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Strictly speaking, the three researchers – Sergey Bravyi, David Gosset, and Robert König – have shown that
parallel quantum algorithms running in a constant time period are strictly more powerful than their classical counterparts; they are provably better at solving certain linear algebra problems associated with binary quadratic forms.
The proof they provided is based on an algorithm to solve a quadratic “hidden linear function” problem that can be implemented in quantum constant-depth. A hidden linear function is a linear function that is not entirely known but is “hidden” inside of another function you can calculate. For example, a linear function could be hidden inside of an oracle that can be queried. The challenge is to fully characterize the hidden linear function based on the results of applying the known function. If this sounds somewhat similar to the problem of inverting a public key to find its private counterpart, it is no surprise, since this is exactly what it is about. In the case of an oracle, the problem is solved by the classical Bernstein-Vazirani algorithm, which minimizes the number of queries to the oracle. Now, according to the three researchers, the fact that the Bernstein-Vazirani algorithm is applied to an oracle limits its practical applicability, so they suggest “hiding” a linear function inside a bidimensional grid graph. After proving that this is indeed possible, they built a quantum constant-depth algorithm to find the hidden function out.
The other half of the proof provided by the researchers is showing that, contrary to a quantum circuit, any classical circuit needs to increase its depth as the number of inputs grows. For example, while the quantum algorithm can solve that problem using at most a quantum circuit of depth 10 no matter how many inputs you have, you need, say, a classical circuit of depth 10 for a 16 inputs problem; a circuit of depth 14 for a 32 inputs problem; a circuit of depth 20 for a 64 inputs problem, and so on. This second part of the proof is philosophically deeply interesting, since it dwells on the idea of quantum nonlocality, which in turn is related to quantum entanglement, one of the most peculiar properties of quantum processors along with superposition. So, quantum advantage would seem to derive from the most intrinsic properties of quantum physics.
At the theortical level, the value of this achievement is not to be underestimated either. As IBM IBM Q Vicepresident Bob Sutor wrote:
The proof is the first demonstration of unconditional separation between quantum and classical algorithms, albeit in the special case of constant-depth computations.
Previously, the idea that quantum computer were more powerful than classical ones was based on factorization problems. Shor showed quantum computers can factor an integer in polynomial time, i.e. more efficiently than any know classical computer algorithms. Albeit an interesting result, this did not rule out the possibility that a more efficient classical factorization algorithm could indeed be found. So unless one conjectured that no efficient solution to the factorization problem could exist, which is equivalent to demonstrate that “ P ? NP”, one could not really say that quantum advantage was proved.
As mentioned, Bravyi, Gosset, and König’s algorithm, relying on a constant number of operations (the depth of a quantum circuit) seems to fit just right with the limitation of current quantum computer processors. Those are basically related to qubits’ error rate and coherence time, which limit the maximal duration of a sequence of operations and their overall number. Therefore, using short-depth circuits is key for any feasible application of current quantum circuits. Thanks to this property of the proposed algorithm, IBM researchers are already at work ot demonstrate quantum advantage using IBM quantum computer, Sutor remarks.
The kilogram is one of the most important and widely used units of measure in the world — unless you live in the US. For everyone else, having an accurate reading on what a kilogram is can be vitally important in fields like manufacturing, engineering, and transportation. Of course, a kilogram is 1,000 grams or 2.2 pounds if you want to get imperial. That doesn’t help you define a kilogram, though. The kilogram is currently controlled by a metal slug in a French vault, but its days of importance are numbered. Scientists are preparing to redefine the kilogram using science.
It’s actually harder than you’d expect to know when a measurement matches the intended standard, even when it’s one of the well-defined Systéme International (SI) units. For example, the meter was originally defined in 1793 as one ten-millionth the distance from the equator to the north pole. That value was wrong, but the meter has since been redefined in more exact terms like krypton-86 wavelength emissions and most recently the speed of light in a vacuum. The second was previously defined as a tiny fraction of how long it takes the Earth to orbit the sun. Now, it’s pegged to the amount of time it takes a cesium-133 atom to oscillate 9,192,631,770 times. Again, this is immutable and extremely precise.
That brings us to the kilogram, which is a measurement of mass. Weight is different and changes based on gravity, but a kilogram is always a kilogram because it comes from measurements of density and volume. The definition of the kilogram is tied to the International Prototype of the Kilogram (IPK, see above), a small cylinder of platinum and iridium kept at the International Bureau of Weights and Measures in France. Scientists have created dozens of copies of the IPK so individual nations can standardize their measurements, but that’s a dangerous way to go about it. If anything happened to the IPK, we wouldn’t have a standard kilogram anymore.
Later this month, scientists at the international General Conference on Weights and Measures are expected to vote on a new definition for the kilogram, one that leaves the IPK behind and ties the measurement to the unchanging laws of the universe. Researchers from the National Institute of Standards and Technology in the US and the National Physical Laboratory in England are working on the problem of connecting mass with electromagnetic forces.
The Kibble Balance at the UK’s National Physical Laboratory.
The heart of this effort is the Kibble Balance, a stupendously complex device that quantifies the electric current needed to match the electromagnetic force equal to the gravitational force acting on a mass. So, it does not measure mass directly but instead measures the electromagnetic force between two plates. This allows scientists to connect the mass of a kilogram to the Planck constant, which is much less likely to change than a metal slug in a French vault.
So, the kilogram isn’t changing in any way that matters in your daily life, but that’s kind of the point. The kilogram is important, so it can’t change. Redefining the kilogram to get away from the IPK ensures it remains the same forever.
High-tech farmers are using LED lights in ways that seem to border on science fiction
By Adrian Higgins in Cincinnati Nov. 6, 2018
ike Zelkind stands at one end of what was once a shipping container and opens the door to the future.
Thousands of young collard greens are growing vigorously under a glow of pink-purple lamps in a scene that seems to have come from a sci-fi movie, or at least a NASA experiment. But Zelkind is at the helm of an earthbound enterprise. He is chief executive of 80 Acres Farms, with a plant factory in an uptown Cincinnati neighborhood where warehouses sit cheek by jowl with detached houses.
Since plants emerged on Earth, they have relied on the light of the sun to feed and grow through the process of photosynthesis.
But Zelkind is part of a radical shift in agriculture — decades in the making — in which plants can be grown commercially without a single sunbeam. A number of technological advances have made this possible, but none more so than innovations in LED lighting.
“What is sunlight from a plant’s perspective?” Zelkind asks. “It’s a bunch of photons.”
Diode lights, which work by passing a current between semiconductors, have come a long way since they showed up in calculator displays in the 1970s. Compared with other forms of electrical illumination, light-emitting diodes use less energy, give off little heat and can be manipulated to optimize plant growth.
Startup Offers To Sequence Your Genome Free Of Charge, Then Let You Profit From It
npr.org"Everything is private information, stored on your computer or a computer you designate," says George Church, genetics professor at Harvard Medical School, about the approach of Nebula Genomics.
Craig Barritt/Getty Images for The New Yorker A startup genetics company says it's now offering to sequence your entire genome at no cost to you. In fact, you would own the data and may even be able to make money off it.
Nebula Genomics, created by the prominent Harvard geneticist George Church and his lab colleagues, seeks to upend the usual way genomic information is owned.
Today, companies like 23andMe make some of their money by scanning your genetic patterns and then selling that information to drug companies for use in research. (You choose whether to opt in.)
Church says his new enterprise leaves ownership and control of the data in an individual's hands. And the genomic analysis Nebula will perform is much more detailed than what 23andMe and similar companies offer.
Nebula will do a full genome sequence, rather than a snapshot of key gene variants. That wider range of genetic information would makes the data more appealing to biologists and biotech and pharmaceutical companies.
Generating a full sequence costs about $1,000, but the price continues to tumble, Church says. Nebula's business model anticipates that companies and research organizations would be willing to pay for the cost of sequencing, if in exchange they also get some key medical information about the person involved. If that proves to be the case, people would get their genetic information at no cost.
Article continues after this message from our sponsor The company hopes most people will pony up $99 to get the process going. "Ninety-nine bucks will get you a little bit of genetic information, but to get the full thing, [companies or researchers] will have to be interested in either your traits or your genome or both," Church says.
My Grandmother Was Italian. Why Aren't My Genes Italian?In fact, people might even make money on the deal, especially if they have an unusual trait that a company wants to study. Those payments could be "probably anywhere from $10 to $10,000, if you're some exceptional research resource," Church says.
And it's not just people with diseases who could be of value to pharmaceutical companies. "Even people who seem to be healthy, they might be super healthy and not even know it," he says.
Church's approach is part of a trend that's pushing back against the multibillion-dollar industry to buy and sell medical information. Right now, companies reap those profits and control the data.
"Patients should have the right to decide for themselves whether they want to share their medical data, and, if so, with whom," Adam Tanner, at Harvard's Institute for Quantitative Social Science, says in an email. "Efforts to empower people to fine-tune the fate of their medical information are a step in the right direction." Tanner, author of a book on the subject of the trade in medical data, isn't involved in Nebula.
The current system is "very paternalistic," Church says. He aims to give people complete control over who gets access to their data, and let individuals decide whether or not to sell the information, and to whom.
"In this case, everything is private information, stored on your computer or a computer you designate," Church says. It can be encrypted so nobody can read it, even you, if that's what you want.
Drug companies interested in studying, say, diabetes patients would ask Nebula to identify people in their system who have the disease. Nebula would then identify those individuals by launching an encrypted search of participants.
People who have indicated they're interested in selling their genetic data to a company would then be given the option of granting access to the information, along with medical data that person has designated.
Other companies are also springing up to help people control — and potentially profit from — their medical data. EncrypGen lets people offer up their genetic data, though customers have to provide their own DNA sequence. Hu-manity.co is also trying to establish a system in which people can sell their medical data to pharmaceutical companies.
Church, a genetics pioneer, has also developed other business models before. The Personal Genome Project allows people to donate their genome and health data to help speed medical research. Veritas Geneticscharges $1,000 to produce a complete genome, and provides the resulting medical information to people along with genetic counseling.
Church has been trying to accelerate research into health and disease through these efforts. Jason Bobe, a geneticist at the Icahn School of Medicine at Mount Sinai, says one bottleneck has been getting people to participate in research. (Bobe has collaborated with Church but isn't involved in Nebula Genomics.)
With more control over personal data, and the possibility of a personal financial return, "I'm hopeful that this model will actually attract people, where historically people have been very disinterested in participation in research."
The greatest hardware hacks of all time were simply the result of finding software keys in memory. The AACS encryption debacle — the 09 F9 key that allowed us to decrypt HD DVDs — was the result of encryption keys just sitting in main memory, where it could be read by any other program. DeCSS, the hack that gave us all access to DVDs was again the result of encryption keys sitting out in the open.
Because encryption doesn’t work if your keys are just sitting out in the open, system designers have come up with ingenious solutions to prevent evil hackers form accessing these keys. One of the best solutions is the hardware enclave, a tiny bit of silicon that protects keys and other bits of information. Apple has an entire line of chips, Intel has hardware extensions, and all of these are black box solutions. They do work, but we have no idea if there are any vulnerabilities. If you can’t study it, it’s just an article of faith that these hardware enclaves will keep working.
Now, there might be another option. RISC-V researchers are busy creating an Open Source hardware enclave. This is an Open Source project to build secure hardware enclaves to store cryptographic keys and other secret information, and they’re doing it in a way that can be accessed and studied. Trust but verify, yes, and that’s why this is the most innovative hardware development in the last decade.
What is an enclave?Although as a somewhat new technology, processor enclaves have been around for ages. The first one to reach the public consciousness would be the Secure Enclave Processor (SEP) found in the iPhone 5S. This generation of iPhone introduced several important technological advancements, including Touch ID, the innovative and revolutionary M7 motion coprocessor, and the SEP security coprocessor itself. The iPhone 5S was a technological milestone, and the new at the time SEP stored fingerprint data and cryptographic keys beyond the reach of the actual SOC found in the iPhone.
The iPhone 5S SEP was designed to perform secure services for the rest of the SOC, primarily relating to the Touch ID functionality. Apple’s revolutionary use of a secure enclave processor was extended with the 2016 release of the Touch Bar MacBook Pro and the use of the Apple T1 chip. The T1 chip was again used for TouchID functionality, and demonstrates that Apple is the king of vertical integration.
But Apple isn’t the only company working on secure enclaves for their computing products. Intel has developed the SGX extension which allows for hardware-assisted security enclaves. These enclaves give developers the ability to hide cryptographic keys and the components for digital rights management inside a hardware-protected bit of silicon. AMD, too, has hardware enclaves with the Secure Encrypted Virtualization (SEV). ARM has Trusted Execution environments. While the Intel, AMD, and ARM enclaves are bits of silicon on other bits of silicon — distinct from Apple’s approach of putting a hardware enclave on an entirely new chip — the idea remains the same. You want to put secure stuff in secure environments, and enclaves allow you to do that.
Unfortunately, these hardware enclaves are black boxes, and while they do provide a small attack surface, there are problems. AMD’s SEV is already known to have serious security weaknesses, and it is believed SEV does not offer protection from malicious hypervisors, only from accidental hypervisor vulnerabilities. Intel’s Management engine, while not explicitly a hardware enclave, has been shown to be vulnerable to attack. The problem is that these hardware enclaves are black boxes, and security through obscurity does not work at all.
The Open Source SolutionAt last week’s RISC-V Summit, researchers at UC Berkeley released their plans for the Keystone Enclave, an Open Source secure enclave based on the RISC-V (PDF). Keystone is a project to build a Trusted Execution Environment (TEE) with secure hardware enclaves based on the RISC-V architecture, the same architecture that’s going into completely Open Source microcontrollers and (soon) Systems on a Chip.
The goals of the Keystone project are to build a chain of trust, starting from a silicon Root of Trust stored in tamper-proof hardware. this leads to a Zeroth-stage bootloader and a tamper-proof platform key store. Defining a hardware Root of Trust (RoT) is exceptionally difficult; you can always decapsulate silicon, you can always perform some sort of analysis on a chip to extract keys, and if your supply chain isn’t managed well, you have no idea if the chip you’re basing your RoT on is actually the chip in your computer. However, by using RISC-V and its Open Source HDL, this RoT can at least be studied, unlike the black box solutions from Intel, AMD, and ARM vendors.
The current plans for Keystone include memory isolation, an open framework for building on top of this security enclave, and a minimal but Open Source solution for a security enclave.
Right now, the Keystone Enclave is testable on various platforms, including QEMU, FireSim, and on real hardware with the SiFive Unleashed. There’s still much work to do, from formal verification to building out the software stack, libraries, and adding hardware extensions.
This is a game changer for security. Silicon vendors and designers have been shoehorning in hardware enclaves into processors for nearly a decade now, and Apple has gone so far as to create their own enclave chips. All of these solutions are black boxes, and there is no third-party verification that these designs are inherently correct. The RISC-V project is different, and the Keystone Enclave is the best chance we have for creating a truly Open hardware enclave that can be studied and verified independently.
Serverless Computing: One Step Forward, Two Steps Back
Joseph M. Hellerstein, Jose Faleiro, Joseph E. Gonzalez, Johann Schleier-Smith, Vikram Sreekanti, Alexey Tumanov and Chenggang Wu UC Berkeley {hellerstein,jmfaleiro,jegonzal,jssmith,vikrams,atumanov,cgwu}@berkeley.edu
ABSTRACT Serverless computing offers the potential to program the cloud in an autoscaling, pay-as-you go manner. In this paper we address critical gaps in first-generation serverless computing, which place its autoscaling potential at odds with dominant trends in modern computing: notably data-centric and distributed computing, but also open source and custom hardware. Put together, these gaps make current serverless offerings a bad fit for cloud innovation and particularly bad for data systems innovation. In addition to pinpointing some of the main shortfalls of current serverless architectures, we raise a set of challenges we believe must be met to unlock the radical potential that the cloud—with its exabytes of storage and millions of cores—should offer to innovative developers.
·1; Rotary-Turbo-InFlow Tech / - GEARTURBINE PROJECT Have the similar basic system of the Aeolipilie Heron Steam Turbine device from Alexandria 10-70 AD * With Retrodynamic = DextroRPM VS LevoInFlow + Ying Yang Way Power Type - Non Waste Looses *8X/Y Thermodynamic CYCLE Way Steps. 4 Turbos, Higher efficient percent. No blade erosion by sand & very low heat target signature Pat:197187IMPI MX Dic1991 Atypical Motor Engine Type.
Taiwan Semiconductor Manufacturing Company (TSMC) is expected to kick off volume production of chips built using an enhanced 7nm with EUV node at the end of March, according to industry sources.
ASML, which provides extreme ultraviolet (EUV) litho equipment, is looking to ship a total of 30 EUV systems in 2019. Of the units to be shipped, 18 have already been reserved by TSMC, the sources indicated.
TSMC is also on track to move a newer 5nm node to risk production in the second quarter of 2019, the sources noted. The foundry will fully incorporate EUV in the 5nm node.
TSMC CEO CC Wei disclosed previously the foundry expects to start taping out 5nm chip designs later in the first half of 2019 and move the node to volume production in the first half of 2020.
Meanwhile, TSMC continues to expand its 7nm chip client portfolio. Wei noted that the foundry's 7nm chip client portfolio is "growing stronger" as more chip designs for applications such as HPC and automotive demand the process.
TSMC started volume producing 7nm chips in April 2018, with AMD, Apple, HiSilicon and Xilinx reportedly being among its major 7nm chip customers. The foundry will soon roll out its EUV-based 7nm process, which will boost its total 7nm chip sales to account for 25% of total wafer sales this year compared with 9% in 2018.
Climate change is inevitable. We can see it every day all over the world. I write more detailed about this topic in my prime essay writing. It was difficult to describe but I did it.
Climate change has been going on for 4 BILLION YEARS, modern humans have only existed for about 100k years. The industrial revolution is about 100 years old.
Open a book, or wikipedia, and never post here again. Your ignorance makes me sick.
"Everything is private information, stored on your computer or a computer you designate," says George Church, genetics professor at Harvard Medical School, about the approach of Nebula Genomics.
The greatest hardware hacks of all time were simply the result of finding software keys in memory. The AACS encryption debacle — the 09 F9 key that allowed us to decrypt HD DVDs — was the result of encryption keys just sitting in main memory, where it could be read by any other program. DeCSS, the hack that gave us all access to DVDs was again the result of encryption keys sitting out in the open.
The goals of the Keystone project are to build a chain of trust, starting from a silicon Root of Trust stored in tamper-proof hardware. this leads to a Zeroth-stage bootloader and a tamper-proof platform key store. Defining a hardware Root of Trust (RoT) is exceptionally difficult; you can always decapsulate silicon, you can always perform some sort of analysis on a chip to extract keys, and if your supply chain isn’t managed well, you have no idea if the chip you’re basing your RoT on is actually the chip in your computer. However, by using RISC-V and its Open Source HDL, this RoT can at least be studied, unlike the black box solutions from Intel, AMD, and ARM vendors.
Right now, the Keystone Enclave is testable on various platforms, including QEMU, FireSim, and on real hardware with the SiFive Unleashed. There’s still much work to do, from formal verification to building out the software stack, libraries, and adding hardware extensions.
