Garman told WIRED ahead of the event that Amazon will also introduce a number of tools to help customers discuss generative AI models, which he says are often too expensive, unreliable and unpredictable.
These include a way to increase the capabilities of smaller models by using larger ones, a system for managing hundreds of different AI agents, and a tool that provides proof that a chatbot’s output is correct. Amazon builds its own AI models to recommend products on its e-commerce platform and other tasks, but it mainly serves as a platform to help other companies build their own AI programs.
While Amazon doesn’t have a ChatGPT-type product to advertise its AI capabilities, the reach of its cloud services will give it an edge in selling generative AI to others, says Steven Dickens, CEO and principal analyst at HyperFRAME Research. “The breadth of AWS, it’s going to be an interesting thing,” he says.
Amazon’s own line of chips will help make the AI software it sells more affordable. “Silicon will have to be a key part of any hyperscaler’s strategy in the future,” says Dickens, referring to the cloud providers that provide hardware to build the largest and most capable AI. He also notes that Amazon has been developing its custom silicon for longer than competitors.
Garman says a growing number of AWS customers are moving from demos to building commercially viable products and services that incorporate generative AI. “One of the things we’re excited about is customers moving from having their AI experiments and proofs of concepts,” he told WIRED.
Garman says many customers are far less interested in pushing the frontier of generative AI than in finding ways to make the technology cheaper and more reliable.
A recently announced AWS service called Model Distillation, for example, can produce a smaller model that is faster and less expensive to run while having similar capabilities to a larger one. “Let’s say you’re an insurance company,” says Garman. “You can ask a whole set of questions, feed them into a really advanced model, and then use that to train the smaller model to be an expert on these things.”
Another new cloud tool announced today, Bedrock Agents, can be used to build and manage so-called AI agents that automate useful tasks such as customer support, order processing and analytics. It includes a master agent who will manage a team of AI subordinates, providing reports on how they are performing and coordinating changes. “You can basically create an agent that says you’re the boss of all the other agents,” says Garman.
