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From: Paul H. Christiansen11/14/2023 12:32:45 PM
   of 1057
 
Bloom Energy (BE - $12.23) – Contributing to the world’s need for decarbonization and the growing data center needs for electricity.

($) Bloom Energy Can Finally Live Up to Clean-Power Buzz – The Wall Street Journal

“Data centers can’t get enough power from the main grid… It’s good news for one California clean-energy stock.”

“These “micro grids” could solve a major problem for power-sucking data centers.”

Select HERE for a copy of Bloom Energy updated Quarterly Revenue chart.


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From: Paul H. Christiansen11/17/2023 9:59:54 AM
   of 1057
 
2023-11-16 – Nvidia - Oppenheimer analyst Rick Schafer reiterates Outperform with $650 target. ($) Briefing.com

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From: Paul H. Christiansen11/17/2023 10:44:46 AM
   of 1057
 
Confluent (CFLT) was recently ($20.17) added to the Model Portfolio

Select HERE for a up-to-date copy of CFLT's Revenue Chart

2023-11-01 – CFLT CEO’s Comments – 2023Q3 Earnings Call Transcript

I want to spend some time now focusing on a critical change we're making to drive growth. Beyond just the friction in the current market environment, the critical project for Confluent is to capture the massive market opportunity in streaming. This is a $60 billion market where we are still just scratching the surface of even the existing open source Kafka usage. And we have additional expansion opportunities from Flink, our connectors and data governance, as I outlined in the earnings call last time.

Critical to our execution against this opportunity is leveraging our go-to-market engine to rapidly land new customers, expand new workloads and ensure the adoption of our full set of product capabilities. To this end, we'll be completing the transition to orient our cloud business around consumption. This will make cloud revenue rather than bookings or committed spend the primary goal of the go-to-market organization for Confluent Cloud. This was a planned transition. Indeed, we began changes in this direction this year, but it’s a transition we’ll be significantly accelerating heading into 2024.

To explain what this means, let me start with a little background. In the traditional world of on-premise software, customers would make big upfront commitments. Salespeople worked with the customer to scope these commitments and were paid as a percentage of the resulting bookings. The marketing organization measured pipeline based on these commitments, and every internal system and process was oriented around measuring and managing the bookings that resulted. There was some misalignment between customer and vendor because customer might end up over purchasing, but this was masked by the fact that the rest of the stack, such as servers that ran the software, were also fundamentally upfront in inelastic purchases.

With the advent of the cloud and the elasticity and flexibility it offered to customers, this model had to evolve. Cloud has a utility-like model where services are metered as they are used. However, in the early days, the go-to-market engine for cloud infrastructure software largely remained as it was previously, selling customer commitments or credits that overlaid this dynamic usage. Alignment between customer and vendor improved somewhat, but the vendor still had an incentive to maximally scope customer commitments. Over the last couple of years, businesses like MongoDB, Snowflake, Datadog and hyperscalers have all transitioned their go-to-market to a fully consumption-based model. In this model, the customer and the go-to-market organization are both oriented around the actual service usage, not the upfront commitment. This fully aligns the customer value realization with the vendor's revenue. Less obvious from the outside is how this completely upends the sales and marketing model.

Pipeline is no longer oriented around maximum customer commitment, but rather new logos and new workloads. Salespeople aren't compensated for getting an upfront booking, but rather for what a customer actually uses, finding new workloads and driving new product adoption. This is an absolute win for customers and also a huge win for vendors, who are actually able to grow faster by removing much of the uncertainty and risk from customer purchasing.

With Confluent Cloud now at nearly 50% of our revenue, having NRR over 140% and continuing rapid growth, it's time for Confluent to complete our transition to this fully consumption-based model. We've already made the transition to usage-based pricing that bills for what is used. But today, our go-to-market is still primarily oriented around booking customer commitments.


2023-11-15 – Confluent (CFLT) - Collected Snippets from Briefing.com

Data Streaming Is Central to the Modern Data Stack

Data streaming enables businesses to continuously process their data in real time for improved workflows, more automation, and superior, digital customer experiences. Confluent helps you operationalize and scale all your data streaming projects so you never lose focus on your core business.

2023-09-01 - Canaccord Genuity began coverage on Confluent (CFLT) at Buy, $40 tgt; CG thinks investors should consider three key elements in the CFLT story: Confluent stands out in a rapidly growing, highly fragmented data streaming landscape. Opportunity in stream processing (Flink) could be as large as core market. Confluent Cloud's differentiated value proposition extends far beyond hosting.

2023-05-30 - Confluent: Data Streaming Hits the Mainstream; Category Leader Positioned to Execute - Needham; tgt $35 (28.71)

Needham's Mike Cikos notes, "Confluent Cloud has been constructed from the ground up to deliver a Cloud-Native SaaS offering that differs from hyperscalers' Cloud-Hosted solutions and provides cross-cloud flexibility. We also see Confluent's development of a fully-managed Flink offering as potentially mirroring Kafka adoption while deepening and broadening the platform. We initiate coverage of Confluent with a Buy rating and a $35 Price Target."

2023-05-16 - Confluent (CFLT) announced new Confluent Cloud capabilities that give customers confidence that their data is trustworthy and can be easily processed and securely shared. With Data Quality Rules, an expansion of the Stream Governance suite, organizations can easily resolve data quality issues so data can be relied on for making business-critical decisions. In addition, Confluent's new Custom Connectors, Stream Sharing, the Kora Engine, and early access program for managed Apache Flink make it easier for companies to gain insights from their data on one platform, reducing operational burdens and ensuring industry-leading performance. Briefing.com

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From: Paul H. Christiansen11/17/2023 10:55:32 AM
   of 1057
 
2023-11-17 – Confluent has been added ($20.17) to our Model Portfolio

Select HERE for an updated copy of CFLT’s Revenue Chart

2023-11-01 – CFLT CEO’s Comments – 2023Q3 Earnings Call Transcript

"I want to spend some time now focusing on a critical change we're making to drive growth. Beyond just the friction in the current market environment, the critical project for Confluent is to capture the massive market opportunity in streaming. This is a $60 billion market where we are still just scratching the surface of even the existing open source Kafka usage. And we have additional expansion opportunities from Flink, our connectors and data governance, as I outlined in the earnings call last time.

Critical to our execution against this opportunity is leveraging our go-to-market engine to rapidly land new customers, expand new workloads and ensure the adoption of our full set of product capabilities. To this end, we'll be completing the transition to orient our cloud business around consumption. This will make cloud revenue rather than bookings or committed spend the primary goal of the go-to-market organization for Confluent Cloud. This was a planned transition. Indeed, we began changes in this direction this year, but it’s a transition we’ll be significantly accelerating heading into 2024.

To explain what this means, let me start with a little background. In the traditional world of on-premise software, customers would make big upfront commitments. Salespeople worked with the customer to scope these commitments and were paid as a percentage of the resulting bookings. The marketing organization measured pipeline based on these commitments, and every internal system and process was oriented around measuring and managing the bookings that resulted. There was some misalignment between customer and vendor because customer might end up over purchasing, but this was masked by the fact that the rest of the stack, such as servers that ran the software, were also fundamentally upfront in inelastic purchases.

With the advent of the cloud and the elasticity and flexibility it offered to customers, this model had to evolve. Cloud has a utility-like model where services are metered as they are used. However, in the early days, the go-to-market engine for cloud infrastructure software largely remained as it was previously, selling customer commitments or credits that overlaid this dynamic usage. Alignment between customer and vendor improved somewhat, but the vendor still had an incentive to maximally scope customer commitments. Over the last couple of years, businesses like MongoDB, Snowflake, Datadog and hyperscalers have all transitioned their go-to-market to a fully consumption-based model. In this model, the customer and the go-to-market organization are both oriented around the actual service usage, not the upfront commitment. This fully aligns the customer value realization with the vendor's revenue. Less obvious from the outside is how this completely upends the sales and marketing model.

Pipeline is no longer oriented around maximum customer commitment, but rather new logos and new workloads. Salespeople aren't compensated for getting an upfront booking, but rather for what a customer actually uses, finding new workloads and driving new product adoption. This is an absolute win for customers and also a huge win for vendors, who are actually able to grow faster by removing much of the uncertainty and risk from customer purchasing.

With Confluent Cloud now at nearly 50% of our revenue, having NRR over 140% and continuing rapid growth, it's time for Confluent to complete our transition to this fully consumption-based model. We've already made the transition to usage-based pricing that bills for what is used. But today, our go-to-market is still primarily oriented around booking customer commitments."



2023-11-15 – Confluent (CFLT) - Collected Snippets from Briefing.com

Data Streaming Is Central to the Modern Data Stack

Data streaming enables businesses to continuously process their data in real time for improved workflows, more automation, and superior, digital customer experiences. Confluent helps you operationalize and scale all your data streaming projects so you never lose focus on your core business.

2023-09-01 - Canaccord Genuity began coverage on Confluent (CFLT) at Buy, $40 tgt; CG thinks investors should consider three key elements in the CFLT story: Confluent stands out in a rapidly growing, highly fragmented data streaming landscape. Opportunity in stream processing (Flink) could be as large as core market. Confluent Cloud's differentiated value proposition extends far beyond hosting.

2023-05-30 - Confluent: Data Streaming Hits the Mainstream; Category Leader Positioned to Execute - Needham; tgt $35 (28.71)

Needham's Mike Cikos notes, "Confluent Cloud has been constructed from the ground up to deliver a Cloud-Native SaaS offering that differs from hyperscalers' Cloud-Hosted solutions and provides cross-cloud flexibility. We also see Confluent's development of a fully-managed Flink offering as potentially mirroring Kafka adoption while deepening and broadening the platform. We initiate coverage of Confluent with a Buy rating and a $35 Price Target."

2023-05-16 - Confluent (CFLT) announced new Confluent Cloud capabilities that give customers confidence that their data is trustworthy and can be easily processed and securely shared. With Data Quality Rules, an expansion of the Stream Governance suite, organizations can easily resolve data quality issues so data can be relied on for making business-critical decisions. In addition, Confluent's new Custom Connectors, Stream Sharing, the Kora Engine, and early access program for managed Apache Flink make it easier for companies to gain insights from their data on one platform, reducing operational burdens and ensuring industry-leading performance. Briefing.com


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From: Paul H. Christiansen11/22/2023 3:07:42 PM
   of 1057
 
Nvidia Revenue Chart – Updated to include 2023Q3.



WOW!

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From: Paul H. Christiansen11/29/2023 12:55:38 PM
   of 1057
 
Nvidia (NVDA). Given the recent extraordinary Y-O-Y Quarterly Revenue gains achieved by NVDA, the obvious question is whether or not those gains are sustainable. The following interview offers a glimpse into the depth and prescience of NVDA's research, and why they continue to be a clear leader in AI and other advanced computer technologies.

cnbc.com

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From: Paul H. Christiansen11/30/2023 9:46:34 AM
1 Recommendation   of 1057
 
Rule, Britannia? – Nay! – Rule Nvidia!!

2023-11-29 - Nvidia's Game to Lose – Barron’s

Every major technology company is chasing Nvidia.

Last week, the semiconductor company posted stellar financial results. Revenue in its latest quarter nearly tripled, with the company citing surging demand for its chips that enable artificial intelligence applications.

This year, developers have been clamoring for the company’s GPUs, or graphics processing units. They're well suited for the parallel computations needed for AI projects, including large language model training and inference, the process of generating answers from those AI models.

Rivals are racing to compete against Nvidia. Earlier this month, Microsoft unveiled its in-house designed Azure Maia AI Accelerator chip, which is scheduled to be rolled out early next year. On Tuesday, Amazon announced the next version of its Trainium AI chip. Advanced Micro Devices, Intel, and Google are actively working on improved products.

It's going to be an uphill battle for them all. Jefferies analyst Mark Lipacis analyzed the September AI workloads from the six top cloud computing companies and found that Nvidia had an 86% share -- a figure that hasn’t changed much over the past year.

He tracked Alibaba Aliyun, Amazon Web Services, Microsoft Azure, Google Cloud Platform, Oracle Cloud, and Tencent Cloud.

There are several reasons why customers don’t want alternatives to Nvidia’s chips, even when they face a long wait to receive their orders.

First, Nvidia has the most mature technology offering for AI. The company has spent over a decade fixing software and driver issues for its software programming ecosystem, CUDA. It means the company has already fixed technical issues that other less experienced vendors may still need to iron out.

Second, Nvidia is cloud-agnostic. Customers have the flexibility to take their Nvidia-powered workloads from one cloud to another. Rival AI chip offerings from Amazon or Google, on the other hand, lock users into their cloud platforms. That reduces flexibility to switch to another provider offering a cheaper service or better technology.

Third, developers stick with Nvidia because of its decades of platform stability, large market share, access to industry specific tools, and its reputation for backward compatibility.

“All the invention of technologies that you build on top of Nvidia accrue,” Jensen Huang, the CEO of Nvidia, said last week.

Then there’s performance. Nvidia still offers the best overall capability when customers assess the company's combination of software, systems hardware, and networking hardware.

Ultimately, developers want the technology that empowers them to build the best AI applications as fast as possible with the fewest technical risks.

It's Nvidia's game to lose.

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From: Paul H. Christiansen11/30/2023 10:20:29 AM
   of 1057
 
Select HERE for a chart of SNOW's quarterly revenues, including 2023Q3.

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From: Paul H. Christiansen11/30/2023 11:28:45 AM
   of 1057
 
Select HERE for Salesforce (CRM) current Revenue Chart, including 2023Q3,

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From: Paul H. Christiansen12/2/2023 11:32:49 AM
   of 1057
 
Select HERE to view Year-to-Date Performance Chart for November 2023.

Select HERE to view Launch-to-Date Performance Chart for November 2023.

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