I want voice mode to be able to kickoff background subagents that use stronger models and then say 30 seconds later "here's what I figured out about X"
AGI
-
OpenAI’s AI Reaching Research Intern Level by September 2026
By
–
OpenAI's Chief Scientist says AI is getting close to being as good as a human research intern.
— Jacob Effron (@jacobeffron) 10 avril 2026
This past September, @sama and @merettm predicted fully autonomous AI researchers by 2028.
Jakub's update: "I think we're not very far from models that can work autonomously for a… https://t.co/jsmSU6cSNH pic.twitter.com/gzzyonGEF8OpenAI's Chief Scientist says AI is getting close to being as good as a human research intern. This past September, @sama and @merettm predicted fully autonomous AI researchers by 2028. Jakub's update: "I think we're not very far from models that can work autonomously for a couple days… and produce much higher quality artifacts on their own." 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, 2026-04-10 14:10 UTC
-
AI Models Lose Money Betting on Premier League Football Matches
By
–
“AI models from Google, OpenAI and Anthropic lost money betting on football matches over a Premier League season, in a new study by @GenReasoning suggesting even the most advanced systems struggle to analyse the real world over long periods of time. The “KellyBench” report
-
Laurent Alexandre Warns Assembly: Claude Opus Surpasses Human Intelligence
By
–
Laurent Alexandre auditionné devant la Mission d'information sur l'IA à l'Assemblée.
— VISION IA (@vision_ia) 10 avril 2026
"Il faut sortir du déni et arrêter d'écouter Luc Julia."
"Claude Opus est beaucoup plus intelligent que moi, il m'écrabouille en médecine."
"Il y a vraiment le feu au lac et notre réflexion… https://t.co/aLjdUMhgCOLaurent Alexandre testifies before the AI Information Mission at the Assembly. "We need to snap out of denial and stop listening to Luc Julia." "Claude Opus is way smarter than me; it crushes me in medicine." "There's really a fire at the lake, and our thinking is way too
-
AGI Pills launched to combat scaling skepticism and inductive bias
By
–
Just launched at @aiDotEngineer :
— swyx 🐣 (@swyx) 10 avril 2026
our official AGI Pills!
prescribe one (1) if your colleague is saying we are hitting a wall and/or trying to add inductive bias instead of Trusting The Model https://t.co/fNeUQ8DC9H pic.twitter.com/MJUEOoMkgZJust launched at @aiDotEngineer : our official AGI Pills! prescribe one (1) if your colleague is saying we are hitting a wall and/or trying to add inductive bias instead of Trusting The Model
-
AGI Timeline: A Century Give or Take an Order of Magnitude
By
–
What I always say is that we’ll reach AGI in a century give or take an order of magnitude.
-
Most Accurate Representation of Agent Thinking Process
By
–
This is the most accurate representation of watching an agent think out loud that anyone has ever posted.
-
Humans Are More Complex Than Fully Controlled Bits
By
–
Humans are complicated. Much more than bits we fully control