@nityasnotes

nitya's notes + building a search engine @exaailabs

San Francisco, CA
Joined December 2020
nityas notes dot com a place where I will keep track of what I’m reading and writing
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Was running through a cloud when the sun came out on this trail I’ll never forget it
Bay Area trail runs are undefeated
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search through time
We built a time machine for the web. Introducing Exa Snapshot: an index of 400 billion historical snapshots of webpages that lets you search as if it's the past. Snapshot is already being used for backtesting prediction models, RL at labs, exploring the pre-AI web, and more.
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by far the coolest product I’ve worked on at Exa so far - versioned view of the web This has taken a ton of work and it is truly just insane to see this in the wild
We built a time machine for the web. Introducing Exa Snapshot: an index of 400 billion historical snapshots of webpages that lets you search as if it's the past. Snapshot is already being used for backtesting prediction models, RL at labs, exploring the pre-AI web, and more.
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We are on the cusp of a wave of new therapies for some of the worst diseases. But the world won’t benefit unless the US fixes its drug regulatory system. My new essay for @nytimes, on how slow clinical trials are now the biggest obstacle to curing cancer. nytimes.com/2026/09/04/opini… - I interviewed dozens of researchers, especially oncologists at leading U.S. centers. A striking consensus emerged: science is no longer the main bottleneck to new cancer drugs. It is our ability to test discoveries in patients through clinical trials. - The cost of starting a Phase 1 trial in America has roughly doubled over the past decade. As a result, companies increasingly take early trials abroad: Australia’s Phase 1 trial volume has nearly doubled in a decade, driven mainly by U.S. companies. - Unfortunately, the underlying incentives are badly asymmetric: Institutions can be blamed for harms caused by moving too fast, but almost no one is blamed when patients deteriorate during avoidable delays. One doctor called the emerging system “ritualized safety over actual risk assessment.” Or as, @DavidHongMD put it: "We often forget that the biggest risk is the cancer itself." - This problem is becoming more urgent because medicine itself is changing. Sequencing, biological engineering and A.I. make increasingly personalized therapies possible. But our regulatory system was mostly built for standardized drugs tested in large populations. - @sytse, the co-founder of GitLab, shows what personalized medicine can achieve: after relapsed osteosarcoma and being told there were no options left, he pursued a highly individualized approach and has now been cancer-free for a year. But doing so required extraordinary resources and regulatory expertise. - Pierce Ogden’s father was less lucky. After molecular analysis identified a drug that might target his glioblastoma, the manufacturer agreed to provide it. But administrative barriers delayed access until it was too late. “My dad was ready to try anything,” Pierce told me. “But the system is paternalistic.” - The A.I. revolution is making this bottleneck more important, not less. A.I. relies on relevant data. Information from early-stage trials could compound with A.I. tools to achieve truly revolutionary medicines. Without the data, this is far less likely to happen. - Another important shift is that innovation increasingly comes from academic labs and small biotech companies rather than Big Pharma. These small companies find it far harder to unable to absorb delays and regulatory barriers. - Apart from cancer, China is the biggest winner from America's outdated medical regulations. China has a much faster trial system, with testing often starting a full year earlier. This allows Chinese pharmaceutical companies to experiment and improve medicines while American companies play with mice. Today, half of all drugs licensed by major pharmaceutical companies originate there, up from less than 5 percent only a decade ago. - But we don't need to copy China. The best model is Australia: lots of on-site scientific and ethics reviews, and requirements that are proportionate to small, early-stage trials. Phase 1 studies there begin roughly 6–12 months faster, without any notable increases in adverse safety events. - Operation TrialBlazer, a 2026 HHS initiative is a good start in this direction, but we need legislative action by Congress to truly make Phase I trials faster and more efficient! I want to thank everyone who helped me with this article: everyone I interviewed and the amazing editors at the Times. This is the result of a months long journey of extensive interviews and research. Special thanks go to those who came on the record. One of the features of the system is an atmosphere of fear, where practitioners are afraid to publicly come out and explain these issues. So anyone who does is a hero in my book!
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Kanagawa drew the wave he is most known for at 73, about 40 years after he started drawing them
On BM25, Stephen Robertson + people that think about the same ideas for decades
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sustained remixing is generative
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On BM25, Stephen Robertson + people that think about the same ideas for decades
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New York rewards those who still know how to look up
Bill Brand’s Masstransiscope is still incredibly cool: a vibrant zoetrope in the old Myrtle Ave station. See it from the right side of a Manhattan-bound B/Q leaving DeKalb. A fun side effect of modernizing the DeKalb Interlocking will be seeing it at full speed, as god intended.
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can't stop thinking about this movie We live in the Marvel Cinematic Universe of media, this is not that. Honest + at times uncomfortable to watch
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scenes of a marriage (1973 version by Ingmar Bergman)
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tldr: global token allocation that accounts for relevance across documents > per document, parallel selection
We’re releasing a research preview of “dynamic highlights”: Given a query and set of pages, a custom model jointly scans the whole set to filter out redundant and irrelevant info, reducing token usage 95% on average. Available today: exa.ai/blog/dynamic-highligh…
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Bf that looks handsome while beating his marathon PR by 10 minutes
2:56:06. Second marathon in the books and new 10-min PR!
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Sub 3 king
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opinionated + wip thoughts on the attention residuals paper from Kimi
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