Eron

AI researcher & builder | Content creator |

[Eron @0xEronn]

MIT PROFESSOR WHO TAUGHT AI FOR 30 YEARS EXPLAINED WHY CLAUDE AND GPT STILL DON'T UNDERSTAND THE WORLD - AND WHAT THEY'RE MISSING

we share 94% of our DNA with chimpanzees - but 50,000 years ago a small group of humans got a capability no other species on the planet has

Representations → Models → Algorithms → Intelligence

Chomsky put it this way: humans learned to take two concepts and create a third from them - without limits and without losing the original two

Claude and GPT process text better than any doctor or lawyer - but if you fill a bucket with water and run - they don't know your leg will get wet - you know because you imagined it

Deep Blue beat the world chess champion not because it thought like a human - but because it processed millions of moves like a bulldozer processes gravel - power without understanding

Alan Turing won World War II by breaking the German code - the British government drove him to suicide for being gay - AI exists because of a man who was already gone by 1954

Lady Lovelace wrote the first programs in 1842 - a hundred years before there were computers to run them on

what models are missing is not data and not parameters - they are missing the internal simulation of the world that appeared in humans 50,000 years ago and has never been reproduced in any machine

bookmark and watch the lecture - this is the only video that explains where AI ends and the human begins

[Stefan. @paradeevic]

https://t.co/fJgVOFIBhG

[Eron @0xEronn]

he is 88 years old, has studied AI for 33 years - and in 30 minutes explained why most AI agents live in an imaginary world

LLMs hallucinate not because they are broken but because that is how they work - without verification nobody catches it when the model invents facts with 97% confidence

an LLM without tools does nothing - it only predicts words - tools give it hands but loops give it the ability to compute anything a machine can compute

loops can drift, go infinite and burn thousands of dollars in tokens - every iteration costs real money and without a stop condition nobody notices

ontology is a formal map of entities and relationships - a second refund on the same order gets caught - a payment sent to the wrong place gets caught - a status field returning "probably shipped" gets caught

expert systems failed in the 1980s because they could not scale - neural networks fixed scaling - now combining both is what keeps agents from going off the rails

save and watch today - 30 minutes from the person who has seen every AI hype cycle and knows exactly which parts actually last

[Codez @0xCodez]

https://t.co/Ph3433giJj

[Eron @0xEronn]

Google course replaces 100 hours of AI automation learning - in 10 minutes you know everything to build your own AI company

the best AI engineers stopped writing longer prompts - and started context engineering

bigger context does not mean better answers - two facts contradict and the model picks the wrong one

4 ways your agent silently fails: hallucinated fact gets reused, model fixates on old history, unrelated details push wrong answers, two sources disagree and nobody catches it

prompt engineering is how you ask - context engineering is everything the model sees - assembled fresh before every single call

4 fixes: notes outside the context window, only what matters this turn, old history in 3 lines, isolated subagents

bookmark this and watch later - the difference between a $50K and a $500K AI developer

[Codez @0xCodez]

https://t.co/Ph3433giJj

[Eron @0xEronn]

He has worked at Microsoft for 50 years and in 10 minutes showed how he made TypeScript + Opus 5 10x faster:

00:00 - compilation that took a minute now takes 5 seconds
08:27 - how Opus 5 becomes 10x smarter with the new speed
12:10 - AI features that become possible when everything runs 10x faster

After watching I realized my TypeScript project could have been compiling in 5 seconds instead of 60 - this whole time.

Bookmark & watch - the article below shows how to get 10x speed today.

[Avid @Av1dlive]

https://t.co/j2vJKM9JlH

[Eron @0xEronn]

MICROSOFT'S LEAD ENGINEER BUILT TYPESCRIPT 7 - AND YOUR PROJECT NOW COMPILES 10X FASTER WITHOUT CHANGING A LINE OF CODE

Visual Studio Code - 1.3 million lines, 8,000 files - TypeScript 6 took 50 seconds - TypeScript 7 takes 6.5 seconds - same machine same code

old compiler used 1 core out of 16 while 15 sat idle - TypeScript 7 uses all of them simultaneously

TypeScript is now number one on GitHub - 1 billion downloads per month

Opus 5 reads your entire TypeScript codebase in seconds, finds the bug, fixes it and opens a PR - while TypeScript 7 compiles the result before you finish your coffee

Claude Code + TypeScript 7 - agent compiles, checks and deploys 10x faster for the same price

upgrade today - the free performance is already waiting

[Avid @Av1dlive]

https://t.co/j2vJKM9JlH

[Eron @0xEronn]

Andrej Karpathy works without days off for 3 years, co-founded OpenAI from scratch - and shared this with 30 students at a private conference for $100K

backpropagation is not complex math - it is one simple idea repeated millions of times

every node in a neural network receives numbers, does something with them and passes them forward - the only thing it needs to know is how its actions affected the final result

chain rule is not about math - it is about how blame for a mistake passes back through the entire chain to every parameter

11 lines of Python is enough to train a neural network - everything else is just forward → backward → update repeated millions of times

do not think of a neural network as a formula - think of it as a graph where every node knows only its local task and the chain figures out the rest

save this and watch today - what cost $100K at a private conference is now free

[Khairallah AL-Awady @eng_khairallah1]

https://t.co/6G146QuPo8