Researcher studying clouds, weather, and wildfires with machine learning and physics

new york city
Joined March 2013
I contend that we have achieved ASI already. What are arguments to the contrary?
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Trying to work out a case for why Anthropic shouldn't go public. Even as a user with no special insight into their ops, there appears to be a path to transformational science with agentic tools and even potentially an "AGI"-equivalent technology.
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However, public markets would be a distraction. Anthropic might need ~10x resources for training and research to reach that breakthrough stage, still the asymmetric upside should more than justify any extra cash injection. Perhaps the US govt could carry the rest of the rounds.
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The following still appears to hold true: A constitutive property of intelligence is the ability of a multi-agent system to create a new Millenium Prize problem they themselves cannot solve.
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There's much to like in this report whitehouse.gov/science/, however I'd like to highlight a major cognitive bias that could hamstring the AI economy. For instance, while the excerpt below from Chapter IV correctly identifies that scaling up inventions is a critical step in 1/4
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decades are any evidence, it's the weakening of local governments and tax bases and excessive centralization of federal-level planning that contributed to off-shoring and all other ills that the report laments. The solution, then, is to reverse that process by co-locating 3/4
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education, research, and industrial capacity across US cities and states. Such a path will ensure that various local governments are able to retain influence over the AI infrastructure build out as well as identify ways in which AI of the future will empower their economies. 4/4
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Jatan Buch retweeted
1/ For nearly 350 years, science has communicated itself through one object: the paper. A linear narrative, frozen as a PDF, written for a human reader. We've come to treat that format as the medium of science itself. It doesn't have to be. It's a historical artifact. 🧵
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Jatan Buch retweeted
The potential for catastrophic effects from the AI boom demands robust deliberation and real democratic governance. Localized initiatives like data center moratoria won't get us there. jacobin.com/2026/04/ai-data-…
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We are actively reviewing applications for a Performance Engineer role at Aeolus expensive-legume-bf0.notion.… I'll be at NeurIPS later in the week, so DM me if you're interested in chatting more about the role or our approach to modern differentiable modeling more broadly!
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Clearing out my old office and finding transparencies from my talks from 25 years ago...
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Jatan Buch retweeted
🚀 I am hiring a Founding Engineer for Inkboard Inc. 🚀👀 I’m confident there is no other role on the market like this - and for the right person, I believe this could be a career defining opportunity. General Requirements: - Good vibes. 😁 - You're a prolific generalist engineer who hates being confined to just code. - You’re rarely blocked: you learn new skills on the fly to get the job done. - Have worked/Are looking to work on atoms and bits rather than just the latter. - Our customers (and we) love nerdy/quirky/joyful things - if you do as well please mention it when you reach out. - (Bonus) You’ve built products people love. More info in the linked tweet below!
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Recently published! Simulating the air quality impact of prescribed fires using graph neural network-based PM2.5 forecasts 👉 bit.ly/3CFlejg By Kyleen Liao, @JBuch7, @karadlamb and @PierreGentine #airquality #wildfires #forecasting
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Usually a good read, Ben Recht absolutely wrote a sophomore-level philosophy analysis of the Higgs discovery, and I’m glad Kyle (who was on the CMS team) corrected the record here!
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recht’s post might qualify for the “not even wrong” distinction, the more I think about it
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I've thought of this as one of the stronger consistency tests for AI NWP models -- glad there's a detailed study out now!
Can #AI-based weather forecasting models (trained on present-day data) provide skillful forecasts also in different colder and warmer states of the climate system? Our new preprint @arxiv explores this question: doi.org/10.48550/arXiv.2409.… Here is what we found so far (🧵1/6)
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Are there any examples of differentiable modeling being applied to ecological systems, or discrete-state systems, more broadly?
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