Image created with Gemini. Image prompt: Hand-painted Studio Ghibli style scene of a hillside seaside observatory terrace at golden hour, a scientist in a linen coat examining a small porcelain smiling mask under a brass microscope while its magnified reflection on a glass plate reveals glowing circuitry and helix patterns beneath the grin, a hand-painted wooden sign above the door reading ‘Science’ in bold clean letters, soft gouache watercolor backgrounds with terracotta rooftops and teal sea beyond, cinematic wide square framing, gentle warm light with quiet mystery.
Anthropic launches AI drug discovery program, Claude Science
https://www.cnbc.com/2026/06/30/anthropic-launches-ai-drug-discovery-program-claude-science.html
Claude Science, an AI workbench for scientists \ Anthropic
https://www.anthropic.com/news/claude-science-ai-workbench
Meta’s Watermelon Matches GPT-5.5 Benchmarks | Let’s Data Science
https://letsdatascience.com/news/metas-watermelon-matches-gpt-55-benchmarks-76a9460e
Introducing GeneBench-Pro — testing whether models can handle the kind of judgment-heavy analysis that real-world computational biology requires. Problems would take a human expert around 20-40 hours to complete. GPT-5.6 Sol is a big step forward.”
https://x.com/gdb/status/2072191801122038207
Introducing GeneBench-Pro | OpenAI
https://openai.com/index/introducing-genebench-pro/
From Brain Waves to Words: Brain2Qwerty Offers a New Path to Communication Without Surgery
https://ai.meta.com/blog/brain2qwerty-brain-ai-human-communication/
Meta says Brain2Qwerty v2 can decode natural sentences from non-invasive brain recordings in real time, reaching 61% word accuracy. The system was trained on about 22,000 sentences from 9 volunteers, each recorded for 10 hours with MEG while typing. Meta compares that with 8%”
https://x.com/kimmonismus/status/2071712776226283902
some exciting new work from our AI teams at Meta on non-invasive brain computer interfaces!”
https://x.com/alexandr_wang/status/2071617674946179264
I’m looking for a semi-private hack space for a few days in SF for me and some of the OpenClaw maintainers. We need to cook. DM leads my way 🙏🦞”
https://x.com/steipete/status/2072475858435276840
We’re introducing GeneBench-Pro, a research-level benchmark for a harder kind of AI progress: how well agents can navigate messy biological data, choose the right analysis path, and make judgment calls that real computational research depends on.”
https://x.com/OpenAI/status/2072004836674167294
Got GLM-5.2 running on my Mac Studio via llama.cpp, the reasoning behind all my medical agentic workflows. It orchestrates a swarm of tiny on-device OpenMed experts: oncology, meds, labs. No cloud, no rate limits, nobody can take it away. AI must be owned, not rented.”
https://x.com/MaziyarPanahi/status/2070503452178796704
AI went from predicting biological processes to controlling them, and now it is becoming an active participant in science. Agents’ architectures perfectly fit the scientific loop at the execution level: read literature, write and run code, generate hypotheses, test them,”
https://x.com/TheTuringPost/status/2072130350042534390
Katalyze – Agentic Infrastructure for Life Sciences
https://www.katalyzeai.com/
If you are on the verge of AGI or ASI, why isn’t your model smart enough to recognize espionage distillation in real time? You say “cure cancer in a few years.” Isn’t sniffing illicit distillation quite a bit easier than curing cancer? Why write letters to DC? Just use AGI.”
https://x.com/bgurley/status/2070487575018786899
I’m worried about scheming AIs. But I also worry that, even if we catch them doing something bad, we still won’t realise! Even today LLMs often take sus actions We need a science of model forensics: WHY did the model misbehave? See our paper for what this could look like:”
https://x.com/NeelNanda5/status/2070547032058761654
REST3D: Reconstructing Physically Stable 3D Scenes from a Single Image” TLDR: reconstructs simulation-ready 3D scenes from a single image by combining agentic physical scene understanding with physics-constrained optimization.”
https://x.com/Almorgand/status/2071984726512906605
Google Cloud will sell specialist AI models built for science
https://thenextweb.com/news/google-cloud-science-ai-models-sandboxaq
You don’t need expensive hardware to build something that feels like real robotics. An Arduino, a servo, and an ultrasonic sensor can scan space and turn echoes into a simple radar view. It sweeps, measures distance, and visualizes it in real time. Cheap, simple, and a solid”
https://x.com/IlirAliu_/status/2071502956336222379
Grant Sanderson – AI and the future of math
https://www.dwarkesh.com/p/grant-sanderson-2
The most important weird thing about LLMs is that they are so general. A bigger LLM that is better at coding is also better at ideation & ethical advice & medicine & math. This isn’t true of everything, jaggedness again (see fiction writing!), but it is remarkably true.”
https://x.com/emollick/status/2071771186569306422
After 15 years (4 internships and exactly 8 years full-time), today is my last day at Google. Growing up as a scientist at Brain and DeepMind was an incredible privilege, and I’m so thankful for the people who made it such a special place. I went from editing decision trees by”
https://x.com/poolio/status/2070191754465440138
Everything Lars Moravy, Tesla’s VP of Engineering, said about Optimus in the latest interview on Herbert’s channel: On the transition of Fremont’s Model S/X lines to Optimus: – Space has been cleared out – Our first line has landed (in Fremont) from our automation groups in the”
https://x.com/TheHumanoidHub/status/2072297648246456393
Always so much fun to chat with @3blue1brown AI has been making much faster progress in math than in other fields. As a result, mathematics is showing us, very concretely, what AI progress in other fields will look like. Even within mathematics, there’s a jagged landscape.”
https://x.com/dwarkesh_sp/status/2071994830813532481
To help accelerate neuroscience breakthroughs, we’re releasing the full training code for Brain2Qwerty v1 and v2, and our partner, @bcbl_, is releasing the v1 dataset. Learn more and explore the artifacts here:”
https://x.com/AIatMeta/status/2071566934571954326
We’re sharing the next major milestone in our non-invasive brain-to-text decoder research: Brain2Qwerty v2. Building on v1, which was published today in @Nature, Brain2Qwerty v2 is the highest-performing end-to-end pipeline capable of real-time sentence decoding from raw brain”
https://x.com/AIatMeta/status/2071566924803395741
GitHub – Pengbinghui/pipeline-math · GitHub
https://github.com/Pengbinghui/pipeline-math
GPT-5.6 is a capable model, especially for long-horizon tasks and knowledge work across coding, computer use, and science. I’m grateful to have had the chance to contribute and to “distill” from the amazing teammates who helped make it possible!”
https://x.com/astonzhangAZ/status/2070565079603687559
We’re happy to announce 2 releases today: – 🧠Brain2qwerty v1 is published at @NatureNeuro – 🚀 Brain2Qwerty v2 is now publicly released Explore how we decode sentences from non-invasive brain recordings:
https://t.co/NFhDVMQoeR Links: 📄v1 Nature Neuro:”
https://x.com/JeanRemiKing/status/2071568417522369008
In my experience, all model routers underestimate the difficulty of non-math/coding tasks and assign them too little intelligence. This is worth addressing, as non-verifiable tasks (innovation, marketing, qualitative analysis) often benefit the most from using “smarter” AI models”
https://x.com/emollick/status/2071265352294584824
Plots of empty desert could soon be worth more than the most fertile farmland in human history. @CJHandmer ran through the back-of-the-envelope math. 10 acres of solar is enough for 1 MW of H100s. And the FLOPS done by those H100s is roughly equivalent to 1000 human brains. If”
https://x.com/dwarkesh_sp/status/2070179362750845038
The Ramanujan Challenge for AI | Combinatorics and more
https://gilkalai.wordpress.com/2026/07/02/the-ramanujan-challenge-for-ai/
The way math is presented can be really misleading about the actual nature of math. In theory, someone could have discovered quantum information theory decades before quantum mechanics even existed. It’s just about combining linear algebra with probability. But nobody would”
https://x.com/dwarkesh_sp/status/2070222272594583669
Mathlib is Lean library that has formalized a lot of humanity’s math concepts and proofs. Grant speculated about a really interesting possibility: You could just have different AIs fork MathLib and build their own parallel math civilization. Lean guarantees that whatever new”
https://x.com/dwarkesh_sp/status/2072403064846520346
Nice example of the increasing benefits of open science and transparent methodologies when writing papers about AI.”
https://x.com/emollick/status/2071094858891120796
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