Garman told WIRED ahead of the event that Amazon will also introduce a range of tools to help customers wrangle generative AI models that he says are often too expensive, unreliable, and unpredictable.
These include a way to boost the capabilities of smaller models 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, for recommending products on its ecommerce platform and other tasks, but it primarily serves as a platform to help other firms build their own AI programs.
While Amazon does not have a ChatGPT-type product to advertise its AI capabilities, the scope of its cloud services will give it an advantage selling generative AI to others, says Steven Dickens, CEO and principal analyst at HyperFRAME Research. “The breadth of AWS—that’s going to be an interesting thing,” he says.
Amazon’s own line of chips will help it make the AI software it sells more affordable. “Silicon is going to have to be a key part of the strategy of any hyperscaler going forward,” says Dickens, referring to cloud providers that offer hardware for building the very largest, 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 now moving on from demos to building commercially viable products and services incorporating generative AI. “One of the things that we’re quite excited about is having customers move from having their AI experiments and proof of concepts,” he told WIRED.
Garman says that 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 newly announced AWS service called Model Distillation, for instance, can produce a smaller model that is faster and less expensive to run while still having similar capabilities to a larger one. “Let’s say you’re an insurance company,” Garman says. “You can take a whole set of questions, feed those into a really advanced model, and then use that to train the smaller model to be an expert on those things.”
Another new cloud tool announced today, Bedrock Agents, can be used to create and manage so-called AI agents that automate useful tasks such as customer support, order processing, and analytics. It includes a master agent that will manage a team of AI underlings, providing reports on how they function and coordinating changes. “You can basically go create an agent that says you’re the boss of all the other agents,” Garman says.
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