Garman told WIRED ahead of the event that Amazon will also introduce a range of tools to support customers negotiate generative AI models, which he says are often too costly, unreliable and unpredictable.
These include a way to extend the capabilities of smaller models using larger ones, a system to manage hundreds of different AI agents, and a tool that provides proof that the chatbot’s output is valid. Amazon builds its own artificial intelligence models to recommend products on its e-commerce platform and for other tasks, but primarily serves as a platform to support other companies build their own artificial intelligence programs.
While Amazon doesn’t have a product like ChatGPT to tout its AI capabilities, its range of cloud services will give it an advantage in selling generative AI to others, says Steven Dickens, CEO and principal analyst at HyperFRAME Research. “The expanded scope of AWS — that’s going to be an interesting thing,” he says.
Amazon’s own line of chips will support make the AI software it sells more affordable. “Silicon will need to be a key part of every hyperscaler’s strategy in the future,” says Dickens, referring to cloud providers offering the hardware to create the largest and most productive AI. He also notes that Amazon has been developing its custom silicon longer than competitors.
Garman says an increasing number of AWS customers are now moving from demos to building commercially viable products and services using generative AI. “One of the things that we’re really excited about is that customers are moving away from AI experiments and proof-of-concepts,” he told WIRED.
Garman says many customers are much less interested in pushing the boundaries of generative AI than in finding ways to make the technology cheaper and more reliable.
For example, a newly announced AWS service called Model Distillation can create a smaller model that is faster and cheaper to run, while having similar capabilities to the larger one. “Let’s say you run an insurance company,” Garman says. “You can take a whole set of questions, feed them into a really advanced model, and then use that to train a smaller model to become an expert on those things.”
Another fresh cloud tool announced today, Bedrock Agents, can be used to create and manage so-called AI agents that automate useful tasks such as customer service, order processing and analytics. It includes a main agent who will manage a team of AI subordinates, providing reports on their functioning and coordinating changes. “You can basically create an agent that claims you are the boss of all the other agents,” Garman says.