As we make our way to AWS re:Invent today in Las Vegas, these are some of the questions on our mind: Will Amazon CEO Andy Jassy make another appearance? Will this, in fact, be Amazon CTO Werner Vogels’ last big closing keynote at the event? Will we be able to line up early enough to score a seat inside the special Acquired podcast recording Thursday morning? 

And how many million enterprise AI billboards will we see between the airport and the Venetian?

But more to the point for Amazon, the company faces a critical test this week: showing that its heavy artificial intelligence investments can pay off as Microsoft and Google gain ground in AI and the cloud.

A year after the Seattle company unveiled its in-house Nova AI foundation models, the expansion into agentic AI will be the central theme as Amazon Web Services CEO Matt Garman takes the stage Tuesday morning for the opening keynote at the company’s annual cloud conference.

The stakes are big, for both the short and long term. AWS accounts for a fifth of Amazon’s sales and more than half of its profits in many quarters, and all the major cloud platforms are competing head-to-head in AI as the next big driver of growth.

With much of the tech world focused on the AI chip race, the conference will be closely watched across the industry for news of the latest advances in Amazon’s in-house Trainium AI chips. 

But even as the markets and outside observers focus on AI, we’ve learned from covering this event over the years that many AWS customers still care just as much or more about advances in the fundamental building blocks of storage, compute and database services.

Amazon gave a hint of its focus in early announcements from the conference:

• The company announced a wave of updates for Amazon Connect, its cloud-based contact center service, adding agents that can independently solve customer problems, beyond routing calls. Amazon Connect recently crossed $1 billion in annual revenue.
• In an evolution of the cloud competition, AWS announced a new multicloud networking product with Google Cloud, which lets customers set up private, high-speed connections between the rival platforms, with an open specification that other providers can adopt. 
• AWS Marketplace is adding AI-powered search and flexible pricing models to help customers piece together AI solutions from multiple vendors.

Beyond the product news, AWS is making a concerted effort to show that the AI boom isn’t just for the big platforms. In a pitch to consultants and integrators at the event, the company released new research from Omdia, commissioned by Amazon, claiming that partners can generate more than $7 in services revenue for every dollar of AWS technology sold.

Along with that research, AWS launched a new “Agentic AI” competency program for partners, designed to recognize firms building autonomous systems rather than simple chatbots.

Garman’s keynote begins at 8 a.m. PT Tuesday, with a dedicated agentic AI keynote from VP Swami Sivasubramanian on Wednesday, an infrastructure keynote on Thursday morning, and Vogels’ aforementioned potential swan song on Thursday afternoon. 

Stay tuned to GeekWire for coverage, assuming we make it to the Strip!

Microsoft says it has linked massive data centers in Wisconsin and Atlanta — roughly 700 miles and five states apart — through a high-speed fiber-optic network to operate as a unified system.

The announcement Wednesday morning marks the debut of what the company is calling its AI “superfactory,” a new class of data centers built specifically for artificial intelligence. The facilities are designed to train and run advanced AI models across connected sites — a setup that Microsoft describes as the world’s first “planet-scale AI superfactory.”

Unlike traditional cloud data centers that run millions of separate applications for different customers, Microsoft says the new facilities are designed to handle single, massive AI workloads across multiple sites. Each data center houses hundreds of thousands of Nvidia GPUs connected through a high-speed architecture known as an AI Wide Area Network, or AI-WAN, to share computing tasks in real time.

Microsoft says it’s using a new two-story data center design to pack GPUs more densely and minimize latency, a strategy enabled in part by a closed-loop liquid cooling system.

By linking sites across regions, the company says it’s able to pool computing capacity, redirect workloads dynamically, and distribute the massive power requirements across the grid so that it isn’t dependent on available energy resources in one part of the country.

This unified supercomputer will train and run the next generation of AI models for key partners such as OpenAI, and for Microsoft’s own internal models.

The new approach shows the rapid pace of the AI infrastructure race among the world’s largest tech companies. Microsoft spent more than $34 billion on capital expenditures in its most recent quarter — much of it on data centers and GPUs — to keep up with what it sees as soaring AI demand.

Amazon is taking a similar approach with its new Project Rainier complex in Indiana, a cluster of seven data center buildings spanning more than 1,200 acres. Meta, Google, OpenAI and Anthropic are making similar multibillion-dollar bets, collectively putting hundreds of billions into new facilities, chips, and systems to train and deploy AI models.

Some analysts and investors see echoes of a tech bubble in the rush to build AI infrastructure, if business customers don’t realize enough value from AI in the near term. Microsoft, Amazon and others say the demand is real, not speculative, pointing to long-term contracts as evidence.

Story corrected at 11:30 a.m. PT to accurately reflect Microsoft’s announcements about which companies will have AI models trained in the facilities.

ChatGPT maker OpenAI, exercising newfound freedom under its renegotiated Microsoft partnership, will expand its cloud footprint for training and running AI models to Amazon’s infrastructure under a new seven-year, $38 billion agreement.

The deal, announced Monday, positions Amazon as a major infrastructure provider for Microsoft’s flagship AI partner, highlighting seemingly insatiable demand for computing power and increasingly complex alliances among big companies seeking to capitalize on AI.

It comes as Microsoft, Amazon, and big tech companies attempt to reassure investors who’ve grown concerned about a possible bubble in AI spending and infrastructure investment.

Under its new Amazon deal, OpenAI is slated to begin running AI workloads on Amazon Web Services’ new EC2 UltraServers, which use hundreds of thousands of Nvidia GPUs. Amazon says the infrastructure will help to run ChatGPT and train future OpenAI models.

Amazon shares rose nearly 5% in early trading after the announcement.

“Scaling frontier AI requires massive, reliable compute,” said OpenAI CEO Sam Altman in the press release announcing the deal. “Our partnership with AWS strengthens the broad compute ecosystem that will power this next era and bring advanced AI to everyone.”

Matt Garman, the AWS CEO, said in the release that Amazon’s cloud infrastructure will serve as “a backbone” for OpenAI’s ambitions.

In an interview with CNBC, Dave Brown, Amazon’s vice president of compute and machine learning services, said the new agreement represents “completely separate capacity” that AWS is building out for OpenAI. “Some of that capacity is already available, and OpenAI is making use of that,” Brown told CNBC.

Amazon has also been deepening its investment in AI infrastructure for Anthropic, the rival startup behind the Claude chatbot. Amazon has invested and committed a total of $8 billion in Anthropic and recently opened Project Rainier, an $11 billion data center complex for Anthropic’s workloads, running on hundreds of thousands of its custom Trainium 2 chips.

Microsoft has been expanding its own relationship with Anthropic, adding the startup’s Claude models to Microsoft 365 Copilot, GitHub Copilot, and its Azure AI Foundry platform

Up to this point, OpenAI has relied almost exclusively on Microsoft Azure for the computing infrastructure behind its large language models. The new deal announced by Microsoft and OpenAI last week revised that relationship, giving OpenAI more flexibility to use other cloud providers — removing Microsoft’s right of first refusal on new OpenAI workloads.

At the same time, OpenAI committed to purchase an additional $250 billion in Microsoft services. Microsoft still holds specific IP rights to OpenAI’s models and products through 2032, including the exclusive ability among major cloud platforms to offer OpenAI’s technology through its Azure OpenAI Service.

OpenAI’s new $38 billion deal with Amazon builds on a relationship that began earlier this year, when Amazon added OpenAI’s first open-weight models in five years to its Bedrock and SageMaker services. Released under an open-source license, those models weren’t bound by OpenAI’s exclusive API agreement with Microsoft, letting Amazon offer them on its platforms.

The latest announcement is part of a series of deals by OpenAI in recent months with companies including Oracle and Google — committing hundreds of billions of dollars overall for AI computing capacity, and raising questions about the long-term economics of the AI boom.