🚨 Sam Altman literally gave a 43-minute masterclass on turning ideas into billion-dollar companies.
Most people will never watch it.
And instead of hype, he broke down what actually makes startups work.
No fluff. Just reality.
He explained that ideas don’t matter nearly as much as execution. The difference between something small and something massive isn’t the idea it’s how relentlessly it’s built and improved over time.
He also emphasized that the best founders don’t chase everything. They focus on one thing that truly matters and push it forward with extreme clarity. Distraction kills more startups than competition ever will.
And then there’s scale. Truly big companies aren’t built for a niche they solve problems that millions of people care about. If the market isn’t large enough, the outcome won’t be either.
His biggest insight? Startups don’t win because they’re smarter they win because they stay in the game longer and iterate faster.
That’s why this masterclass stands out.
Because while most people are waiting for the perfect idea…
The best ones are already building.
Here's my conversation all about AI in 2026, including technical breakthroughs, scaling laws, closed & open LLMs, programming & dev tooling (Claude Code, Cursor, etc), China vs US competition, training pipeline details (pre-, mid-, post-training), rapid evolution of LLMs, work culture, diffusion, robotics, tool use, compute (GPUs, TPUs, clusters), continual learning, long context, AGI timelines (including how stuff might go wrong), advice for beginners, education, a LOT of discussion about the future, and other topics.
It's a great honor and pleasure for me to be able to do this kind of episode with two of my favorite people in the AI community:
1. Sebastian Raschka (@rasbt)
2. Nathan Lambert (@natolambert)
They are both widely-respected machine learning researchers & engineers who also happen to be great communicators, educators, writers, and X posters.
This was a whirlwind conversation: everything from the super-technical to the super-fun.
It's here on X in full and is up everywhere else (see comment).
Timestamps:
0:00 - Introduction
1:57 - China vs US: Who wins the AI race?
10:38 - ChatGPT vs Claude vs Gemini vs Grok: Who is winning?
21:38 - Best AI for coding
28:29 - Open Source vs Closed Source LLMs
40:08 - Transformers: Evolution of LLMs since 2019
48:05 - AI Scaling Laws: Are they dead or still holding?
1:04:12 - How AI is trained: Pre-training, Mid-training, and Post-training
1:37:18 - Post-training explained: Exciting new research directions in LLMs
1:58:11 - Advice for beginners on how to get into AI development & research
2:21:03 - Work culture in AI (72+ hour weeks)
2:24:49 - Silicon Valley bubble
2:28:46 - Text diffusion models and other new research directions
2:34:28 - Tool use
2:38:44 - Continual learning
2:44:06 - Long context
2:50:21 - Robotics
2:59:31 - Timeline to AGI
3:06:47 - Will AI replace programmers?
3:25:18 - Is the dream of AGI dying?
3:32:07 - How AI will make money?
3:36:29 - Big acquisitions in 2026
3:41:01 - Future of OpenAI, Anthropic, Google DeepMind, xAI, Meta
3:53:35 - Manhattan Project for AI
4:00:10 - Future of NVIDIA, GPUs, and AI compute clusters
4:08:15 - Future of human civilization
🚨Breaking: This 1-hour MIT lecture on Probability Theory might teach you more about prediction markets than a 2-month quant internship.
Most people will skip it.
And that’s exactly why they’ll stay confused about how uncertainty actually works.
It’s not just math it’s a way of thinking. A framework for making better decisions when outcomes aren’t guaranteed.
Watching it feels like unlocking a new lens.
The biggest insight? Prediction isn’t about certainty it’s about probabilities. The best thinkers don’t guess outcomes, they assign likelihoods and update them as new information comes in.
It also shows why most people get decisions wrong. They rely on intuition, ignore base rates, and overreact to noise instead of signals.
And that’s the real edge. Not complex models but clear thinking under uncertainty.
That’s why this MIT lecture is worth your time.
Because while most people chase shortcuts…
A few will understand the system behind every prediction.
Bookmark this & give it 1 hour today, no matter what. It’s the most productive start you can give your week.
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