Data For Science

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[Data For Science @data4sci]

Our latest Substack post is now live

Graph Neural Networks 101

Come learn the the basics of how GNNs work under the hood, with a fascinating new dataset

https://t.co/lE2ZDNdjlU

[Data For Science @data4sci]

[2606.05080] AutoLab: Can Frontier Models Solve Long-Horizon Auto Research and Engineering Tasks? — A useful look at whether today’s frontier models can handle genuinely long-horizon research and engineering workflows, not just short tasks.… https://t.co/YspzgroKem

[Data For Science @data4sci]

Mathematicians issue warning as AI rapidly gains ground — Worth a read; the useful bits are usually in the examples and edge cases. https://t.co/Z6C1MwLeMA

[Data For Science @data4sci]

Expanding Project Glasswing \ Anthropic — Anthropic is expanding Project Glasswing to about 150 additional organizations across 15+ countries. Useful context on how they’re scaling deployment and partnerships beyond the… https://t.co/aD8RgmbNHM

[Data For Science @data4sci]

The Speed of Prototyping in the Age of AI — A practical take on how AI is compressing the prototype-to-ship cycle, without pretending it replaces craft. Useful if you’re figuring out where to lean on tools and where… https://t.co/mpJyvWALVu

[Data For Science @data4sci]

Stanford CS336 | Language Modeling from Scratch — Solid one-stop hub for Stanford’s CS336—useful if you want a structured path through modern language modeling, with the schedule and assignments laid out clearly for self-study or reference. https://t.co/rVPPGwQWwF

[Data For Science @data4sci]

Corporate America Is Starting to Ration AI as Cost Skyrockets — Worth a read; the useful bits are usually in the examples and edge cases. https://t.co/lD6vvVYq0R

[Data For Science @data4sci]

Social interactions in isolated, confined, and extreme environments: A study of Antarctic winter teams using wearable sensors — Worth a read; the useful bits are usually in the examples and edge cases. https://t.co/UfZCZyw1pB

[Data For Science @data4sci]

Why I Made a Journal for AI-Generated Papers — Cesar A. Hidalgo — A thoughtful take on how AI-generated papers could force a redesign of research institutions, not just research workflows. Worth… https://t.co/uwr2vcHc37

[Data For Science @data4sci]

[2605.22763v1] Advancing Mathematics Research with AI-Driven Formal Proof Search — A clear overview of how AI-guided formal proof search can support real math research, not just toy benchmarks. Useful if you’re tracking where automated… https://t.co/dpJCcW4JzR

[Data For Science @data4sci]

The Science of Unpredictability | Los Alamos National Laboratory — A clear, accessible look at how the FPUT problem helped spark chaos theory and modern nonlinear dynamics. Useful context for anyone working… https://t.co/aaSWSruI9e

[Data For Science @data4sci]

After Automation | Every — A useful counterpoint to the “AI will eliminate work” narrative: as automation improves, it often shifts effort into new human tasks rather than removing it. Worth reading if you’re thinking about how roles and… https://t.co/fmu6A4ku94

[Data For Science @data4sci]

[2605.06394] Lecture Notes on Statistical Physics and Neural Networks — Clear lecture-style notes connecting statistical physics tools to neural network theory—useful as a structured refresher if you want the big ideas and standard derivations… https://t.co/7OQ9k6yi7g

[Data For Science @data4sci]

[2605.06394] Lecture Notes on Statistical Physics and Neural Networks — Clear lecture-style notes connecting statistical physics tools to neural network theory—useful as a structured refresher if you want the big ideas and standard derivations… https://t.co/7OQ9k6yi7g

[Data For Science @data4sci]

[2605.12460] Multi-Stream LLMs: Unblocking Language Models with Parallel Streams of Thoughts, Inputs and Outputs — Interesting take on making LLMs less sequential by running parallel streams for reasoning, inputs, and outputs. Worth a skim if… https://t.co/RZYpUmrOEU

[Data For Science @data4sci]

Sycophantic AI decreases prosocial intentions and promotes dependence — Worth a read; the useful bits are usually in the examples and edge cases. https://t.co/NaeXvSeNKe

[Data For Science @data4sci]

Global approaches to infectious disease surveillance and modeling | Nature Medicine — Clear overview of why infectious disease surveillance is getting harder—and how federated analytics could unlock cross-border modeling… https://t.co/tVAZcu6yHy

[Data For Science @data4sci]

Persuading large language models to comply with objectionable requests — Worth a read; the useful bits are usually in the examples and edge cases. https://t.co/oTWIeRFFrT

[Andrej Karpathy @karpathy]

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

[Data For Science @data4sci]

[2604.09839] Steered LLM Activations are Non-Surjective — Useful if you’re thinking about activation steering as a general-purpose control knob: this paper argues the mapping from steering directions to reachable behaviors isn’t onto, so some… https://t.co/31UxzxTf4a

[Data For Science @data4sci]

Project Glasswing: what Mythos showed us — A clear-eyed look at what happened when security-focused LLMs were aimed at real production code—what they caught, what they missed, and what needs to change before this approach can… https://t.co/CcPEQpBQzK