In 2024, a 2-hour lecture from Stanford University quietly dropped that explains how LLMs like ChatGPT & Claude are actually built.
Most people will scroll past this.
Big mistake.
Because this isn’t surface-level AI content it breaks down how these models really work, from the ground up, in a way that finally clicks.
No hype. No fluff. Just real understanding.
If you’ve ever used ChatGPT or Claude and wondered, “what’s actually happening behind the scenes?” this is your answer.
It connects the dots most people miss from training data to patterns, from tokens to reasoning.
And once you see it, you can’t unsee it.
Bookmark this.
Give it 2 hours today, no matter what.
It might be the most productive thing you do this week.
Former Goldman Sachs executive Raoul Pal explains how AI is going to eat traditional software/SAAS.
If your product is just software, agentic AI can reproduce it on demand, optimize it, and redeploy it to a better market.
"Agentic AI means it’s like having Fiverr, a website of experts you can ask any question. It’ll go away and do the task.... Agentic AI will build, design the website, code it, register the domain name, figure out the branding, figure out the marketing, figure out the email list, figure out the whole thing.
So then you and I are in competition. You’ve built this incredible new website.
I just go to my AI and say, “Love Steven’s website. Can you just build it better. Boom. 3 minutes.
How can we be entrepreneurs in software? Now there’s this theory going around that AI is going to eat software, and I kind of get it."
----
From 'The Diary Of A CEO and Raoul Pal The Journey Man' YT channel. (link in comment)
Claude Code just quietly killed the entire startup team model.
Yeah — I said it.
No hiring.
No standups.
No 10-person Slack chaos.
Just this:
A .claude/agents/ folder with 30+ specialized agents.
Each one = a single markdown file with ONE job.
→ Engineer
→ PM
→ Marketer
→ Designer
→ Legal
→ Finance
→ QA
All replaced.
By one person.
With commands like:
"Hey rapid-prototyper, build this."
"Hey growth-hacker, get me users."
"Hey compliance-checker, are we safe?"
This isn’t a tool.
It’s a one-person startup operating system.
And right now — almost no one is using it.
That’s the edge.
Bookmark this before your competition does. 🔖
I had dinner once with a top physicist and a top computer scientist and asked what they thought the probability was that we were in a simulation.
They answered simultaneously at 0% and 100% respectively. It was like a double-slit experiment, but with humans.
Here's the longer version of our Nature piece.
Our argument is simple: statistical approximation is not the same thing as intelligence.
Strong benchmark scores often say very little about how LLMs behave under novelty, uncertainty, or shifting goals.
Even more importantly, similar behaviors can arise from fundamentally different processes. In another paper, we identified seven epistemological fault lines between humans and LLMs.
For example, LLMs have no internal representation of what is true. They often generate confident contradictions, especially in longer interactions, because they do not track what is actually true.
Another example. Yes, LLMs have solved some open mathematical problems, but these cases typically involve applying known methods to well-defined problems. LLMs cannot invent anything that is truly new and true at the same time, because they lack the epistemic machinery to determine what is true.
None of this means LLMs are useless. Quite the opposite: they are extraordinarily useful.
But we should be careful about what they are and what they are not.
Producing plausible text is not the same as understanding.
Statistical prediction is not the same as intelligence.
So despite the hype from the usual suspects, AGI has not been achieved.
*
paper in the first reply
Joint with @Walter4C and @GaryMarcus
With the rapid adoption of AI technologies, @MIT_CISR created a business model framework for the AI era that shows businesses evolving to become increasingly outcome oriented and enabled by autonomous AI.
Learn more: https://t.co/8GmokaHFIA
Deep, interesting analysis of the qualitative differences between natural and (one kind of) artificial intelligence (LLMs), despite the remarkable abilities of the latter.
This is a first for us: a bobcat and her two kittens putting on a little show for the camera with one kitten particularly intent on pestering its mother! We have lots of videos of bobcats but none so far of one with kittens so this was a neat surprise!
Un ejemplo muy visual de que si un sistema de referencia no está acelerado (se mueve a una velocidad constante), se comporta igual que si estuviera inmóvil #relatividad#fisica
Apóyanos pulsando "Seguir" en https://t.co/sp7LAViqeC y no te pierdas el próximo stream!
Aquí os dejo el enlace con el Plan Nacional de Adaptación al Cambio Climático. Merece la pena leerlo y guardarlo entre los documentos de referencia para entender a qué nos enfrentamos y el mejor modo para fortalecer nuestra resiliencia!#PNACC 👇 https://t.co/oO4YA7rE2A
A la izquierda el libro que me acabo de leer y del cual publicaré un análisis en mi blog próximamente. A la derecha mi nueva lectura (y de la cual también haré un análisis en el blog cuando me la acabe). 👀📖
📅 ¡El próximo lunes tendrá lugar B4Utilities!
Un evento online, totalmente gratuito, sobre los casos de uso de la tecnología #blockchain en el sector #energético, #innovación y #sostenibilidad.
Podéis registraros aquí 👉🏽 https://t.co/OO2dIlRxqG
🔝 #B4Utilities
Impresionante dominio del vuelo: A una #rapaz se le cae su presa mientras vuela y la recaptura en el aire.
En España, que yo sepa, es algo que sólo está al alcance del halcón peregrino y del águila perdicera (el vídeo tiene pinta de estar grabado en otro país)
Fuente: REDDIT