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  • Auto-Research for Data: The Underrated ML Game Changer

    By

    @thom_wolf

    –

    Auto-research for ML training models is all the rage now, but underrated is: auto-research for data! Sure, you can squeeze out a bit of model performance by optimizing hyperparameters, but code agents can do data work that has been very labour intensive and required a lot of attention to a lot details effortlessly: > download data from many different data sources > bring all the data sources into uniform format > do detailed EDA: find patterns and outliers > look at 100s of samples and take detailed notes > make beautiful infographics rather than mpl plots > iterate on data filtering by looking at more samples > make a simple pipelines robust and scalable It's now possible to write data pipelines for dozens of data sources in hours that would have taken weeks of reading many docs, debugging APIs and data formats, wrangling outliers and missing data. A few weeks ago we gave Claude access to the CPU partition of our cluster and it iteratively refined filters to retrieve a domain subset of FineWeb. This would have taken me 2-3 days to work through while it took Claude just a few hours with almost no babysitting and with a nice logbook. Thus the long tail of small, niche data sources becomes more accessible and can be aggregated to even larger high quality datasets for cool applications. Data has been fuelling LLM progress more than model architecture innovations, so I am very excited about this!

    → View original post on X — @thom_wolf, 2026-03-24 17:04 UTC

  • OpenAI Foundation Update and News Details

    By

    @sama

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    More details here: openaifoundation.org/news/up…

    → View original post on X — @sama

  • OpenAI Foundation launches with $1 billion commitment to AI safety

    By

    @sama

    –

    AI will help discover new science, such as cures for diseases, which is perhaps the most important way to increase quality of life long-term. AI will also present new threats to society that we have to address. No company can sufficiently mitigate these on their own; we will need a society-wide response to things like novel bio threats, a massive and fast change to the economy, extremely capable models causing complex emergent effects across society, and more. These are the areas the OpenAI Foundation will initially focus on, and in my opinion are some of the most important ones for us to get right. The Foundation will spend at least $1 billion over the next year. @woj_zaremba, co-founder of OpenAI, will transition to Head of AI Resilience. I believe that shifting how the world thinks about safety to include a Resilience-style approach is critical, and I am extremely grateful to Wojciech for taking on this role. Wojciech has been my cofounder for the last decade; anyone who knows him will understand what I mean when I say he is one of a kind. He has a lot of ideas about how we build a new kind of AI safety. @JacobTref is joining as Head of Life Sciences and Curing Diseases. @annaadeola, our VP of Global Impact, will transition to Head of AI for Civil Society and Philanthropy. @robert_kaiden is joining as Chief Financial Officer. @jeffarnold is joining as Director of Operations.

    → View original post on X — @sama

  • Why There Is No AlphaFold for Materials Science

    By

    @latentspacepod

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    Why There Is No "AlphaFold for Materials" https://
    latent.space/p/materials Materials Science is a force for good everywhere in our lives, from your clothes to the computers you use. We catch up on AI for Materials Discovery with Prof. Heather Kulik of @KulikGroup
    , one of the first

    → View original post on X — @latentspacepod

  • LiteLLM Supply Chain Attack: Bug Saved Developers from Credential Theft
    LiteLLM Supply Chain Attack: Bug Saved Developers from Credential Theft

    By

    @mjasay

    –

    When vibe coding is an unalloyed good: your hacker vibe coded their way to a bug that limited the efficacy of their attack. 😅😮‍💨 (But still very serious.) Andrej Karpathy (@karpathy) Software horror: litellm PyPI supply chain attack. Simple `pip install litellm` was enough to exfiltrate SSH keys, AWS/GCP/Azure creds, Kubernetes configs, git credentials, env vars (all your API keys), shell history, crypto wallets, SSL private keys, CI/CD secrets, database passwords. LiteLLM itself has 97 million downloads per month which is already terrible, but much worse, the contagion spreads to any project that depends on litellm. For example, if you did `pip install dspy` (which depended on litellm>=1.64.0), you'd also be pwnd. Same for any other large project that depended on litellm. Afaict the poisoned version was up for only less than ~1 hour. The attack had a bug which led to its discovery – Callum McMahon was using an MCP plugin inside Cursor that pulled in litellm as a transitive dependency. When litellm 1.82.8 installed, their machine ran out of RAM and crashed. So if the attacker didn't vibe code this attack it could have been undetected for many days or weeks. Supply chain attacks like this are basically the scariest thing imaginable in modern software. Every time you install any depedency you could be pulling in a poisoned package anywhere deep inside its entire depedency tree. This is especially risky with large projects that might have lots and lots of dependencies. The credentials that do get stolen in each attack can then be used to take over more accounts and compromise more packages. Classical software engineering would have you believe that dependencies are good (we're building pyramids from bricks), but imo this has to be re-evaluated, and it's why I've been so growingly averse to them, preferring to use LLMs to "yoink" functionality when it's simple enough and possible. — https://nitter.net/karpathy/status/2036487306585268612#m

    → View original post on X — @mjasay, 2026-03-24 17:00 UTC

  • Perplexity Computer transforms investment research and analysis workflow
    Perplexity Computer transforms investment research and analysis workflow

    By

    @aravsrinivas

    –

    I never found a way to adopt the old version of Perplexity in my investment process, but the things you can one-shot in Perplexity Computer are mind bogglingly good, and it has become a daily driver for me (for the avoidance of doubt, this is not a sponsored post). For example, I always created a guidance credibility analysis, which is a 10-year study of company guidance behavior vs. ultimate results in subsectors: which companies consistently beat/missed/held? These trends can be strong initial indicators of business momentum shifts (i.e. a beat and raise story who just held guidance in Q3 for the first time in 5 years has some information). And you see patterns here that cause you to skeptically question guidance (high or low). Perplexity Computer can one shot this with a 9-page report. Validation is critical, so I may have a different Perplexity Computer space or a Claude CoWork session go and systematically validate, then spot check & validate any key events by hand. But the ability to spin this up quickly, at scale is but one of many emerging capabilities that has me very excited about the very recent agentic capabilities. Computer (@AskPerplexity) We're hosting a Perplexity Computer stock pitch competition starting on March 30th for students enrolled in a US undergraduate or graduate program. Students will have 1 week to research, analyze, and pitch a publicly-listed stock, using only Perplexity Computer. — https://nitter.net/AskPerplexity/status/2036470683308544495#m

    → View original post on X — @aravsrinivas, 2026-03-24 16:58 UTC

  • Microsoft and NVIDIA Partner to Transform Nuclear Energy with AI
    Microsoft and NVIDIA Partner to Transform Nuclear Energy with AI

    By

    @kimmonismus

    –

    Microsoft and NVIDIA are teaming up to revolutionize nuclear energy with AI-driven tools that streamline permitting, design, and operations, cutting timelines and costs dramatically. Even before computing, energy will be the biggest bottleneck, and everyone is aware of that by

    → View original post on X — @kimmonismus

  • SIMA 2: Next-Generation AI Agent for Virtual 3D Worlds

    By

    @ronald_vanloon

    –

    SIMA 2: Next-Gen #AIAgent Built to Navigate Virtual #3D Worlds
    by @GoogleDeepMind #ArtificialIntelligence #MachineLearning #ML #Technology

    → View original post on X — @ronald_vanloon

  • Security vs Speed: Oracle’s AI Advantage for Enterprise Needs

    By

    @mjasay

    –

    Both care about security, but for the hedge fund, speed trumps many other considerations. For the bank, speed is always second to data security, customer privacy, etc. This is where a company like Oracle will win: the AI a dev wants with the safety/security their company requires

    → View original post on X — @mjasay, 2026-03-24 16:57 UTC

  • AI Adoption Divergence Between Financial Institutions

    By

    @mjasay

    –

    Was lucky to discuss AI adoption today with two technical leaders: one at a large hedge fund and the other a major retail bank. The bank lags the hedge fund, which isn't surprising. Different risk profile. What *was* surprising? How *wildly* divergent their AI adoption is.

    → View original post on X — @mjasay, 2026-03-24 16:57 UTC