arijo
2.1K posts
@arijo
Feeling Buggy | Founder
Doadores dos partidos e campanhas passam a ser secretos #Echobox=1776218553" target="_blank" rel="nofollow noopener">cnnportugal.iol.pt/corrupcao/doad…
We recently published the first-ever expert consensus paper on ketogenic dietary therapy for serious mental illness. Whether you’re a fellow clinician seeking guidance about how to safely incorporate ketogenic therapies into mental health care or someone who wants to try a ketogenic diet to improve your own mental health, this concise, peer-reviewed, open-access resource is free to download and refer to as you explore the powerful potential of a metabolically-minded approach. Hope is on the menu! @IainCampbellPhD @KetoCounselor @ShebaniMD @ChrisPalmerMD @BethZupec @loricalabresemd
I built CourtWatch.us — a free public database for American citizens who deserve safer communities. You can track which judges released defendants who then got rearrested, skipped court, or violated their release conditions. All public records. All free. I started with Orange County FL and will be expanding to all 67 Florida counties and eventually every state in the country. This first batch of info is from 2024 and since public reports are released in March/April for the previous year, data is behind. But I wanted to see if this is plausible. After adding 2024,I'll add 2025 and then figure out how to get real-time-data uploaded. It's in beta — would love to know what you think 👇 Numbers don't lie, but criminals do. courtwatch.us @bennyjohnson @jockowillink @GrantCardone @LauraLoomer @nickshirleyy @j_fishback
Demis Hassabis: If you know the structure of a protein, the real question becomes—where will your drug bind, and what will it actually do? That’s where the next wave of AI comes in. Not just predicting structures, but modeling interactions, outcomes, and real biological impact. At Isomorphic Labs, this is already happening—with 17 active drug programs and partnerships with giants like Eli Lilly and Novartis. The goal? Scale that to 100. This is a fundamental shift in how medicine gets built. Instead of slow, expensive trial-and-error in wet labs, AI allows researchers to run thousands of hypotheses in silico—hundreds to thousands of times more efficiently. The wet lab becomes validation, not exploration. Drug discovery is turning into a computational problem. Faster cycles, smarter predictions, and potentially massive breakthroughs in human health.
Introducing PerturbAI. Today we announced our emergence from stealth with the release of the world’s largest in vivo CRISPR data engine, interrogating the effects of thousands of genetic perturbations across 8 million cells throughout the whole brain. This dataset represents a new category of biological data: organism-level, circuit-resolved causal genomics leading to novel targets and therapeutics. By combining scalable in vivo CRISPR perturbation with AI, we model biological systems at unprecedented resolution and simulate therapeutic interventions before committing to expensive downstream development. We’re grateful to our collaborators at @NVIDIAHealth and @10xGenomics for helping make this landmark dataset possible. Read More: perturb.ai/news #CRISPR #AI #DrugDiscovery #FunctionalGenomics #Biotech
Introducing 𝑨𝒕𝒕𝒆𝒏𝒕𝒊𝒐𝒏 𝑹𝒆𝒔𝒊𝒅𝒖𝒂𝒍𝒔: Rethinking depth-wise aggregation. Residual connections have long relied on fixed, uniform accumulation. Inspired by the duality of time and depth, we introduce Attention Residuals, replacing standard depth-wise recurrence with learned, input-dependent attention over preceding layers. 🔹 Enables networks to selectively retrieve past representations, naturally mitigating dilution and hidden-state growth. 🔹 Introduces Block AttnRes, partitioning layers into compressed blocks to make cross-layer attention practical at scale. 🔹 Serves as an efficient drop-in replacement, demonstrating a 1.25x compute advantage with negligible (<2%) inference latency overhead. 🔹 Validated on the Kimi Linear architecture (48B total, 3B activated parameters), delivering consistent downstream performance gains. 🔗Full report: github.com/MoonshotAI/Att…
NEW: 🇩🇪🇨🇳 German Chancellor Merz says Germans need to work more in order to match China: “We are simply no longer productive enough. Each individual may say, “I already do quite a lot.” And that may be true. But when you return from China, ladies and gentlemen, you see things more clearly. With work-life balance and a four-day week, long-term prosperity in our country cannot be maintained. We will simply have to do a bit more.”
This article @vsmason references is a waste of print space, reading time and intellectual effort. It starts with the ridiculous assumption that cost to orbit on a Falcon 9 is $3,600 per ton (hint: it's SpaceX's selling price!), and proceeds down the hopeless rabbit hole with continuing - and increasing - errors. If you want to get a rigorous "explainer on this issue" I recommend you follow and read posts by @aaronburnett on this subject. Best independent analysis on the economics orbital AI.
