Good morning. @kareem_carr says us AI boosters aren't believable. Well, it's good enough to build this: https://
alignednews.com/ai, thanks @blevlabs
. And it is good enough to drive our car. Thanks @Tesla
. And good enough to clean my floors, thanks @maticrobots
. And good enough
AI
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China’s Advanced Electric Rails and US Potential for Innovation
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Concerns Over Unregulated AI Technology Deployed to Children
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How have we got to the point where we are rolling out untested/unregulated AI technology to kids while they are literally in the process of learning?!
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Official Blueprint for Building Skills for Claude Released Free
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read the official blueprint for Claude skills for free here: → https://
resources.anthropic.com/hubfs/The-Comp
lete-Guide-to-Building-Skill-for-Claude.pdf
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Stanford Lecture Offers Deep Dive into LLM Architecture
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Cette conférence de 2 heures à Stanford t’apprendra davantage sur la manière dont les LLM comme ChatGPT et Claude sont construits que ce que la plupart des personnes travaillant dans les meilleures entreprises d’IA apprennent durant toute leur carrière.
— Jouhatsu | AI Influence Operator (@Jouhatsu_ai) 4 mai 2026
Ajoute-la à tes Signet🔖… pic.twitter.com/JOVAKrBsNSCette conférence de 2 heures à Stanford t’apprendra davantage sur la manière dont les LLM comme ChatGPT et Claude sont construits que ce que la plupart des personnes travaillant dans les meilleures entreprises d’IA apprennent durant toute leur carrière. Ajoute-la à tes Signet
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Boston Dynamics Spot Uses AI for Whole-Body Tire Manipulation
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Boston Dynamics’ Spot Masters Whole-Body Manipulation — Using AI to Drag, Roll, and Stack 15 kg Tires with Precision
— Ronald van Loon (@Ronald_vanLoon) 4 mai 2026
by @rai_inst#Robotics #Engineering #ArtificialIntelligence #Innovation #Technology pic.twitter.com/nQf4l1xOGSBoston Dynamics’ Spot Masters Whole-Body Manipulation — Using AI to Drag, Roll, and Stack 15 kg Tires with Precision
by @rai_inst #Robotics #Engineering #ArtificialIntelligence #Innovation #Technology -
Anthropic Releases Official 33-Page Claude Skills Playbook
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WE JUST GOT THE ULTIMATE PLAYBOOK FROM ANTHROPIC 🤯
— Charly Wargnier (@DataChaz) 4 mai 2026
their massive 33-page official guide on Claude Skills is the only guide you need.
make sure to bookmark it.
link below in the 🧵↓ https://t.co/dH8Mpu6aam pic.twitter.com/mSXw8vHdj6WE JUST GOT THE ULTIMATE PLAYBOOK FROM ANTHROPIC their massive 33-page official guide on Claude Skills is the only guide you need. make sure to bookmark it. link below in the ↓
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Investor Backs Cofounder AI Agent as Standout Agentic Product
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since babyagi, i've seen hundreds of agentic products and pitches
— Yohei (@yoheinakajima) 4 mai 2026
there are only a few i immediately loved, and only one that i invested in past my usual entry stage
that was cofounder 1 from @intelligenceco , and it was hard to believe 4 people had built that entire thing in a… https://t.co/PTPxOs5eh5since babyagi, i've seen hundreds of agentic products and pitches there are only a few i immediately loved, and only one that i invested in past my usual entry stage that was cofounder 1 from @intelligenceco , and it was hard to believe 4 people had built that entire thing in a
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Abacus AI Studio Unifies LLMs and Creative Generation Tools
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Abacus AI Studio is what happens when AI tools stop being separate products and start working like one system. It connects models like GPT-5.5 (thinking) and Opus 4.7 with generation tools like Grok Imagine, Nano Banana Pro, and SeeDance 2.0 – so the entire creative process runs
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Perplexity develops a new Digest feature
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Perplexity is working on a new Digest feature. It seems to be connected to the upcoming Context for Perplexity Computer and potentially will be able to pull recent context from connected sources into a personal aggregated summary.
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GenLIP Trains ViT to Directly Predict Caption Tokens
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"Let ViT Speak: Generative Language-Image Pre-training" Instead of contrastive image-text matching or adding a separate text decoder, this paper, GenLIP, trains a ViT to directly predict caption tokens from image patches with a standard next-token loss. A key component they use