Will it work? It's hard to say. The startup provides no supporting research, or evidence that it's tested micro-scale prototypes. It's unclear why the company hasn't gone with Darrieus-style turbine blades, which connect back to the central axis at the top, and tend to be both structurally stronger and more efficient. One wonders about longevity, since all VAWT blades are subjected to strong forces from every angle as they spin – and about the efficiency losses, lifespan and replacement procedures for the gigantic bearings you'd need to support and spin a 400-meter-long shaft inside a counter-rotating 400-meter-long tube, with the mass tilted off-center most of the time. In seawater, of course, for decades.

Not to mention, it's apparently getting hard to find test locations for wind tech in the North Sea, because there are too many other test projects "almost queueing up" in the region, according to Norway's Teknisk Ukeblad.

On the positive side, there's not a tie to be seen amongst the leadership team, so clearly they're feeling confident and relaxed about this whole thing. World Wide Wind claims partnerships with Uppsala University, Sinted, North Wind, Kjeller Vindteknik, Norwegian Energy Partners, and the Norwegian Offshore Wind Cluster.

As with all clean energy moonshot projects, we desperately want to believe. The expansion and decarbonization of worldwide energy grids cannot possibly happen fast enough, as climate change enters its terrible toddler phase and the unthinkable consequences start becoming impossible to ignore. Giant 40-megawatt coaxial towers way out at sea, undercutting the LCoE of today's offshore wind, could make a huge contribution in the existential battle of the coming century. But we don't need renders, diagrams and promises, we need tangible results – and we need them yesterday.

We've reached out to World Wide Wind, and we hope to bring you a closer look at this technology as soon as possible.

Source: World Wide Wind via Recharge

newatlas.com

[Julius Wong] Designing a way to make oxygen injectable [graphic] Jarad Mason and his team h...

Julius Wong — 9/4/2022 9:34:01 AM

Designing a way to make oxygen injectable

Jarad Mason and his team have created permanently “porous” water, allowing gases to be stored at high concentrations within the liquid. Credit: Kris Snibbe/Harvard Staff Photographer

What if emergency medical personnel could treat a desperately ill patient in need of oxygen with a simple injection instead of having to rely on mechanical ventilation or rush to get them onto a heart-lung bypass machine?

A new approach to transporting gases using a class of materials called porous liquids represents a big step toward artificial oxygen carriers and demonstrates the immense biomedical potential of these unusual fluids.

In a study published last month in Nature, a team of scientists in Harvard's Department of Chemistry and Chemical Biology detail a new approach to transporting gases in aqueous environments using porous liquids. The authors identified and tailored multiple porous frameworks that can store much higher concentrations of gases, including oxygen (O2) and carbon dioxide (CO2), than normal aqueous solutions. This breakthrough may hold the key to creating injectable sources of oxygen as a bridge therapy for cardiac arrest, creating artificial blood substitutes, and overcoming longstanding challenges in preserving organs for transplants.

"We realized that there would be a lot of benefits to using liquids with permanent microporosity to address gas-transport challenges in water and other aqueous environments," said Jarad Mason, the paper's senior author and assistant professor of chemistry and chemical biology. "We've designed fluids that can transport O2 at densities that exceed that of blood, which opens up exciting new opportunities for transporting gases for a variety of biomedical and energy applications."

Liquids with permanent microporosity are a new class of materials that are composed of microscopic porous particles dispersed in a liquid medium. Imagine tiny, recyclable, sponge-like bits capable of soaking up gases in their holes and releasing them. Until now, all porous liquids have consisted of microporous nanocrystals or organic cage molecules dispersed in organic solvents or ionic liquids that are too large to diffuse through the pore entrances. The researchers developed a new strategy to create aqueous porous liquids—termed "microporous water"—with high gas capacities based on thermodynamics.

The work was led by members of Mason's lab, including doctoral students Daniel P. Erdosy, Malia Wenny, Joy Cho, Miranda V. Walter, postdoctoral researcher Christopher DelRe, and undergraduate Ricardo Sanchez. Computational simulations and biological experiments were also performed in collaboration with scientists at Boston Children's Hospital and Northwestern University, including Felipe Jiminez-Angeles, Baofu Oiao, and Monica Olvera de la Cruz.

Water is a polar molecule, making it a great solvent for other polar molecules such as ethanol and sugar, but it is much worse at dissolving non-polar molecules like O2 gas. As such, pure water can carry 30 times less oxygen than red blood cells. The extremely low solubility of gases in water has imposed a hard limit on many biomedical and energy-related technologies that require the transport of gas molecules through aqueous fluids. This new mechanism for gas transportation overcomes the low solubility of gases in water and enables rapid gas transport.

Inspired by pores in certain proteins that are accessible to water molecules but overall remain dry in aqueous solutions, the team proposed that microporous nanocrystals with hydrophobic internal surfaces and hydrophilic external surfaces could be designed to leave the microporous framework permanently dry in water and available to absorb gas molecules.

"We had to reconcile two seemingly contradictory properties," Erdosy said. "We designed the internal surface to be hydrophobic and water-repelling, and the external surface to be hydrophilic and water-loving, because otherwise the fluid would phase separate like oil and water."

The team synthesized the materials in their lab and tested their ability to absorb and release gases. They found that microporous water can reversibly transport extremely high densities of gases through water-based environments. Using this strategy, the team developed a porous liquid that can carry a higher density of O2 than is even present in the pure gas. These aqueous porous liquids display remarkable shelf-stability, allowing them to be stored at room temperature for months before use.

"With some more development, you could imagine storing oxygen in a microporous liquid on an ambulance to have it ready to inject into a person whenever its needed," Wenny said.

The lab plans to conduct more experiments on microporous water to test its biomedical applications, while continuing to explore other potential uses for the materials.

"We want to develop more materials and animal models to create and test an oxygen carrier in vivo," Erdosy said. "We also have a more energy-focused project planned on using microporous water to address gas transport challenges in electrocatalysis."

phys.org

[Frank Sully] AI 2041: Book Review Summary Well, I’ve read and reviewed six of ten of the fut...

Frank Sully — 8/30/2022 1:07:24 PM

AI 2041: Book Review Summary

Well, I’ve read and reviewed six of ten of the futuristic, speculative stories and discussion about the status quo and future of various important AI technologies, including gargantuan natural language processing AI models, autonomous vehicles, virtual reality and the MetaVerse

AI 2041: First Thoughts

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Book Review Continued: AI 2041

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Book Review “AI 2041”: Part 3

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The fourth story discussed above, “Contactless Love” discusses AI advances in biotechnology. One of the most profound AI advances is Google’s subsidiary’s DeepMind’s solution of Protein Folding and the release of a massive free database.

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“Contactless Love” also discusses the use of medical and consumer robotics. Google’s “Moon Shot X” was recently renamed to Everyday Robotics:

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AI 2041: Fifth Story and the Metaverse

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AI 2041 Book Review Continued - “The Holy Driver”

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[Frank Sully] AI 2041 Book Review Continued - “The Holy Driver” Message 33980096

Frank Sully — 8/30/2022 10:11:20 AM

[Frank Sully] Fully autonomous robotic restaurant to launch in San Francisco August 22, 2022...

Frank Sully — 8/23/2022 1:50:03 PM

Fully autonomous robotic restaurant to launch in San Francisco

August 22, 2022

SAN FRANCISCO, Aug. 22, 2022 /PRNewswire/ — Mezli, a startup based in San Mateo, CA, has announced the launch of its fully-autonomous robotic restaurant, the first of its kind in the world. The restaurant, located in the Spark Social food park in San Francisco, will be celebrating its grand opening on Sunday, August 28th.

Mezli’s restaurant will be the first-ever to serve a full hot menu to customers without requiring any human intervention. This automated approach allows Mezli to offer its menu of Mediterranean grain bowls, sides, and drinks at a significantly lower price point than similar fast-casual restaurants – its grain bowls start at $6.99 – providing a healthy, convenient and affordable dining option for neighborhood residents and workers.

Mezli was founded by a team of Stanford engineers: Alex Kolchinski, Alex Gruebele, and Max Perham. As graduate students at Stanford, Mezli’s founders found that they had no nearby food options that were convenient, affordable, and healthy. Putting their technical backgrounds to use, they teamed up with Michelin-star chef Eric Minnich to solve the problem with a combination of robotic and culinary innovation.

The team started full-time work on Mezli in January of 2021 while participating in the Y Combinator startup accelerator and working out of the Kitchentown food innovation center. During 2021, the team opened a pop-up restaurant, built a prototype robot, and brought on a number of employees, investors, including roboticist Pieter Abbeel and restaurateur Zaid Ayoub, and advisors, including Charles Bililies of Souvla.

Now, Mezli is launching its first fully-robotic location, which will also be the first fully-autonomous restaurant in the world. Previous automated culinary concepts have either achieved partial automation of fresh hot menus, but required human involvement in the process, or achieved full automation of simpler menus, like rehydrated noodle bowls and made-to-order cold salads. Mezli’s restaurant will be the first to autonomously serve customers a fully customizable, made-to-order hot menu, with no human intervention required at all.

Mezli’s approach of unlocking fresh, healthy food at affordable prices by reimagining the nature of food service from the ground up has already attracted attention.

“It resonates with me,” Mezli’s investor Pieter Abbeel said. “Anything physical is always harder than you think, so if you don’t come up with a first principles way to solve it, it will be difficult. In addition, from day one, the food was being served and that is compelling.”

Looking ahead, after the launch at Spark Social, the Mezli team plans to expand to multiple locations while also widening the culinary options available through the Mezli platform. Because robotic Mezli restaurants are smaller and cheaper to build than traditional fast-casual restaurants, they can be deployed in a wider range of locations, at a smaller carbon footprint per location, while serving fresh, healthy meals at a low price point. It’s exactly that offering that Mezli’s team plans to eventually make available nationwide.

producebluebook.com

[Frank Sully] Cloud Robotics Market Is Expected to Reach $43.73 Billion by 2031: Allied Market...

Frank Sully — 8/23/2022 1:31:40 PM

Cloud Robotics Market Is Expected to Reach $43.73 Billion by 2031: Allied Market Research

Increase in the popularity of remote working, surge in demand for remote working tools, rapid industrialization, and rise in need for centralized monitoring and control of industrial tools are expected to drive the growth of the global clous robotics market. Significant increase in demand for robotics and automation solutions in various end-use industries during the pandemic had a positive impact on the market. August 19, 2022

Source: Allied Market Research

Portland, OR , Aug. 19, 2022 (GLOBE NEWSWIRE) -- According to the report published by Allied Market Research, the global cloud robotics market generated $4.62 billion in 2021, and is projected to generate $43.73 billion by 2031, manifesting a CAGR of 25.3% from 2022 to 2031. The report offers a detailed analysis of the top winning strategies, evolving market trends, market size and estimations, value chain, key investment pockets, drivers & opportunities, competitive landscape and regional landscape. The report is a useful source of information for new entrants, shareholders, frontrunners and shareholders in introducing necessary strategies for the future and taking essential steps to significantly strengthen and heighten their position in the market.

COVID-19 Scenario:

The outbreak of COVID-19 had had a positive impact on the growth of the global cloud robotics market, owing to the occurrence of lockdowns in various countries across the globe.

Lockdowns resulted in the decreased number of workforces across various industries, which subsequently surged the demand for cloud robotic as more and more industries were in need for centralized monitoring to take control of various industrial tools.

Thus, rapid industrialization and the growth in need for automation boosted the demand for cloud robotics.

In addition, evolving demand of the manufacturing industries along with the surge in demand for robotics and automation solutions in the healthcare and chemical industries further drive the growth of the market.

The report offers a detailed segmentation of the global cloud robotics market based on component, service model, robot type, enterprise size, industry vertical, and region.

Based on component, the software segment held the dominating market share in 2021, holding nearly three-fourths of the global market, and is expected to maintain its leadership status during the forecast period. The service segment, on the other hand, is expected to cite the fastest CAGR of 27.3% during the forecast period.

Based on service model, the SaaS segment held the largest market share in 2021, garnering nearly half of the global market, and is expected to maintain its leadership status during the forecast period. The IaaS segment, on the other hand, is expected to cite the fastest CAGR of 27.1% during the forecast period.

Based on robot types, the industrial robots segment held the dominating market share in 2021, garnering nearly three-fourths of the global market, and is expected to maintain its leadership status during the forecast period. The service robots segment, on the other hand, is expected to cite the fastest CAGR of 27.5% during the forecast period.

Based on industry vertical, the manufacturing segment held the dominating market share in 2021, holding around four-fifths of the global market, and is expected to maintain its leadership status during the forecast period. The aerospace and defense segment, on the other hand, is expected to cite the fastest CAGR of 28.8% during the forecast period.

Based on region, the market across Asia-Pacific held the largest market share in 2021, holding more than two-thirds of the global cloud robotics industry, and is expected to maintain its leadership status during the forecast period. In addition, the same region is expected to cite the fastest CAGR of 26.0% during the forecast period. The report also analyses other regions such as North America, LAMEA and Europe.

The key players analyzed in the global cloud robotics market report include IBM, Kuka AG, Microsoft, Ortelio Ltd., Rapyuta Robotics Co. Ltd., Rockwell Automation Inc., ABB, Amazon Robotics, C2RO, Calvary Robotics, CloudMinds, Fanuc Corporation, Google, Hit Robot Group, Huawei, V3 Smart Technologies, and XTend Robotics.

globenewswire.com

[Frank Sully] China’s robotics sector makes breakthroughs, closing in on that of advanced coun...

Frank Sully — 8/23/2022 1:15:52 PM

China’s robotics sector makes breakthroughs, closing in on that of advanced countries

By Ma Jingjing and Liu Yang

Published: Aug 21, 2022

Photo taken on Aug. 18, 2022 shows a 5G remote control excavator during an expo of the World Robot Conference 2022 (WRC 2022) in Beijing, capital of China. The WRC 2022 is held from Aug. 18 to 21 in Beijing. More than 500 sets of robots are displayed during the conference and over 30 of them make their world debuts in Beijing.(Photo: Xinhua)

China's robotics industry has attained remarkable and substantive achievements in recent years, and is expected to catch up with that of developed countries like Japan in less time than imagined thanks to new technologies like artificial intelligence (AI) and big data, officials and experts said during the 2022 World Robot Conference (WRC) concluded on Sunday.

Chinese robotics enterprises have made phased breakthroughs in core components such as precision decelerators, high-performance servo motors and new-type sensors, while progress has also been made in core software represented by the robot operating system and has entered into practical application, Xin Guobin, vice minister of the Ministry of Industry and Information Technology, said at the WRC.

During the four-day event held in Beijing, many Chinese companies, including specialized robot firms and traditional manufacturing giants, showcased their latest technologies and products.

Hangzhou-based Unitree Robotics attracted widespread attention as the company staged a performance involving 130 Go1 robot dogs. "The performance is only a form to showcase our robot dogs, through which customers can learn more about our products," the company told the Global Times on Sunday, noting that Unitree has been speeding up to create more application scenarios for the robots, not only in the industrial end but also entering daily lives.

According to the company, the servo motors, decelerators, controllers and most of the sensors of its quadruped robots have all achieved independent research and development. The company said that it has applied for more than 100 patents and has more than 80 licensed patents.

"China's robotics sector has formed a complete industrial chain, though there is still gap between China and advanced countries like Japan in core components such as servo motors - an electrical device that rotate parts of robots with high efficiency and precision - and decelerators," Liu Gang, director of the Nankai Institute of Economics and chief economist at the Chinese Institute of New Generation AI Development Strategies, told the Global Times on Sunday.

With the emergence of new technologies like AI and big data, it would take less time for China to catch up with these nations, he said, noting that China may even overtake them like how China's electric vehicle industry overtook Japan.

China released the 14th Five-Year Plan for the Robotics Industry in December, aiming to make the country a global center of excellence for robotics technology innovation, advanced manufacturing and integrated applications by 2025.

Currently, the self-reliance rate of making certain robots has reached 90 percent, and domestic companies' competitiveness is greatly improved with lower costs. In addition to robotics firms, domestic traditional manufacturing companies like home appliance maker Gree Electric Appliances have been engaged in the R&D of robots for smart manufacturing within its factories, contributing to the advance of robotics technologies in a variety of scenarios, Liu said.

Domestic AI firm Beijing OrionStar Technology Co takes the lead in the industry to put forward the formula of "AI + software + hardware + service = robot." Its self-researched AI technology covers intelligent voice and face recognition algorithm, indoor navigation algorithm as well as cloud big data algorithm. In addition, based on Android, they have created a full self-research navigation technology and Robot OS open system.

OrionStar told the Global Times that Chinese service robots have great potential to lead the world, as the country is recognized as enjoying the most complete supply chain systems in the world.

Moreover, China has advantages in talent with a broad talent pool, with the internet industry nurturing a large cohort of world-class engineers, product managers and digital technologists, which also contributed to the country's advantage in various aspects such as big data and AI, the company noted.

In spite of a complex international environment, global robotics enterprises accelerated opening-up and cooperation, with the robotics industrial and supply chain further integrated. In 2021, some leading robotics multinationals such as Fanuc, Yaskawa and ABB announced to step up R&D and production in China to better integrate into the market, Xin said.

"China welcomes global investors to invest in and grow their business in the country and benefit from the country's business opportunities," he stressed, noting that China will continue to encourage robotics enterprises, institutions and organizations at home and abroad to form innovation and supply chain partnerships to build open, stable and safe robotics industrial and supply chains.

China is the world's largest market for the application of robots. The output of China's industrial robots reached 366,000 units in 2021, up 68 percent on a yearly basis. The production of service robots in the country soared 49 percent year-on-year to 9.21 million units last year, according to data from the National Bureau of Statistics.

In the first half of this year, the total volume of disclosed financing in the robotics industry amounted to over 5 billion yuan ($733 million), mainly in key fields such as core parts, collaborative robots and surgery robots, official data showed.

globaltimes.cn

[Frank Sully] TOP MOST ADVANCED AND ARTIFICIAL INTELLIGENCE POWERED MILITARY ROBOTS IN 2022 b...

Frank Sully — 8/23/2022 1:03:16 PM

TOP MOST ADVANCED AND ARTIFICIAL INTELLIGENCE POWERED MILITARY ROBOTS IN 2022

by Market Trends

August 23, 2022

The way wars are fought has changed exponentially since world war II. Undetectable drones, ballistic missiles. The budget required to keep up with the advancing technologies has also increased considerably. If autonomous robots are used in wars, soldiers will have more responsibilities, not less; they will have to perform normal tasks and use robots per requirements. In this video, you will get to know about the top most advanced and artificial intelligence-powered military robots in 2022

MUTT- Multi-Utility Tactical Transport:MUTT accompanies the soldiers and carries equipment that eases travel while traveling on foot in difficult terrains. It can carry 1200 pounds of weight and provide up to 3000 watts of power, and travel 60 miles on a single fill.

RISE: RiSE, a climbing robot by Boston Robotics, has micro-clawed feet that allow it to deftly scale rough surfaces, including walls, fences, and trees. The RiSE project aims to build a bioinspired climbing robot with the unusual ability to walk on land and climb vertical terrain.

DOGO: DOGO, was developed to function as a watchdog for soldiers in battle. This robot, created by General Robotics, is the terrestrial version of the common combat drone. The most intriguing aspect of DOGO is that a fully armed commando can carry.

AVATAR III: AVATAR III is Robotex’s tactical robot. This robot improves the skills of law enforcement and first responders by enabling them to safely and quickly investigate dangerous situations. AVATAR III is fully customizable with a plug-and-play payload bay, allowing users to configure the robot to their needs.

Centaur: A skilled warfighter is one who is capable of finding, verifying, determining, and eliminating dangers, including landmines, unexploded ordnance, improvised explosive devices, and moving forces. A centaur is a medium-sized unmanned ground vehicle that may be controlled remotely.

analyticsinsight.net

[Frank Sully] AI Continues To Build The Foundation For A Remarkable Future In Biology Aug. 23...

Frank Sully — 8/23/2022 12:44:25 PM

AI Continues To Build The Foundation For A Remarkable Future In Biology

Aug. 23, 2022

Summary

DeepMind, an Alphabet-owned AI research firm, made the structural data on more than 200 million proteins from its AlphaFold tool freely available.This represents data on roughly 1 million species and covers the vast majority of known proteins on Earth.What’s also incredible is that AlphaFold’s database is, in conjunction with the European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI), freely available with a simple interface.

Black_Kira

By Christopher Gannatti

July 28, 2022, was a historic day in both biology and artificial intelligence (AI). DeepMind, an Alphabet-owned ( GOOG) ( GOOGL) AI research firm, made the structural data on more than 200 million proteins from its AlphaFold tool freely available. This represents data on roughly 1 million species and covers the vast majority of known proteins on Earth.1

In Proteins, Shape Can Determine Function

In the late 1990s into the early 2000s, the scientific community was awash with news of the race to sequence the human genome. This genome contains the instructions embedded in DNA about how cells should build certain structures, typically by forming proteins made from different combinations of amino acids.

In a sense, DNA is the instruction manual, amino acids are the building blocks and proteins are the product. Knowing the code, though important, is not enough.

Figure 1 is instructive on the point. This is the image of a protein that may protect the organism responsible for malaria from attack by the human immune system. Even if you knew the list and the order of all the amino acids, it would be difficult to go from that list to something that looks like Figure 1 in three dimensions.

Figure 1: Protein Associated with the Malaria Parasite

The importance of the shape of the protein cannot be overstated:

It can correspond to the way in which it might react in the presence of different molecules, like those associated with various drug therapies.

Variations in the shape - sometimes termed mutations - could be instructive in determining the causal factors of certain symptoms or diseases.

Parts of the shape could be used as targets. Think of the “spike protein” associated with the virus behind the COVID-19 pandemic, specifically targeted in the mRNA vaccines.

AlphaFold Represents a Leap Forward

Scientific breakthroughs are difficult, in that, in many cases, one builds on another and another and another. The process can take decades before widespread results impact the lives of the general public.

For instance, we sequenced the human genome, but that did not necessarily lead to immediate cures for all sorts of diseases or conditions. While mRNA research had been occurring for decades, the COVID-19 pandemic was a catalyst that supercharged the process of using mRNA in the specific case of the vaccines.

AlphaFold’s new database is therefore unlikely to lead to immediate cures for challenging conditions. The critical element regards how researchers who would have formerly had to undertake a cumbersome process of X-ray crystallography to determine the shape of a given protein could instead go to the database. Experimental techniques would still have their place, but less time would have to be spent on the equivalent of the blank page.

What’s also incredible is that AlphaFold’s database is, in conjunction with the European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI), freely available with a simple interface.

It also provides an estimate of the accuracy, recognizing that predictions based on AI do not always yield perfect results. Roughly 35% of the 214 million predictions are deemed highly accurate - roughly as good as experimental results. A further 45% are deemed to be accurate enough for many applications.2

Drug Discovery: Better Therapeutics Developed More Efficiently

Even before the onset of inflation at the levels seen in the summer of 2022, it was widely recognized that drug development is time-consuming and expensive. As a result, many medications carry exorbitant price tags. Any process that could mitigate this pressure without degrading the quality of the therapies would be enormously valuable.

Considering the following could be instructive as the space continues to progress:

Pipeline Growth: From 2010 to 2021, 20 smaller companies focused on AI drug discovery, typically with a focus on smaller molecules, had development pipelines that were roughly 50% as robust as those of 20 of the largest big pharma companies. We recognize that the reporting of pipelines may not be perfect and that a molecule in a pipeline is not a finished product, but activity is the first step on the path.

Pipeline Composition: This is not always disclosed, but the information available indicates that AI-focused companies tend to concentrate on well-established biological targets for their therapies, around which much is known. Data is the fuel for AI, and these companies will also want higher chances of success. Bigger pharma companies will be more likely to venture into more emerging areas of drug discovery.

Chemical Structures and Properties:It is too early to draw any robust conclusions regarding AI drug discovery efforts versus big pharma efforts on this point.

Discovery Timelines: Preliminary data appears to indicate that, while traditional approaches tend to take five or six years in preclinical phases, AI-focused drug discovery might be able to, in certain cases, take this timeline down to four years.We’d note that it’s more a story of progress than perfection, in that we appear to be some distance away from AI being able to fully create new drugs. But AI represents an entirely new set of tools that could have beneficial impacts.

AlphaFold’s database, for example, may provide drug researchers with important inputs and catalysts for different ideas, even if it doesn’t have the immediate answer or cure right there in its system.

Focus on the AI and BioRevolution Megatrends

At WisdomTree, we focus on both the AI megatrend and the BioRevolution megatrend. What we see here with the case of AlphaFold is an important case study in the fact that AI is a tool that can potentially supercharge other megatrends, in this case the BioRevolution.

It is no accident that the BioRevolution is ramping up at the same time massive amounts of data, massive amounts of processing power and other things like cloud computing are readily available. It is exciting to consider what the coming decades can bring in these areas.

1 Source: Callaway, Ewen, “’The Entire Protein Universe’: AI Predicts Shape of Nearly Every Known Protein,” Nature, Volume 608, 8/4/22.2 Source: Callaway, 8/4/22. 3 Source: Jayatunga et al, “AI in small-molecule drug discovery: a coming wave?” Nature Review: Drug Discovery, Volume 21, 3/22.

sdquarter.com

[Julius Wong] Sensor could help patients stay on top of their meds [graphic] A tiny, touch-...

Julius Wong — 8/21/2022 2:16:55 PM

Sensor could help patients stay on top of their meds

A tiny, touch-based sensor uses sweat to detect the level of lithium in the body. Credit: Jialun Zhu and Shuyu Lin

Lithium can alleviate the symptoms of bipolar disorder and depression—if taken in just the right amount. Too little won't work, while too much can bring on dangerous side effects. To precisely monitor the amount of this medication in the body, patients must undergo invasive blood tests. But today, scientists report the invention of a tiny sensor that detects lithium levels from sweat on the surface of a fingertip in as little as 30 seconds, without a trip to the clinic.

The researchers will present their results today at the fall meeting of the American Chemical Society (ACS).

Not only must lithium be taken at a certain dosage, but patients often struggle to take it as prescribed and may miss pills. So, when the medication doesn't appear to be working, health care providers need to know how much medication the patient is actually swallowing. But current options for monitoring have significant drawbacks. For example, blood draws produce accurate results, but they are invasive and time consuming. Pill counters, meanwhile, don't directly measure the intake of the medication. To address these limitations, the team turned to another body fluid.

"Although it may not be visible, the human body constantly produces sweat, often only in very small amounts," says Shuyu Lin, Ph.D., a postgraduate student researcher who is co-presenting the work with graduate student Jialun Zhu at the meeting. "Small molecules derived from medication, including lithium, show up in that sweat. We recognized this as an opportunity to develop a new type of sensor that would detect these molecules."

"Through a single touch, our new device can obtain clinically useful molecular-level information about what is circulating in the body," says Sam Emaminejad, Ph.D., the project's principal investigator, who is at the University of California, Los Angeles (UCLA). "We already interact with a lot of touch-based electronics, such as smart phones and keyboards, so this sensor could integrate seamlessly into daily life."

Devising a sensor to detect lithium presented some technical challenges, however. Sweat is generally only present in minute amounts, but the electrochemical sensing needed to detect charged particles of lithium required an aqueous, or watery, environment. To provide it, the team engineered a water-based gel containing glycerol. This extra ingredient prevented the gel from drying out and created a controlled environment for the electronic portion of the sensor.

To trap the lithium ions after they traversed the gel, the team used an ion-selective electrode. The accumulating ions generate a difference in electrical potential compared with a reference electrode. The researchers used this difference to infer the concentration of lithium present in sweat. Together, these components comprise a tiny, rectangular sensor that is smaller than the head of a thumbtack and can detect lithium in about 30 seconds. The sensor is still in the preliminary testing phase, but ultimately, the researchers envision incorporating it into a larger, yet-to-be designed system that provides visual feedback to the provider or the patient.

After characterizing the sensor using an artificial fingertip, the team recruited real people to test it, including one person on a lithium treatment regimen. The researchers recorded this person's lithium levels before and after taking the medication. They found that these measurements fell close to those derived from saliva, which prior research has shown to accurately measure lithium levels. In the future, the researchers plan to study the effects of lotion and other skin products on the sensor's readings.

This technology also has applications beyond lithium. Emaminejad is developing similar touch-based sensors to monitor alcohol and acetaminophen, a painkiller also known as Tylenol, while also exploring the possibility of detecting other substances. The complete sensing systems could include additional features, such as encryption secured by a fingerprint, or, for substances prone to abuse, a robotic dispensing system that releases medication only if the patient has a low level in their bloodstream.

phys.org

[Frank Sully] Stanford engineers present new chip that ramps up AI computing efficiency Stanf...

Frank Sully — 8/18/2022 6:29:13 PM

Stanford engineers present new chip that ramps up AI computing efficiency

Stanford engineers created a more efficient and flexible AI chip, which could bring the power of AI into tiny edge devices.

AI-powered edge computing is already pervasive in our lives. Devices like drones, smart wearables, and industrial IoT sensors are equipped with AI-enabled chips so that computing can occur at the “edge” of the internet, where the data originates. This allows real-time processing and guarantees data privacy.

The NeuRRAM chip is not only twice as energy efficient as state-of-the-art, it’s also versatile and delivers results that are just as accurate as conventional digital chips. (Image credit: David Baillot/University of California San Diego.)

However, AI functionalities on these tiny edge devices are limited by the energy provided by a battery. Therefore, improving energy efficiency is crucial. In today’s AI chips, data processing and data storage happen at separate places – a compute unit and a memory unit. The frequent data movement between these units consumes most of the energy during AI processing, so reducing the data movement is the key to addressing the energy issue.

Stanford University engineers have come up with a potential solution: a novel resistive random-access memory (RRAM) chip that does the AI processing within the memory itself, thereby eliminating the separation between the compute and memory units. Their “compute-in-memory” (CIM) chip, called NeuRRAM, is about the size of a fingertip and does more work with limited battery power than what current chips can do.

“Having those calculations done on the chip instead of sending information to and from the cloud could enable faster, more secure, cheaper, and more scalable AI going into the future, and give more people access to AI power,” said H.-S Philip Wong, the Willard R. and Inez Kerr Bell Professor in the School of Engineering.

“The data movement issue is similar to spending eight hours in commute for a two-hour workday,” added Weier Wan, a recent graduate at Stanford leading this project. “With our chip, we are showing a technology to tackle this challenge.”

They presented NeuRRAM in a recent article in the journal Nature. While compute-in-memory has been around for decades, this chip is the first to actually demonstrate a broad range of AI applications on hardware, rather than through simulation alone.

Putting computing power on the deviceTo overcome the data movement bottleneck, researchers implemented what is known as compute-in-memory (CIM), a novel chip architecture that performs AI computing directly within memory rather than in separate computing units. The memory technology that NeuRRAM used is resistive random-access memory (RRAM). It is a type of non-volatile memory – memory that retains data even once power is off – that has emerged in commercial products. RRAM can store large AI models in a small area footprint, and consume very little power, making them perfect for small-size and low-power edge devices.

By combining computing and memory in one place, the NeuRRAM chip could enhance the efficiency and applications of a wide variety of AI-enabled devices, such as smart wearables, industrial sensors, and drones.(Image credit: Nicolle Fuller/Sayo Studio)

Even though the concept of CIM chips is well established, and the idea of implementing AI computing in RRAM isn’t new, “this is one of the first instances to integrate a lot of memory right onto the neural network chip and present all benchmark results through hardware measurements,” said Wong, who is a co-senior author of the Nature paper.

The architecture of NeuRRAM allows the chip to perform analog in-memory computation at low power and in a compact-area footprint. It was designed in collaboration with the lab of Gert Cauwenberghs at the University of California, San Diego, who pioneered low-power neuromorphic hardware design. The architecture also enables reconfigurability in dataflow directions, supports various AI workload mapping strategies, and can work with different kinds of AI algorithms – all without sacrificing AI computation accuracy.

To show the accuracy of NeuRRAM’s AI abilities, the team tested how it functioned on different tasks. They found that it’s 99% accurate in letter recognition from the MNIST dataset, 85.7% accurate on image classification from the CIFAR-10 dataset, 84.7% accurate on Google speech command recognition and showed a 70% reduction in image-reconstruction error on a Bayesian image recovery task.

“Efficiency, versatility, and accuracy are all important aspects for broader adoption of the technology,” said Wan. “But to realize them all at once is not simple. Co-optimizing the full stack from hardware to software is the key.”

“Such full-stack co-design is made possible with an international team of researchers with diverse expertise,” added Wong.

Fueling edge computations of the futureRight now, NeuRRAM is a physical proof-of-concept but needs more development before it’s ready to be translated into actual edge devices.

But this combined efficiency, accuracy, and ability to do different tasks showcases the chip’s potential. “Maybe today it is used to do simple AI tasks such as keyword spotting or human detection, but tomorrow it could enable a whole different user experience. Imagine real-time video analytics combined with speech recognition all within a tiny device,” said Wan. “To realize this, we need to continue improving the design and scaling RRAM to more advanced technology nodes.”

“This work opens up several avenues of future research on RRAM device engineering, and programming models and neural network design for compute-in-memory, to make this technology scalable and usable by software developers”, said Priyanka Raina, assistant professor of electrical engineering and a co-author of the paper.

If successful, RRAM compute-in-memory chips like NeuRRAM have almost unlimited potential. They could be embedded in crop fields to do real-time AI calculations for adjusting irrigation systems to current soil conditions. Or they could turn augmented reality glasses from clunky headsets with limited functionality to something more akin to Tony Stark’s viewscreen in the Iron Manand Avengers movies (without intergalactic or multiverse threats – one can hope).

If mass produced, these chips would be cheap enough, adaptable enough, and low power enough that they could be used to advance technologies already improving our lives, said Wong, like in medical devices that allow home health monitoring.

They can be used to solve global societal challenges as well: AI-enabled sensors would play a role in tracking and addressing climate change. “By having these kinds of smart electronics that can be placed almost anywhere, you can monitor the changing world and be part of the solution,” Wong said. “These chips could be used to solve all kinds of problems from climate change to food security.”

Additional co-authors of this work include researchers from University of California San Diego (co-lead), Tsinghua University, University of Notre Dame, and University of Pittsburgh. Former Stanford graduate student Sukru Burc Eryilmaz is also a co-author. Wong is a member of Stanford Bio-X and the Wu Tsai Neurosciences Institute, and an affiliate of the Precourt Institute for Energy. He is also Faculty Director of the Stanford Nanofabrication Facility and the founding faculty co-director of the Stanford SystemX Alliance – an industrial affiliate program at Stanford focused on building systems.

This research was funded by the National Science Foundation Expeditions in Computing, SRC JUMP ASCENT Center, Stanford SystemX Alliance, Stanford NMTRI, Beijing Innovation Center for Future Chips, National Natural Science Foundation of China, and the Office of Naval Research.

news.stanford.edu

[Frank Sully] Nvidia online GTC event will feature 200 sessions on AI, the metaverse, and Omn...

Frank Sully — 8/18/2022 6:12:43 PM

Nvidia online GTC event will feature 200 sessions on AI, the metaverse, and Omniverse

Message 33967366

[Frank Sully] Marco Hutter’s Keynote at the 2022 IEEE International Confetence on Robotics and...

Frank Sully — 8/18/2022 4:23:38 PM

Marco Hutter’s Keynote at the 2022 IEEE International Confetence on Robotics and Automation (ICRA)

PROF. DR. MARCO HUTTER

MEMBER OF THE BOARD of Anybotics

Marco is Associate Professor at ETH Zurich, Branco Weiss Fellow, co-founder and Vice-Chairman of ANYbotics. His research interests are in the development of novel machines and actuation concepts together with the underlying control, planning, and learning algorithms for locomotion and manipulation.

50 minute video presenting the state of the art in autonomous robots.

[Frank Sully] Berkshire Grey Inc $2.87 31.65% +0.69 Today Mr. Market liked the earning rep...

Frank Sully — 8/12/2022 6:30:02 PM

Berkshire Grey Inc

$2.87

31.65%

+0.69 Today

Mr. Market liked the earning report!

[Frank Sully] IKEA’s Chain Building Robot [youtube video]

Frank Sully — 8/12/2022 3:16:29 PM

[Julius Wong] Berkshire Grey GAAP EPS of -$0.12 beats by $0.03, revenue of $23.45M beats by $1...

Julius Wong — 8/12/2022 9:10:14 AM

Berkshire Grey GAAP EPS of -$0.12 beats by $0.03, revenue of $23.45M beats by $14.83M

Aug. 11, 2022 7:05 AM ET Berkshire Grey, Inc. (BGRY)By: Niloofer Shaikh, SA News Editor 2 Comments

Berkshire Grey press release (NASDAQ: BGRY): Q2 GAAP EPS of -$0.12 beats by $0.03.

Revenue of $23.45M (+421.1% Y/Y) beats by $14.83M.

The company expects revenue of approximately $70M-80M for 2022 vs. consensus of $89.63M.

The updated estimate for 2022 revenue reflects the company’s expectation that one of its projects with a large customer will be delayed. Berkshire Grey and this customer are discussing changes in the project schedule and an expanded scope for the project which has the potential to increase Berkshire Grey’s overall opportunity with this customer in 2023 and beyond.

[Julius Wong] This 17-Year-Old Designed a Motor That Could Potentially Transform the Electric ...

Julius Wong — 8/12/2022 7:21:43 AM

This 17-Year-Old Designed a Motor That Could Potentially Transform the Electric Car Industry

Robert Sansone’s research could pave the way for the sustainable manufacturing of electric vehicles that do not require rare-earth magnets

Robert Sansone with his novel synchronous reluctance motor. Society for Science

Robert Sansone is a natural born engineer. From animatronic hands to high-speed running boots and a go-kart that can reach speeds of more than 70 miles per hour, the Fort Pierce, Florida-based inventor estimates he’s completed at least 60 engineering projects in his spare time. And he’s only 17 years old.

A couple years ago, Sansone came across a video about the advantages and disadvantages of electric cars. The video explained that most electric car motors require magnets made from rare-earth elements, which can be costly, both financially and environmentally, to extract. The rare-earth materials needed can cost hundreds of dollars per kilogram. In comparison, copper is worth $7.83 per kilogram.

“I have a natural interest in electric motors,” says Sansone, who had used them in different robotics projects. “With that sustainability issue, I wanted to tackle it, and try and design a different motor.”

The highschooler had heard of a type of electric motor—the synchronous reluctance motor—that doesn’t use these rare-earth materials. This kind of motor is currently used for pumps and fans, but it isn’t powerful enough by itself to be used in an electric vehicle. So, Sansone started brainstorming ways he could improve its performance.

Over the course of a year, Sansone created a prototype of a novel synchronous reluctance motor that had greater rotational force—or torque—and efficiency than existing ones. The prototype was made from 3-D printed plastic, copper wires and a steel rotor and tested using a variety of meters to measure power and a laser tachometer to determine the motor’s rotational speed. His work earned him first prize, and $75,000 in winnings, at this year’s Regeneron International Science and Engineering Fair (ISEF), the largest international high school STEM competition.

The less sustainable permanent magnet motors use materials such as neodymium, samarium and dysprosium, which are in high demand because they’re used in many different products, including headphones and earbuds, explains Heath Hofmann, a professor of electrical and computer engineering at the University of Michigan. Hofmann has worked extensively on electric vehicles, including consulting with Tesla to develop the control algorithms for its propulsion drive.

“The number of applications that use magnets just seems to be getting larger and larger,” he says. “A lot of the materials are mined in China, and so the price can often depend upon our trade status with China.” Hofmann adds that Tesla recently started using permanent magnets in its motors.

Electric motors use rotating electromagnetic fields to spin a rotor. Coils of wire in the stationary outer portion of the motor, called the stator, produce these electromagnetic fields. In permanent magnet motors, magnets attached to the edge of a spinning rotor produce a magnetic field that is attracted to the opposite poles on the spinning field. This attraction spins the rotor.

Synchronous reluctance motors don’t use magnets. Instead, a steel rotor with air gaps cut into it aligns itself with the rotating magnetic field. Reluctance, or the magnetism of a material, is key to this process. As the rotor spins along with the rotating magnetic field, torque is produced. More torque is produced when the saliency ratio, or difference in magnetism between materials (in this case, the steel and the non-magnetic air gaps), is greater.

Instead of using air gaps, Sansone thought he could incorporate another magnetic field into a motor. This would increase this saliency ratio and, in turn, produce more torque. His design has other components, but he can’t disclose any more details because he hopes to patent the technology in the future.

Sansone’s novel motor outperformed a similarly-designed traditional synchronous reluctance motor in tests of torque and efficiency. Robert Sansone

“Once I had this initial idea, then I had to do some prototyping to try and see if that design would actually work,” Sansone says. “I don’t have tons of resources for making very advanced motors, and so I had to make a smaller version—a scale model—using a 3-D printer.”

It took several prototypes before he could test his design.

“I didn't have a mentor to help me, really, so each time a motor failed, I had to do tons of research and try and troubleshoot what went wrong,” he says. “But eventually on the 15th motor, I was able to get a working prototype.”

Sansone tested his motor for torque and efficiency, and then reconfigured it to run as a more traditional synchronous reluctance motor for comparison. He found that his novel design exhibited 39 percent greater torque and 31 percent greater efficiency at 300 revolutions per minute (RPM). At 750 RPM, it performed at 37 percent greater efficiency. He couldn’t test his prototype at higher revolutions per minute because the plastic pieces would overheat—a lesson he learned the hard way when one of the prototypes melted on his desk, he tells Top of the Class, a podcast produced by Crimson Education.

In comparison, Tesla’s Model S motor can reach up to 18,000 RPM, explained the company’s principal motor designer Konstantinos Laskaris in a 2016 interview with Christian Ruoff of the electric vehicles magazine Charged.

Sansone validated his results in a second experiment, in which he “isolated the theoretical principle under which the novel design creates magnetic saliency,” per his project presentation. Essentially, this experiment eliminated all other variables, and confirmed that the improvements in torque and efficiency were correlated with the greater saliency ratio of his design.

“He's definitely looking at things the right way,” Hofmann says of Sansone. “There's the potential that it could be the next big thing.” Though, he adds that many professors work on research their whole lives, and it’s “fairly rare that they end up taking over the world.”

Hofmann says the materials for synchronous reluctance motors are cheap, but the machines are complex and notoriously difficult to manufacture. High manufacturing costs are, therefore, a barrier to their widespread use—and a major limiting factor to Sansone’s invention.

Sansone agrees, but says “with new technologies like additive manufacturing [such as 3-D printing], it would be easier to construct it in the future.”

Sansone is now working on calculations and 3-D modeling for version 16 of his motor, which he plans to build out of sturdier materials so he can test it at higher revolutions per minute. If his motor continues to perform with high speed and efficiency, he says he’ll move forward with the patenting process.

Sansone’s entire experimental setup. Robert Sansone

As a rising senior at Fort Pierce Central High School, Sansone has dreams of attending the Massachusetts Institute of Technology. His winnings from ISEF will go toward college tuition.

Sansone says he hadn’t originally planned to enter into the competition. But when he learned that one of his classes allowed him to complete a year-long research project and paper on a topic of his choice, he decided to take the opportunity to continue working on his motor.

“I was thinking if I'm able to put this much energy into it, I might as well make it a science fair project and compete with it,” he explains. After doing well at the district and state competitions, he advanced to ISEF.

Sansone is waiting until his next phase of testing before he approaches any car companies, but he hopes that one day his motor will be the design of choice for electric vehicles.

“Rare-earth materials in existing electric motors are a major factor undermining the sustainability of electric vehicles,” he says. “Seeing the day when EVs are fully sustainable due to the help of my novel motor design would be a dream come true.”

smithsonianmag.com

[Julius Wong] Scientists Create a More Sustainable LED From Fish Scales Researchers microwa...

Julius Wong — 8/9/2022 7:43:30 PM

Scientists Create a More Sustainable LED From Fish Scales

Researchers microwaved fish waste to produce a unique nanoform of carbon that could be used for LED devices in the future

A procedure developed by scientists in Japan can convert fish scales into a carbon-based nanomaterial. Takashi Shirai from NITech, Japan

Scientists have discovered that by microwaving fish waste, they can quickly and efficiently create carbon nano-onions (CNOs)—a unique nanoform of carbon that has applications in energy storage and medicine. This method could be used to make cheaper and more sustainable LEDs in the future. The researchers from Nagoya Institute of Technology in Japan published their findings in Green Chemistry.

CNOs are nanostructures with spherical carbon shells in a concentric layered structure similar to an onion. They have “drawn extensive attention worldwide in terms of energy storage and conversion” because of their “exceptionally high electrical and thermal conductivity, as well as large external surface area,” per the paper. They’ve been used in electronics and for biomedical applications, such as bio-imaging and sensing and drug delivery, write the authors in the study.

Though CNOs were first reported in the 1980s, conventional methods of manufacturing them have required high temperatures, a vacuum and a lot of time and energy. Other techniques are expensive and call for complex catalysts or dangerous acidic or basic conditions. This “greatly limits the potential of CNOs,” per a statement from Nagoya Institute of Technology.

The newly discovered method requires only one step—microwave pyrolysis of fish scales extracted from fish waste—and can be done within ten seconds, per the authors.

How exactly the fish scales are converted into CNOs is unclear, though the team thinks it has to do with how collagen in the fish scales can absorb enough microwave radiation to quickly increase in temperature. This leads to pyrolysis, or thermal decomposition, which causes the collagen to break down into gasses. These gasses then support the creation of CNOs.

This method is a “straightforward way to convert fish waste into infinitely more useful materials,” and the resulting CNOs have a high crystallinity, which gives them “exceptional optical properties,” per the statement. They also have high functionalisation, which means they're "bonded to other small molecules on their surface," writes Ellen Phiddian for Cosmos. This combination of attributes means the CNOs can glow bright blue, per Cosmos.

“The CNOs exhibit ultra-bright visible-light emission with an efficiency (or quantum yield) of 40 percent,” says Takashi Shirai, a coauthor and professor in the Nagoya Institute of Technology’s Department of Life Science and Applied Chemistry, in a statement. “This value, which has never been achieved before, is about 10 times higher than that of previously reported CNOs synthesized via conventional methods.”

Because of these excellent optical properties, the CNOs could be used to create “large-area emissive flexible films and LED devices,” Shirai says in the statement. “These findings will open up new avenues for the development of next-generation displays and solid-state lighting.”

See missing graphics at
smithsonianmag.com

[Frank Sully] You’re correct Julius. Thanks for catching the slip up in the article!

Frank Sully — 8/7/2022 11:07:06 AM

[Julius Wong] Berkshire Grey, Inc. (BGRY), not BGY (BlackRock Enhanced International Dividend ...

Julius Wong — 8/7/2022 7:57:06 AM

Berkshire Grey, Inc. (BGRY), not BGY (BlackRock Enhanced International Dividend Trust)