Amazon CEO Andy Jassy touts AI push in shareholder letter

Amazon CEO Andy Jassy outlined the e-commerce giant’s approach to artificial intelligence (AI) development in his annual letter to shareholders released Thursday.

Jassy wrote that Amazon aims to “empower builders, inside and outside of our company,” with its approach to developing products and services for customers. He went on to characterize builders as “people who like to invent” and go through the process of iterative improvements to enhance an existing tool or experience.

“What matters to builders is having the right tools to keep rapidly improving customer experiences,” he wrote. “The best way we know how to do this is by building primitive services. Think of them as discrete, foundational building blocks that builders can weave together in whatever combination they desire.”

In the context of generative AI (GenAI), Jassy explained that Amazon and AWS have applied this approach to their AI initiatives so that they meet different needs.


Amazon CEO Andy Jassy

Amazon CEO Andy Jassy touted the company’s AI push in his letter to shareholders. (Kevin Winter/Getty Images / Getty Images)

“Much of the early public attention has focused on GenAI applications, with the remarkable 2022 launch of ChatGPT,” he said. “But, to our ‘primitive’ way of thinking, there are three distinct layers in the GenAI stack, each of which is gigantic, and each of which we’re deeply investing.

“The bottom layer is for developers and companies wanting to build foundation models (‘FMs’). The primary primitives are the computer required to train models and generate inferences (or predictions), and the software that makes it easier to build these models,” he explained.

“To date, virtually all the leading FMs have been trained on Nvidia chips, and we continue to offer the broadest collection of Nvidia instances of any provider,” Jassy noted. “That said, supply has been scarce and cost remains an issue as customers scale their models and applications.”

Jassy wrote that, in response to customers’ requests for Amazon to “push the envelope on price-performance for AI chips” like it did with Gravitron generalized CPU chips, the company has built custom AI training chips called Trainium and inference chips dubbed Inferentia.


AWS Amazon Q AI Assistant

The Amazon Q AI tool helps businesses analyze their data. (Jaap Arriens/NurPhoto via Getty Images / Getty Images)

He noted that, last fall, leading FM maker Anthropic announced it would use Trainium and Inferentia chips to build, train and deploy those models and that those chips are now into their second version with improved cost and performance.

“The middle layer is for customers seeking to leverage an existing FM, customize it with their own data, and leverage a leading cloud provider’s security and features to build a GenAI application – all as a managed service,” Jassy said. 

“Amazon Bedrock invented this layer and provides customers with the easiest way to build and scale GenAI applications with the broadest selection of first- and third-party FMs, as well as ease-of-use capabilities that allow GenAI builders to get higher quality model outputs more quickly.

“The top layer of this stack is the application layer. We’re building a substantial number of GenAI applications across every Amazon consumer business.” 


Amazon App

Amazon released the Rufus AI-powered shopping assistant last year. (Photo Illustration by Sheldon Cooper/SOPA Images/LightRocket via Getty Images / Getty Images)

Jassy explained that those GenAI apps include new AI-powered shopping assistant Rufus, a more intelligent version of Alexa; advertising capabilities that allow users to generate images; videos and copy using natural language; and productivity apps for customers and sellers.

The company is also building apps within AWS, including what Jassy called “arguably the most compelling early GenAI use case – a coding companion.” 

“We recently launched Amazon Q, an expert on AWS that writes, debugs, tests, and implements code, while also doing transformations (like moving from an old version of Java to a new one), and querying customers’ various data repositories (e.g. Intranets, wikis, Salesforce, Amazon S3, ServiceNow, Slack, Atlassian, etc.) to answer questions, summarize data, carry on coherent conversation, and take action,” he explained. “Q is the most capable work assistant available today and evolving fast.”


Jassy said AWS’ AI initiatives meeting those varying customer needs will help propel the next phase of AI development internally and externally.

“These AWS services, at all three layers of the stack, comprise a set of primitives that democratize this next seminal phase of AI, and will empower internal and external builders to transform virtually every customer experience that we know (and invent altogether new ones as well). We’re optimistic that much of this world-changing AI will be built on top of AWS,” Jassy wrote.

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