- AWS used its NYC summit to talk up its dominance in AI
- An exec claimed that many on of the top AI models are on AWS
- In fact, the cloud remains crucial to AI growth
Amazon Web Services (AWS) chose a blistering Wednesday in Manhattan to talk about generative artificial intelligence (GenAI) at the delightful Jacob Javits Convention Center on the west side.
It was so hot — in fact — that even the bomb-sniffing dogs at the Javits were sweating (see dog, right). Yet despite this, Amazon said the GenAI's head remains firmly in clouds.
![Bomb sniffing dog](https://qtxasset.com/quartz/qcloud4/styles/half_body_width/s3/media/image/dog_0_0.jpg?VersionId=B7.UpumQjmdmWJHxSJz5rRDdZ64lVdGH&itok=7nspW-AK)
AWS, however, was here to get you get jazzed about the possibilities and uses of Gen AI. At the summit, the company announced eight AI enhancements on the day of show, as hundreds of people took in the keynote, break-out sessions and exhibits at the show.
Matt Wood, VP of artifical intelligence at AWS, highlighted the company's dominance in the GenAI field among cloud providers during his keynote.
"We've launched 326 generative AI features into general availability since 2023," he said from the stage. "If you look at the numbers you can see that AWS has launched more than twice as many new capabilities for machine learning and generative AI than all of the other cloud providers combined."
![Photo by Dan Jones](https://qtxasset.com/quartz/qcloud4/styles/half_body_width/s3/media/image/wood.jpg?VersionId=sQsZf5Y.Nr14ngdvYM4PLMDPpPF5p42S&itok=C9oFc89W)
Wood, in fact, said in the keynote that GenAI would be tied at the hip with cloud — and thus AWS — for the foreseeable future.
"The foundation for AI is the cloud," he said, noting that the main workloads running now are training models (large language models, etc.,) and workloads running inference — or predictions — running those models.
"The vast majority of the successful models out there are enabled by foundational infrastructure and innovations on AWS," Wood claimed. He named Anthropic and Mistral AI models as notable examples, as well as Stability AI and all the work going on around Hugging Face.