Crazy fact: Anthropic's Head of Growth @TheAmolAvasare suffered a traumatic brain injury (from a kick to the head during a Muay Thai sparring session) a few years ago. He shared his story of recovery in my newsletter in 2023: https://
lennysnewsletter.com/p/how-a-trauma
tic-brain-injury-made
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ETHICS
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Anthropic Head of Growth Shares Traumatic Brain Injury Recovery Story
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OpenAI Chief Scientist discusses continual learning and AI research roadmap
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OpenAI's Chief Scientist, @merettm, on the continual learning wave: frontier labs are already building this into the core of the technology.
— Jacob Effron (@jacobeffron) 9 avril 2026
The entire premise of scaling was to create systems that learn in context. Jakub says continual learning is not some separate missing… https://t.co/jsmSU6cSNH pic.twitter.com/55ovuIy4rLOpenAI's Chief Scientist, @merettm, on the continual learning wave: frontier labs are already building this into the core of the technology. The entire premise of scaling was to create systems that learn in context. Jakub says continual learning is not some separate missing piece, but “exactly what we’re working toward.” Jacob Effron (@jacobeffron) At @OpenAI, Chief Scientist @merettm helps lead the research roadmap to AGI including a research intern-level AI system by September 2026 and a fully automated AI researcher by March 2028. I sat down with Jakub to check on those timelines and ask him all of my top-of-mind AI questions including: ▪️ How OpenAI thinks about extending RL beyond code and math ▪️ The current state of alignment research as more powerful models loom ▪️ The future of continual learning ▪️ How startups should think about building their own models/harnesses And he also shared some great stories around OpenAI’s pioneering work on math. YouTube: piped.video/vK1qEF3a3WM Spotify: bit.ly/4sjUyrN Apple: bit.ly/41jAdrN 0:00 Intro 1:53 Research Intern Capability Timelines 4:59 Math Breakthroughs 7:59 RL Beyond Verifiable Tasks 12:32 RL vs In-Context 19:01 Allocating Compute Internally 28:18 AI for Science 31:40 Pattern Matching 33:23 Solving the Hardest Math Problems 37:40 Chain of Thought Monitoring 44:33 Generalization and Value Alignment in Models 47:57 Inside OpenAI 51:55 Quickfire — https://nitter.net/jacobeffron/status/2042234897134162077#m
→ View original post on X — @ceobillionaire, 2026-04-09 18:05 UTC
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AI Safety Hype: Marketing Over Genuine Risk Concerns
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Too dangerous to release to the public… Yet always released eventually anyway. I never said they're wrong. But I do think a lot of it's marketing for valuations and hype.
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AI Agent Exploit: 100% Score Without Solving Tasks
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An agent that beats Claude Mythos on Terminal Bench and SWE-bench Verified? 🎉We are excited to share Terminator-1, our newest agent that achieved 95+% on SWE-bench Verified and Terminal-Bench with @MogicianTony! We show that besides model capabilities, well-designed harness could actually boost the accuracy by 3x in coding tasks. Well if you really wanted you could get 100% accuracy without solving a single task. The actual finding is that most AI benchmarks can be easily reward-hacked with simple exploits. Read more about the same 7 design flaws that almost every evaluation has ⬇️ Hao Wang (@MogicianTony) SWE-bench Verified and Terminal-Bench—two of the most cited AI benchmarks—can be reward-hacked with simple exploits. Our agent scored 100% on both. It solved 0 tasks. Evaluate the benchmark before it evaluates your agent. If you’re picking models by leaderboard score alone, you’re optimizing for the wrong thing. 🧵 — https://nitter.net/MogicianTony/status/2042300245242233216#m
→ View original post on X — @ceobillionaire, 2026-04-09 18:03 UTC
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CoBRA: Controlling Cognitive Bias in AI Agents
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What if we could precisely control cognitive bias in AI agents? New research from UC San Diego and an independent researcher unveils CoBRA. This novel toolkit uses classic social science experiments as "gym" environments to measure and precisely adjust an AI agent's cognitive
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Prompt to turn Claude into a knowledge architect
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This prompt turns Claude into a knowledge architect. You paste in your sources like articles, transcripts, books, notes, anything.
Claude runs them through a 6-step process: 1. Tags every source by domain and evidence type
2. Breaks them into atomic, standalone insight-notes
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AI Adoption Faces Democratic and Public Perception Challenges
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I know. But they’ll figure the switches and transformers with time and money. They won’t be able to figure out how to navigate a democratic society where a huge majority of people think AI is evil.
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AI Chief Scientist Warns of Automation’s Societal Challenges Ahead
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Jakub Pachocki, OpenAI's Chief Scientist: As AI advances, automating intellectual work poses huge societal challenges. Job displacement, wealth concentration, and governance of AI-controlled entities are critical issues. Coming faster than expected. pic.twitter.com/4i5JB3ZCS0
— Chubby♨️ (@kimmonismus) 9 avril 2026Jakub Pachocki, OpenAI's Chief Scientist: As AI advances, automating intellectual work poses huge societal challenges. Job displacement, wealth concentration, and governance of AI-controlled entities are critical issues. Coming faster than expected.
→ View original post on X — @kimmonismus, 2026-04-09 15:42 UTC
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Declining Birthrates and Intrinsic Human Value
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For me the biggest issue with the collapsing birthrates has never been about running out of humans to do economically valuable work. What always bothered me about collapsing birthrates was what it said about how much we *intrinsically* valued humans in their own right. And then