Garman told WIRED ahead of the event that Amazon will also introduce a set of tools to help customers grapple with generative AI models, which he says are often too expensive, unreliable and unpredictable.
These include a way to augment 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 to recommend products on its e-commerce platform and other tasks, but it mainly serves as a platform to help other businesses build their own AI programs.
While Amazon doesn’t have a ChatGPT-type product to tout its AI capabilities, the breadth of its cloud services will give it an edge in selling generative AI to others, said Stephen 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 artificial intelligence software it sells more affordable. “Silicon is going to have to be a key part of any hyperscaler’s strategy going forward,” says Dickens, referring to the cloud providers that offer the hardware to build the biggest and most capable AI. He also notes that Amazon has been developing its custom silicon longer than competitors.
Garman says a growing number of AWS customers are now moving from demos to building commercially viable products and services involving generative AI. “One of the things we’re very excited about is customers giving up their AI and proof-of-concept experiments,” he told WIRED.
Garman says many customers are far less interested in pushing the boundaries 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 cheaper 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, load them into a really advanced model, and then use that to train the smaller model to be an expert on those things.”
Another new cloud-based 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 who will manage a team of AI subordinates, providing reports on how they are performing and coordinating changes. “Basically, you can create an agent that says you’re the boss of all the other agents,” says Garman.
