By now, you’d be hard pressed to find anyone who isn’t broadly familiar with the AI heavyweights and their flagship models. OpenAI has ChatGPT, Anthropic has Claude, Google has Gemini. But what does Amazon have?
Not a whole lot, it turns out. Unlike its competitors in the tech megacorp scene, Amazon’s standout AI model — organized under the name “Nova” — is about the farthest thing from a household name. And that’s not likely to change anytime soon, because the ecommerce giant is now gutting its in-house AI labs, Bloomberg reports.
Per the outlet, Amazon is scaling back the ambitions of most of its Nova AI models and reorganizing its AI development teams as part of an effort to narrow its focus on “highest priority” goals, after its power-hungry large language models turned out to be a bust.
Accordingly, the company has put most of its AI models on ice, Amazon insiders told Bloomberg. This includes its text-based Nova models, as well as video- and image-generating models, all of which have been placed in a state of “keep the lights on,” meaning they’re technically still supported, but only receive the bare minimum resources needed to sustain them.
Instead, labor and computing power are being diverted toward a singular “frontier-model effort” led by Pieter Abbeel, director of the Berkeley Robot Learning Lab whose robotics company Covariant was hoovered up by Amazon in 2024. At the time Abbeel joined the tech giant, Covariant’s founders were working on AI models for robots, which lines up pretty well with Amazon’s push to automate everything it possibly can.
News of the shift in Amazon’s strategic focus comes a week after it closed one of its key AI offices in San Francisco, an 80-person site specializing in research on artificial general intelligence, the supposed next-level of AI development where the tech obtains human-level intelligence and reasoning skills.
With urgent questions swirling over whether LLMs can ever usher in a return on investment — let alone AGI — it may be that Amazon is jumping out of the AI hype cycle while it still can.
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