🚨 Anthropic just showed a 27-minute workshop on how to actually do prompts for Claude.
Taught by the people who built it.
Free. No registration. No paywall.
I've seen $300 courses that don't cover what they teach in the first 8 minutes.
Watch it and bookmark it now.
Stanford just put a $200,000 education on YouTube for free and most people scrolled past it.
Professor Chad Jones gave you 1 hour of economic data that most people will only understand when it's too late.
Economist at Stanford GSB, the man who studies what happens after the biggest technological shifts in history.
No tuition, no campus, no $200,000 debt, just 1 hour and a YouTube link.
Electricity changed the world, the internet changed the world, he just explained why AI does both at the same time.
The article below is the 25 prompts that turn everything he described into your advantage.
This 1 hour lecture on "Probability Theory" from MIT will teach you more about prediction markets than 2 month internship at at a Wall Street Quant firm.
Bookmark this & give it 1 hour today, no matter what. It’s the most productive start you can give your week. Then read post below.
You enjoyed America’s Next Top Model back in the day. I’m not saying the show wasn’t messed up, but when you view content from the 2000s with the lens of today, you’re bound to find some twisted shit. We were all part of the problem fyi, not just Tyra. You were entertained.
There’s a reason many women don’t report sexual assault. Shandi from America’s Next Top Model had her assault completely filmed start to finish from multiple angles and had over a dozen witnesses. No one stepped in. She was vilified. Women know the system doesn’t work for us.
these two think they can dodge blame for how Shandi was sexually assaulted and then the show spun the narrative that she cheated on her boyfriend… oh no honey
What breaks my heart even more for Shandi is how young she was, having her abuse filmed, broadcasted & spinned into a cheating storyline. Imagine the time it must’ve taken her to unlearn the gilt and realise she did nothing wrong? #ANTM#Netflix#RealityCheck
Let’s be real: Academia is dead.
The peer review system has devolved into a zero-sum game of gatekeeping. We have PhD students—who are literal competitors—judging each other's survival. It’s not "scientific exchange" anymore; it’s a reward system for those who game the broken evaluation matrix.
If the judges are biased, justice is an illusion. Time to stop pretending.
🚨 This MIT paper just broke everything we thought we knew about AI reasoning.
These researchers built something called Tensor Logic that turns logical reasoning into pure mathematics. Not symbolic manipulation. Not heuristic search. Just tensor algebra.
Here's how it works:
Logical propositions become vectors. Inference rules become tensor operations. Truth values propagate through continuous transformations.
Translation? Deduction and neural computation finally speak the same language.
This isn't symbolic AI bolted onto deep learning. It's not deep learning pretending to do logic. It's a unified framework where both happen simultaneously.
Every major AI model today hits a wall with consistency because logic is discrete and gradients are continuous. You can't backpropagate through "true or false."
Tensor Logic erases that boundary completely.
The system embeds Boolean reasoning, probabilistic inference, and predicate logic inside a single differentiable framework. That means you can train it end-to-end like a neural network while maintaining logical guarantees.
In experiments, the system performs logical inference as matrix operations. Neural nets can now reason with symbolic precision. Symbolic systems can learn from data like neural nets.
The numbers are wild. The system handles complex logical queries with the same computational efficiency as matrix multiplication. No expensive search. No combinatorial explosion.
But here's the part that should terrify the incumbents: this scales.
Traditional symbolic AI chokes on ambiguity. Neural networks hallucinate logical structures. Tensor Logic gets both right simultaneously.
If this approach spreads, we might finally get models that don't just predict truths they can prove them. Systems that reason with mathematical certainty while learning from messy real-world data.
The implications go way beyond academic AI. Every system that needs both learning and guarantees autonomous vehicles, medical diagnosis, financial systems, legal reasoning just got a new foundation.
Current AI is either good at learning or good at logic. Never both.
That dichotomy just ended.
The fusion of logic and learning isn't coming. It's already here.