{"id":20840,"date":"2026-02-05T21:05:09","date_gmt":"2026-02-05T21:05:09","guid":{"rendered":"https:\/\/nationalgunowner.org\/index.php\/2026\/02\/05\/sara-hooker-raises-50m-to-challenge-a-i-s-conventional-wisdom\/"},"modified":"2026-02-05T21:05:12","modified_gmt":"2026-02-05T21:05:12","slug":"sara-hooker-raises-50m-to-challenge-a-i-s-conventional-wisdom","status":"publish","type":"post","link":"https:\/\/nationalgunowner.org\/index.php\/2026\/02\/05\/sara-hooker-raises-50m-to-challenge-a-i-s-conventional-wisdom\/","title":{"rendered":"Sara Hooker Raises $50M to Challenge A.I.\u2019s Conventional Wisdom"},"content":{"rendered":"
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Sara Hooker\u2019s new startup, Adaption Labs, argues that algorithmic innovation, not scale, will define the next era of A.I. Courtesy Adaption<\/span><\/figcaption><\/figure>\n

Sara Hooker<\/a>, a computer scientist known for her work on machine learning<\/a> at Google<\/a> and Canadian A.I. startup Cohere<\/a>, has spent the past few years doing her \u201ctour of duty\u201d across some of the A.I. industry\u2019s most competitive frontier labs.<\/a> Now, she\u2019s striking out on her own\u2014and taking a rebellious stance against the industry\u2019s most ingrained principles. Hooker and her co-founder, Sudip Roy<\/a>, have raised $50 million for their new startup, Adaption Labs, they announced yesterday (Feb. 4). The company is centered around the premise that efficient, self-learning training methods\u2014not mass amounts of data and energy\u2014will lead to the best models.<\/p>\n

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\u201cMost of A.I. progress is: you build the biggest model, and then you ship the same model to billions of people around the world; no matter what language, what industry, what enterprise,\u201d Hooker told Observer. \u201cThis is a radical departure from that.\u201d<\/p>\n

Her ambitious wager has grabbed the attention of Silicon Valley. The San Francisco-based startup\u2019s round was led by Emergence Capital Partners, with participation from Mozilla Ventures, Fifty Years, Threshold Ventures, Alpha Intelligence Capital, e14 Fund and Neo. Adaption Labs declined to share details of its valuation.<\/p>\n

Conventional wisdom in A.I. suggests that more compute leads to bigger and more capable models. But Adaption Labs believes that approach has hit a wall. \u201cOne of our core beliefs is that no frontier A.I. lab is going to quadruple the size of their model for the next year,\u201d said Hooker. \u201cThat means all bets are off.\u201d<\/p>\n

Instead, Hooker is interested in experimenting with building models that can learn continuously and adapt to workloads in real time as they interact with different environments. User feedback, for example, should immediately change the behavior of A.I. tools instead of being \u201clost in a vacuum.\u201d An emphasis on efficiency at Adaption Labs will also include exploring ideas like \u201cgradient-free learning,\u201d which looks for alternatives to traditional training methods that rely on optimization algorithms to adjust model parameters in an effort to minimize errors.<\/p>\n

Hooker and Roy are poised to disrupt an industry that they have spent their careers advancing. Both worked for years at Google before moving on to Cohere, where Hooker acted as vice president of research, and Roy served as senior director of inference. Despite departing Cohere last year, Hooker said she is \u201cproud\u201d of the work she did, which included a focus on multilingual model development. But Adaption Labs\u2019 goals of enabling adaptive data, intelligence and interfaces wouldn\u2019t be achievable within a traditional frontier lab, she said, due to those areas being split across different teams. \u201cIt\u2019s much easier to start with that urgency of putting them all on the same pillar from the beginning,\u201d she said.<\/p>\n

Adaption Labs isn\u2019t alone in going against the grain. A growing chorus of voices in Silicon Valley has begun to question the industry\u2019s dominant assumptions. Yann LeCun<\/a>, who recently left Meta<\/a> to launch AMI Labs, has raised doubts about traditional scaling law principles; so has David Silver<\/a>, a former Google DeepMind<\/a> researcher whose startup, Ineffable Intelligence, focuses on training self-learning models through experience rather than feeding them data<\/a>.<\/p>\n

Hooker\u2019s fresh funding is primarily earmarked for building out a team. Adaption Labs is currently hiring for 10 roles, some of which can be based in global locations such as Turkey, Mexico and Brazil. Staffers are also offered a distinctive perk: an \u201cAdaptive Passport\u201d that allows them to take an annual trip to a country they\u2019ve never visited before. \u201cWe want to encourage people to not only explore, but we want to represent that we\u2019re a global technology company from day one,\u201d said Hooker. Roy was the first to take advantage of the benefit, using it for a trip to Costa Rica last year.<\/p>\n

Hooker expects that a reckoning of traditional scaling laws as major A.I. developers confront the reality that ever-greater computing power is yielding diminishing returns. Algorithmic innovation will be the real driver of progress. \u201cThis is the year in which it will really matter,\u201d she said.<\/p>\n

\t\t\t\t\"Sara<\/p><\/div>\n