Mark Heynen’s Post

Amazon Bedrock introduces Prompt Management and Prompt Flows in public preview to accelerate development, testing, and deployment of generative AI applications. The new features enable developers and business users to create more efficient, effective, and easier to maintain AI solutions. #aws #awscloud #cloud #amazonbedrock #announcements #artificialintelligence #generativeai

How Microsoft's AI Investment is Stabilizing Its Cloud Business: ZDNet reports an interesting static from Microsoft's CEO Satya Nadella. "We have over 1 million paid Copilot users in more than 37,000 organizations that subscribe to Copilot for business, with significant traction outside the United States." And Microsoft's quarterly results also "showed early signs that the company's investments in generative AI were beginning to bolster sales, most notably reversing what had been slowing growth of the company's important cloud computing product," reports the New York Times. (Alternate URL here.) The company had $56.5 billion in sales in the three months that ended in September, up 13% from a year earlier. Profit hit $22.3 billion, up 27%. The results beat analyst expectations and Microsoft's own estimates. Microsoft had told investors that A.I. wouldn't start producing meaningful results until after the start of 2024, when more products became widely available. The company and its competitors are racing to put generative A.I. into nearly every product they offer. Microsoft is seen by many companies as a leading A.I. provider, thanks to its partnership with — and $13 billion investment in — the start-up OpenAI, which introduced the chatbot ChatGPT almost a year ago. Microsoft's flagship cloud computing product, Azure, grew 29%, up from 26% in the previous quarter. About three percentage points of Azure's growth came from generative A.I. products, including the access Microsoft provides to OpenAI's GPT-4 language model, more than the company had told investors to expect. More than 18,000 organizations are using Microsoft's Azure OpenAI services, Satya Nadella, the company's chief executive, said in a call with investors. He said that included customers who had not used Azure before. "Azure again took share as organizations took their workloads to our cloud," Mr. Nadella said... The company said that sales could increase as much as 8.7% in the current quarter, exceeding investor expectations, and that it was investing in building data centers to support the demand for A.I. and cloud computing... Microsoft's personal computing business grew just 3%, to $13.7 billion, reflecting how consumer behaviors have shifted since the laptop-buying binges of the pandemic. The revenue of the Windows operating system installed on new computers was up 4%. Gaming provided a consumer bright spot, with Xbox content and services up 13%. Next month Microsoft integrates its Copilot AI product into its Excel/Word/Teams "productivity suite" — but Microsoft CEO Satya Nadella said that 40% of Fortune 100 companies have already been testing the feature during its "limited preview", and "so far, so good." Yet the article notes it isn't all good news for Microsoft. Investment bank UBS has told investors that while Microsoft integrated an AI-powered chatbot into its Bing search engine, there is "no evidence" that Bing has actually gained any search market share. Read mor

How Microsoft's AI Investment is Stabilizing Its Cloud Business: ZDNet reports an interesting static from Microsoft's CEO Satya Nadella. "We have over 1 million paid Copilot users in more than 37,000 organizations that subscribe to Copilot for business, with significant traction outside the United States." And Microsoft's quarterly results also "showed early signs that the company's investments in generative AI were beginning to bolster sales, most notably reversing what had been slowing growth of the company's important cloud computing product," reports the New York Times. (Alternate URL here.) The company had $56.5 billion in sales in the three months that ended in September, up 13% from a year earlier. Profit hit $22.3 billion, up 27%. The results beat analyst expectations and Microsoft's own estimates. Microsoft had told investors that A.I. wouldn't start producing meaningful results until after the start of 2024, when more products became widely available. The company and its competitors are racing to put generative A.I. into nearly every product they offer. Microsoft is seen by many companies as a leading A.I. provider, thanks to its partnership with — and $13 billion investment in — the start-up OpenAI, which introduced the chatbot ChatGPT almost a year ago. Microsoft's flagship cloud computing product, Azure, grew 29%, up from 26% in the previous quarter. About three percentage points of Azure's growth came from generative A.I. products, including the access Microsoft provides to OpenAI's GPT-4 language model, more than the company had told investors to expect. More than 18,000 organizations are using Microsoft's Azure OpenAI services, Satya Nadella, the company's chief executive, said in a call with investors. He said that included customers who had not used Azure before. "Azure again took share as organizations took their workloads to our cloud," Mr. Nadella said... The company said that sales could increase as much as 8.7% in the current quarter, exceeding investor expectations, and that it was investing in building data centers to support the demand for A.I. and cloud computing... Microsoft's personal computing business grew just 3%, to $13.7 billion, reflecting how consumer behaviors have shifted since the laptop-buying binges of the pandemic. The revenue of the Windows operating system installed on new computers was up 4%. Gaming provided a consumer bright spot, with Xbox content and services up 13%. Next month Microsoft integrates its Copilot AI product into its Excel/Word/Teams "productivity suite" — but Microsoft CEO Satya Nadella said that 40% of Fortune 100 companies have already been testing the feature during its "limited preview", and "so far, so good." Yet the article notes it isn't all good news for Microsoft. Investment bank UBS has told investors that while Microsoft integrated an AI-powered chatbot into its Bing search engine, there is "no evidence" that Bing has actually gained any search market share. Read mor

Good effort by Richard Waters in cutting through the Big Tech cloud/GenAI hype-storm. He makes some critical points, including that very little of the Q1 revenue had anything to do with GenAI, and that all the Big Techs have committed to spending obscene amounts of capital. Another point most forget is the change in depreciation -- extending the life of chips for accounting purposes added $billions in profits. Let's take Microsoft, for example, as they reported the most revenue from GenAI products. How much of that revenue was sourced from MSFT strategic investments like OpenAI whose CEO has said he's willing to burn $50 billion a year chasing AGI? OpenAI alone might account for a quarter of Azure's AI revenue -- all of LLM chatbot investments perhaps half. Should cloud services spend from LLM investments be recorded as revenue for Microsoft? Probably not. It's MSFT's capital investment being recirculated back as cloud revenue. What's the margin on these LLM investments? Probably negative for everyone but chip makers and cloud vendors, unless factoring in capex, in which case I suspect it's still a loss for cloud vendors. The underlying problem is consumer LLMs are not only very costly--probably a deep loss even before copyright compensation, and use an insane amount of power and water, but are also inherently insecure and inaccurate due to the nature of the technology. Moreover, they are mostly unnecessary. Precision data management systems like the patented core of our KOS are far more efficient, and frankly much more intelligent from an enterprise perspective. 1) No copyright infringement or related liability or repetitional risk, not to mention risking the entire product investment if SCOTUS rules against LLMs. 2) Much less risk and much greater accuracy. We don't use language models except for GenAI (compartmentalized) -- not for most of the personalized learning, not for intel, not for risk management and prevention, and not for most of the productivity. 3) We reduce financial and environmental costs over LLMs by about 90% off the top due mostly to focus on high quality data vs boiling the entire human knowledge base. A glaring omission from the discussion is the assumption (still) that Big Techs will dominate AI, which is not necessarily the case at all. That wrongly presumes LLMs are the best method for customers when in fact LLMs are the best for Big Techs (in the near term, but could be disastrous in the mid term). https://lnkd.in/gyAag5_U

Lately I've been very caught working on an extremely ambitious and unprecedented AI project for one of our major Enterprise Clients that unfortunately I cannot disclose, but what I can disclose of this is the amazing collaboration I had with the Google / Google Cloud team on this project. Google & I share a common vision for Enterprise AI and our collaboration towards a common client and project was thus met with excitement and enthusiasm, and I was very happy to see the Google team matching my drive at each step. Google Vertex AI platform's modular architecture and advanced MLOps capabilities, as well as its tight integration with Google Cloud services made it the right choice for this project and I am happy that it did! I believe it's only the start of the many projects we will further develop together using their amazing Vertex AI platform. 👉 Check out more about our collaboration here: https://lnkd.in/d4D-qQPz The project is being developed using Google's Vertex AI platform, and as such I will soon follow-up with a more technical article of the Google / Google Cloud Vertex AI platform and how to use it for Enterprise AI Applications Development. Do leave a comment below if you'd be interested to see this soon. 👇 #AI #ML #Engineering #Google

Did you hear how Google Cloud and Hugging Face have teamed up to make it easy for developers on Hugging Face to serve and train their AI models with Vertex AI or GKE.

How Microsoft's AI Investment is Stabilizing Its Cloud Business: ZDNet reports an interesting static from Microsoft's CEO Satya Nadella. "We have over 1 million paid Copilot users in more than 37,000 organizations that subscribe to Copilot for business, with significant traction outside the United States." And Microsoft's quarterly results also "showed early signs that the company's investments in generative AI were beginning to bolster sales, most notably reversing what had been slowing growth of the company's important cloud computing product," reports the New York Times. (Alternate URL here.) The company had $56.5 billion in sales in the three months that ended in September, up 13% from a year earlier. Profit hit $22.3 billion, up 27%. The results beat analyst expectations and Microsoft's own estimates. Microsoft had told investors that A.I. wouldn't start producing meaningful results until after the start of 2024, when more products became widely available. The company and its competitors are racing to put generative A.I. into nearly every product they offer. Microsoft is seen by many companies as a leading A.I. provider, thanks to its partnership with — and $13 billion investment in — the start-up OpenAI, which introduced the chatbot ChatGPT almost a year ago. Microsoft's flagship cloud computing product, Azure, grew 29%, up from 26% in the previous quarter. About three percentage points of Azure's growth came from generative A.I. products, including the access Microsoft provides to OpenAI's GPT-4 language model, more than the company had told investors to expect. More than 18,000 organizations are using Microsoft's Azure OpenAI services, Satya Nadella, the company's chief executive, said in a call with investors. He said that included customers who had not used Azure before. "Azure again took share as organizations took their workloads to our cloud," Mr. Nadella said... The company said that sales could increase as much as 8.7% in the current quarter, exceeding investor expectations, and that it was investing in building data centers to support the demand for A.I. and cloud computing... Microsoft's personal computing business grew just 3%, to $13.7 billion, reflecting how consumer behaviors have shifted since the laptop-buying binges of the pandemic. The revenue of the Windows operating system installed on new computers was up 4%. Gaming provided a consumer bright spot, with Xbox content and services up 13%. Next month Microsoft integrates its Copilot AI product into its Excel/Word/Teams "productivity suite" — but Microsoft CEO Satya Nadella said that 40% of Fortune 100 companies have already been testing the feature during its "limited preview", and "so far, so good." Yet the article notes it isn't all good news for Microsoft. Investment bank UBS has told investors that while Microsoft integrated an AI-powered chatbot into its Bing search engine, there is "no evidence" that Bing has actually gained any search market share. Read mor

Amazon debuts AI cloud assistant Q Amazon unveiled a new AI-powered assistant called Q, promising to reshape how AWS customers build, manage and run cloud workloads. Designed expressly for business settings, Q allows querying 17 years of Amazon Web Services (AWS) knowledge to get infrastructure and workload recommendations tuned to a company's specific apps and data. Users can customize Q by linking internal sources like Jira and Salesforce for organization-aware responses. But Q moves beyond answering questions. It can proactively notify teams over Slack, generate summaries and content, and automate tasks like creating tickets through configurable plugins. On stage, AWS CEO Adam Selipsky demonstrated Q suggesting optimized Amazon EC2 configurations for a video encoding app based on cost and performance considerations. "Q is going to be transformative. We want all different types of workers to benefit," Selipsky stated, positioning Q as a time-saving expert for development, maintenance and more. The launch signals Amazon's expanding push into verticalized, workflow-aware AI solutions locking customers within its ecosystem. With Q, Amazon aims to become the intelligent layer connecting teams to the knowledge, systems and data central to their jobs. #artificialintelligence #ai #cloud More information: https://lnkd.in/eGA_22mM https://aws.amazon.com/q/ https://lnkd.in/eWTuQvgz

An overview of Google Cloud Dataflow’s key new capabilities: Autotuning: Autotuning is at the foundation of Dataflow,when large-scale distributed systems is handling data in motion is challenging, so the function of Automating becomes more important,Dataflow team implemented the following autotuning features: • Asymmetric autoscaling to improve performance by independently scaling user workers and backend resources. • In-flight job option updates to allow customers to update autoscaling parameters for long-running streaming jobs without downtime. • Fast worker handover • Intelligent autoscaling • Intelligent downscale dampening • Autosharding for BigQuery Storage Write API: Autosharding dynamically adjusts the number of shards for BigQuery writes so that the throughput keeps up with the input rate. Performance and efficiency • Dynamic thread scaling:They built a system that automatically and dynamically adjusts the number of threads to deliver better efficiency. • Vertical autoscaling for batch jobs:Vertical autoscaling works hand in hand with horizontal autoscaling to automatically adjust the amount of resources (specifically memory) to prevent job failures because of out of memory errors. • ARM processors in Dataflow • SDK (Apache Beam) performance improvements Machine Learning: Machine Learning relies on have good data and the ability to process that data. Many of you use Dataflow today to process data, extract features, validate models and make predictions,earlier this year they launched RunInference, a Beam transform for doing ML predictions. It replaces complex, error-prone, and often repetitive code with a simple built-in transform. RunInference lets us focus on our pipeline code and abstracts away the complexity of using a model, allowing the service to optimize the backend for your data applications, Google is now adding a number of new features and enhancements to RunInference. • Dead-letter queue  • Pre/post–processing operations  • Support for remote inference with Vertex AI endpoints in VertexAIModelHandler. please read this article if you want more details. cr:Google Cloud Blog

Are you a CTO or Developer at a #Startup or #SaaS company and interested in Microsoft Cloud and AI? Check out this essential list of Microsoft Build sessions curated just for you: https://lnkd.in/grzc-FpW