Meat might be too differentiated already. Mike Levin's immortal planaria are more blobby
RESEARCH
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OpenClaw Revolution Continues with Nous Research and Hermes
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The revolution that @openclaw started continues. Learn about @NousResearch and its Hermes competitor. Starts at 4 p.m. Pacific Time (in about 20 minutes). nitter.net/i/spaces/1DGleEpaXLrJL
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Meta’s New Model Criticized for Benchmark Optimization Over Real Utility
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The new model from Meta is already looking like a disappointment: overoptimized for public benchmark numbers at the detriment of everything else. Knowing how to evaluate models in a way that correlates with actual usefulness is a core competency for AI labs, and any new lab is unlikely to be successful without first figuring that out.
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Dietary Intervention With AI Models for Pediatric Brain Cancer Treatment
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Can rebooting the diet, eliminating 2 essential amino acids, help treat an aggressive brain cancer in children?
mechanism and potential established from experimental model https://
nejm.org/doi/full/10.10
56/NEJMcibr2516825
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Building Benchmark Factory to Combat Model Overfitting
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As models overfit to benchmarks, @alexgshaw of @LaudeInstitute is thinking about the problem this way: “how can we build the benchmark factory – the machine that other people can use to make their benchmarks – as opposed to just creating our own benchmarks one-by-one?”
— Snorkel AI (@SnorkelAI) 8 avril 2026
Enter… pic.twitter.com/3lre0GRO3GAs models overfit to benchmarks, @alexgshaw of @LaudeInstitute is thinking about the problem this way: “how can we build the benchmark factory – the machine that other people can use to make their benchmarks – as opposed to just creating our own benchmarks one-by-one?” Enter
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A2RLeague Racing Robots Exceed Human Performance Capabilities
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He should support @A2RLeague They have many innovators involved. I saw them race a Formula 2 robot faster than the human could go for the first time last year.
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Human Disagreement on AGI Alignment Remains Fundamental Challenge
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It’s not. But the assumption that humans will agree on AGI alignment before building AGI is inherently flawed. A brief study of human history (or indeed a study AI history) should make that clear.
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Hermes Discussion with Nous Research CTO
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Bummer, am talking about Hermes with the CTO of @NousResearch then. Will join after if you are till running.
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DISCO: AI-Designed Enzyme Engineering via Diffusion Co-design
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Going from a beautiful idea to successful wet lab experiments is the dream cycle of every scientist.
— Kirill Neklyudov (@k_neklyudov) 8 avril 2026
This is exactly what DISCO does but at insane, inhuman scale. Given numerous chemical constraints including binding targets and off-targets, it generates proposals for wet-lab… https://t.co/c7TbU3xUhpGoing from a beautiful idea to successful wet lab experiments is the dream cycle of every scientist. This is exactly what DISCO does but at insane, inhuman scale. Given numerous chemical constraints including binding targets and off-targets, it generates proposals for wet-lab testing at unprecedented throughput. For @martoskreto, @AlexanderTong7, and me, it also means bringing Feynman-Kac Correctors from idea stage to a successful practical technique! Jarrid Rector-Brooks (@jarridrb) What if AI could invent enzymes that nature hasn’t seen? 👩🔬🧑🔬 Introducing 🪩 DISCO: Diffusion for Sequence-structure CO-design 14 rounds of directed evolution and over a year of wet lab work. That's what it took to engineer an enzyme for selective C(sp³)–H insertion, one of the most challenging transformations in organic chemistry. DISCO surpasses this with a single plate. No pre-specified catalytic residues, no template, no theozyme, no inverse folding, just joint diffusion over protein sequence and structure. 📝 Blog: disco-design.github.io/ 📄 Paper: arxiv.org/abs/2604.05181 💻 Code: github.com/DISCO-design/DISC… — https://nitter.net/jarridrb/status/2041893841301860542#m
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Domino enables reproducible AI workflows for bioengineering collaboration
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In this demo, we show how Domino enables cross-lab collaboration, reproducible AI workflows, and end-to-end experiment tracking to accelerate bioengineering at scale. Watch to see how leading research teams are building biology on demand: https://
hubs.ly/Q04b41SG0