Image created with gemini-3.1-flash-image-preview with claude-opus-4.7. Image prompt: Using the provided reference images, keep the authentic Sonoran Desert trail setting, lighting, and weathered ranger-station sign style, but render the sign header as bold ‘SCIENCE’ with trail entries like ‘Hypothesis Ridge → 1.2’, ‘Peer Review Loop → 3.4’, ‘Replication Saddle → 0.8’ and a small magnifying-glass emblem in place of the medallion; on a volcanic boulder beside the post place an open field notebook with pencil botanical sketches and a small brass hand lens, saguaro and palo verde behind, photorealistic midday desert light.
China approves brain chip to overcome paralysis | Nature Biotechnology
https://www.nature.com/articles/s41587-026-03101-8
Perplexity and Computer now allow you to run Deep and Wide Research on sources trusted by doctors and medical professionals like the New England Journal of Medicine, the British Medical Journal, the American Diabetes Association, and so on.
https://x.com/AravSrinivas/status/2051711236224761983
Perplexity and Computer now connect to premium health sources, starting with NEJM and BMJ Group, with 9 more medical journals and clinical databases on the way. Ask health questions and get answers cited from the same sources relied on by hospitals and research institutions.
https://x.com/perplexity_ai/status/2051710342242480538
Medicine | The 2026 AI Index Report | Stanford HAI
https://hai.stanford.edu/ai-index/2026-ai-index-report/medicine
📣 We’re continuing to bring more value to our AI Pro and Ultra subscribers! Google Health Coach is unlocked by Google Health Premium, which is going to be included at no extra cost in our Google AI Pro and Ultra plans starting on May 26. I’ve been dogfooding the Fitbit Air and
https://x.com/shimritby/status/2052439569136767291
Get up close and personal with your health. On May 26, the Fitbit app becomes the #GoogleHealth app for both Android and iOS– combining the best of Fitbit tracking with the power of Google to create a more holistic wellness experience. Learn more:
https://x.com/googlehealth/status/2052392762255761701
Introducing Fitbit Air. It’s lightweight, screenless and comfortable enough to wear 24/7 — with a battery life* of up to a week. * Battery life depends upon many factors and usage and actual battery life may be lower.
https://x.com/Google/status/2052501704155775481
Introducing the Google Health app
https://blog.google/products-and-platforms/products/google-health/google-health-app/
New paper (on an old AI) tests o1 against doctors on medical benchmarks & real ER cases: “across a variety of scenarios and applications, the large language model outperformed both human physicians and older models” The potential suggests an “urgent need for prospective trials.”
https://x.com/emollick/status/2050197369250033813
1/ Holy: Astronomers just pointed an AI at NASA data from 2.2 million stars. It found over 100 hidden planets, including worlds so extreme they shouldn’t even exist according to current theory. I love it. Lets break it down and explain what it means 🧵:
https://x.com/kimmonismus/status/2051305620914233400
One of the coolest stories I heard from David Reich about the interaction between genetics and human culture: The caste system was powerful enough to essentially ‘freeze’ Indian genetics for thousands of years, almost completely stopping the process of genetic mixture.
https://x.com/dwarkesh_sp/status/2051421803692908600
Symbiotic brain-machine drawing via visual brain-computer interfaces | npj Biomedical Innovations
https://www.nature.com/articles/s44385-026-00086-6
The MIT-IBM Computing Research Lab launches to shape the future of AI and quantum computing | MIT News | Massachusetts Institute of Technology
https://news.mit.edu/2026/mit-ibm-computing-research-lab-launches-0429
yes it will change… in the future people will prefer to interact with AI via brain-computer interfaces
https://x.com/iScienceLuvr/status/2052465922640593068
@_philschmid The common way is to use datasets with triplets of context/question/answer and concatenate multiple contexts to create long contexts LOFT is a example of dataset like that
https://x.com/gabriberton/status/2051050627942568319
Accelerating and automating science and research is one of the noblest pursuits right now. We need to jointly train not just single meaning units like word vectors, not just embed all sentences, not only train one model to be prompted by any question, but ideally the entire
https://x.com/RichardSocher/status/2051121805482676323
AI Decoder Could Cut Quantum Errors by Up to 17×, Study Finds
AI Decoder Could Cut Quantum Errors by Up to 17×, Study Finds
AI inference just plays by different rules
https://www.theregister.com/software/2026/05/04/ai-inference-just-plays-by-different-rules/5223647
AI Outperforms Doctors in Emergency Room Tasks, New Harvard Study Shows | Harvard Magazine
https://www.harvardmagazine.com/ai/ai-outperforms-doctors-diagnosis-harvard-study
AI training faces a very different set of trade-offs compared to human evolution. Because you can directly copy a trained model basically for free, it makes sense to amortize in the pre-trained weights the learning that humans spread across a lifetime.
https://x.com/dwarkesh_sp/status/2050697033632330047
Computer science basically got started in the 1930s when Turing and Church just laid down what the theory of everything was. They just said, here’s how computation works. And then we’ve spent 90 years since then just exploring consequences of that and gradually building up more
https://x.com/dwarkesh_sp/status/2049941366348890169
DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training Overview: DORA is an asynchronous RL training system designed to remove the rollout bottleneck in LLM post-training. The key issue is skewed generation, where a few extremely long reasoning
https://x.com/TheAITimeline/status/2051401348726317146
How To Scale Your Model
https://jax-ml.github.io/scaling-book/
How well does this work? One quick independent test is to see if it can recover an “”internal CoT”” in cases where AIs can solve math problems in a single forward pass. TLDR: it doesn’t. (TBC, this might require the NLA to see activations at multiple positions/location to work.)
https://x.com/RyanPGreenblatt/status/2052458229624672549
Humans are systematically undertrained. Given the computing power of the human brain, optimal training would require seeing orders of magnitude more data during childhood – maybe millions of years’ worth. Obviously we’d die long before this. Massive undertraining is necessary
https://x.com/dwarkesh_sp/status/2049972212942401698
Import AI 455: AI systems are about to start building themselves.
https://importai.substack.com/p/import-ai-455-automating-ai-research
Import AI 455: Automating AI Research | Import AI
Neural networks might speak English, but they think in shapes. Understanding their rich *neural geometry* is key to understanding how they work – and to debugging and controlling them with precision. Starting today, we’re releasing a series of posts on this research agenda. 🧵
https://x.com/GoodfireAI/status/2052420446910644616
Note Clark’s definition of RSI here, from his newsletter, is “a frontier model is able to autonomously train a successor version of itself.” This is a weaker claim than what I assumed he meant, which was that human researchers would no longer be useful vs. AI ones.
https://x.com/goodside/status/2051388803047158175
separating infra and science for long context doesn’t make sense, most long context science is about making computation and memory (capacity and bandwidth) feasible at scale. today’s infra wouldn’t support MHA on a 1T model at 1M context
https://x.com/eliebakouch/status/2051374295620665713
Some shilling, but I really mean it: Yesterday I had a mathematical disagreement with Alex @__kolesnikov__ and we bet a beer. After going back and forth on pen and paper, we resolved where the disagreement was. (As always, he was more right than me. I concede 2/3 of the beer
https://x.com/giffmana/status/2051925008457273527
Surprisingly little effect from a well-designed study.
https://x.com/emollick/status/2051438513476747759
the lock-in isn’t the harness — it’s the context pipeline feeding it. whoever owns how repo state gets pulled, ranked, and compressed into the attention window owns the developer, regardless of model or framework choice
https://x.com/AnthonyMaio/status/2050976650943213964
This is a very interesting paper It argues that a real scientific theory of deep learning is starting to form. Researchers call it “”learning mechanics.”” It’s like physics, but for how neural networks learn. Now there are 5 active research areas that together look like pieces of
https://x.com/TheTuringPost/status/2050007859115733078
To really understand embeddings, you need a few core ideas: – vectors and dimensions – dense vs sparse representations – vector and embedding spaces – what latent space means – semantic similarity importance – and how embeddings are formed These concepts completely change and
https://x.com/TheTuringPost/status/2051255782197637393
vLLM Real-World Lab Report
https://avkcode.github.io/blog/how-vllm-works.html
We need more work on AI inequality, but this study is not about GenAI, the survey was fielded in 2022. “In this study, we selected items from Wave 119 (N = 10,087), which were collected from December 12 to December 18, 2022.”
https://x.com/emollick/status/2050231392374501701
We use previous generations of Composer to train future ones. Our autoinstall system has earlier Composer models set up dev environments for RL training. That way, the next generation can focus on learning to solve harder problems.
https://x.com/cursor_ai/status/2052116064474161556
Webinar | Beyond the Model: A Practitioner’s Guide to Harness Engineering
https://pages.temporal.io/webinar-grid-dynamics-harness-engineering.html
Why @michael_nielsen disagrees with the view that science will keep getting harder and harder as low-hanging fruit is picked:
https://x.com/dwarkesh_sp/status/2049640034878550031
Folding the TP and SP parallelism schemes onto a single axis enables us to shard both the weight tensors and the activation tensors along the same GPUs. This changes the communication volume scaling (see paper). This volume is across fewer GPUs, so we have more flexibility to
https://x.com/QuentinAnthon15/status/2051362275483963709
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