Othman Laraki

The AI Revolution in Cancer: Grab your musket & don't wait for a silver bullet. Ask any AI frontier lab leader what AI will do for humanity and "cure cancer" tops every list. The image is always the same: miracle drugs. That's not how it's actually playing out. ...

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We directly served about 750,000 participants and they serve the global community by contributing to one of humanity's largest and most diverse healthcare datasets.

Huge milestone to see the @AllofUsResearch data release of one of @NIH largest ever projects, where @Color was a major contributor. Proud moment for us and we hope a big step in biomedical research. nytimes.com/2026/06/30/sci…

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A Nature Medicine study found general-purpose LLMs are now outperforming dedicated medical AI products on physician-reviewed clinical tasks. The authors compared OpenEvidence and UpToDate Expert AI with GPT-5.2, Gemini 3.1 Pro, and Claude Opus 4.6 on medical exam questions, clinician-style answers, and real questions doctors asked during care. In 100 de-identified physician questions from live clinical use, blinded clinicians again preferred the frontier models, especially on completeness and clarity,

@km Woot!!!! Congrats @km and @stevejang!

so grateful to get to live in this incredible time, and do this interesting work. thank you all for the friendship and support.

"The single most effective team/collaboration AI product @Color has used 🚀" - @othman

A no prize for pessimism note from Tyler Cowen.

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jfc....

Nearly 90% of large employers now cite cancer as one of their top three cost drivers. In a new Nasdaq.com op ed, PICI CEO @DrKarenKnudsen and @Color CEO @othman discuss what they call“the triple wave” driving this trend: rising cancer diagnoses among younger populations, increased complex and costly treatments, and a growing survivor workforce requiring long-term treatment. In the piece, they outline steps employers can take to move from reactive management to proactive cancer care strategies. Read the full piece here: nasdaq.com/articles/how-c…

Built with Google AI, Color Health’s Virtual Cancer Clinic helps make high quality cancer care more accessible.

This is how Morocco announced their World Cup squad 🇲🇦

Agents should have access to every system. Introducing Integuru: generate fast, reliable APIs for any platform⚡️ API calls complete in ~3 seconds with 99.9%+ success. No browsers or RPA. No data caching needed. With auth support. @InteguruAI is free to use. Thread below.

“can i start you off with an appetizer, maybe 30 tortillas?” “god no, i can’t eat that many tortillas!” “how about if cut them up into triangles, fry them in seed oil, & serve them with some salsa?” “omg that sounds delightful”.

I wonder if the apparent weakness of AI not being able to identify interesting research directions is a false equivalency more than a weakness. When we say that humans identify interesting research directions, we are talking about the collective and ignore the fact that most research directions or ideas we individually come up with are not that great. As a collective, between all the shots on goal, a few are legitimately interesting and when those happen, the collective knows how to recognize it (sometimes). The more apt comparison would be to see if many AI systems in parallel (with a variety of temperature settings, training datasets, etc) would (a) be able to explore a space and (b) identify novel & interesting findings. It could be that many of the lack of creativity / taste types of critiques are less fundamental capability problems but rather the types of experiments we run.

I think we are in the process of discovering that humans are bad at mathematics. A gibbon would scoff at an Olympic climber; the human body is not optimized for climbing. We're getting mounting evidence that our brain may be far from optimal for advanced math. No disrespect to mathematicians. I was a two-time IMO silver medalist; I'm just smart enough to appreciate that some people are much, much smarter. But it's starting to look like math is somewhere on the midpoint of Moravec’s paradox; between chess (computers surpassed us some time back) and cooking (probably many years to go, for general capabilities). It's fairly hard for us, and so it looks like computers are going to surpass us. AI math still has important weaknesses. For instance, AI systems have not yet shown any ability to identify interesting research directions, or develop new concepts on which further work can build. But they are starting to look superhuman in some respects. And once AI *starts* to become superhuman in some domain, we all know what happens next.

The latest IQ test involves data centers and water.

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See also: Color Health moving deeper into cancer services, complete with virtual ‘tumor boards’ statnews.com/2026/05/06/can… #PM101