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As someone who's built with modern LLM architectures, this Laplace transform lecture is the closest thing to a "why Mamba works" explainer I've ever seen released for free. Everyone thinks transformers are the only path to modern LLMs. State space models like Mamba and S4 challenge that using math... show more

fintex

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110,467 görüntüleme • 2 ay önce •via X (Twitter)

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As someone who ships LLM systems in production, this 22-minute Laplace transform video is the closest thing to a "why Mamba solves what transformers can't" explainer I've ever seen released for free. Everyone thinks scaling transformers is the only path forward. State space models beat them on long context using math Laplace built in 1785. This video shows the trick. Bookmark & watch today. The math is older than the United States.

As someone who ships LLM systems in production, this 22-minute Laplace transform video is the closest thing to a "why Mamba solves what transformers can't" explainer I've ever seen released for free. Everyone thinks scaling transformers is the only path forward. State space models beat them on long context using math Laplace built in 1785. This video shows the trick. Bookmark & watch today. The math is older than the United States.

fintex

26,102 görüntüleme • 2 ay önce

As someone who ships LLM systems in production, this Laplace transform video is the closest thing to a "why Mamba beats transformers" explainer I've ever seen released for free. Everyone thinks attention is what makes LLMs powerful. Laplace proved in 1785 that any signal breaks into exponential pieces - locate the poles, expose the frequencies. Mamba and Claude run on this exact trick. 34 minutes. Bookmark & watch today. The math is older than the United States.

As someone who ships LLM systems in production, this Laplace transform video is the closest thing to a "why Mamba beats transformers" explainer I've ever seen released for free. Everyone thinks attention is what makes LLMs powerful. Laplace proved in 1785 that any signal breaks into exponential pieces - locate the poles, expose the frequencies. Mamba and Claude run on this exact trick. 34 minutes. Bookmark & watch today. The math is older than the United States.

Eron

67,007 görüntüleme • 1 ay önce

As someone who trains LLMs, this 20-minute gradient descent video is the closest thing to a "why the memorization vs generalization debate matters" explainer I've ever seen released for free. Everyone thinks neural nets learn features. They often just memorize. The video walks through the 2017 paper that shocked the field: shuffle your labels randomly and modern networks will still fit them perfectly. 25 minutes. Bookmark & watch today.

As someone who trains LLMs, this 20-minute gradient descent video is the closest thing to a "why the memorization vs generalization debate matters" explainer I've ever seen released for free. Everyone thinks neural nets learn features. They often just memorize. The video walks through the 2017 paper that shocked the field: shuffle your labels randomly and modern networks will still fit them perfectly. 25 minutes. Bookmark & watch today.

fintex

15,922 görüntüleme • 2 ay önce

As someone who's been shipping LLMs since the GPT-2 days, this lecture on cross-entropy from a Stanford math grad is the closest thing to an ML PhD qualifying exam I've ever seen released publicly for free. Everyone thinks language models predict the next word. They don't. They compress language. Once you see the math, you can't unsee it. 33 minutes. Bookmark & watch today.

As someone who's been shipping LLMs since the GPT-2 days, this lecture on cross-entropy from a Stanford math grad is the closest thing to an ML PhD qualifying exam I've ever seen released publicly for free. Everyone thinks language models predict the next word. They don't. They compress language. Once you see the math, you can't unsee it. 33 minutes. Bookmark & watch today.

fintex

356,334 görüntüleme • 2 ay önce

As someone who reads every transformer paper that drops, this Fourier series lecture is the closest thing to a Google FNet explainer I've ever seen released for free. Everyone thinks attention is what makes transformers powerful. Google replaced attention with a 200-year-old Fourier transform. It nearly matched BERT and ran 7x faster. 25 minutes. Bookmark & watch today. Then read the article below - I broke down the 5 pieces of math the AI hype skips.

As someone who reads every transformer paper that drops, this Fourier series lecture is the closest thing to a Google FNet explainer I've ever seen released for free. Everyone thinks attention is what makes transformers powerful. Google replaced attention with a 200-year-old Fourier transform. It nearly matched BERT and ran 7x faster. 25 minutes. Bookmark & watch today. Then read the article below - I broke down the 5 pieces of math the AI hype skips.

fintex

101,169 görüntüleme • 2 ay önce

As someone who builds with LLMs and diffusion models, this 14-minute heat equation video is the closest thing to a "why noise reversal actually works" explainer I've ever seen released for free. Everyone thinks diffusion is a novel AI concept. It's the heat equation from 1822. The forward process spreads noise like heat, and the reverse process is what your model learns. Bookmark & watch this weekend. Same math, from 19th-century physics to 2025 image generation.

As someone who builds with LLMs and diffusion models, this 14-minute heat equation video is the closest thing to a "why noise reversal actually works" explainer I've ever seen released for free. Everyone thinks diffusion is a novel AI concept. It's the heat equation from 1822. The forward process spreads noise like heat, and the reverse process is what your model learns. Bookmark & watch this weekend. Same math, from 19th-century physics to 2025 image generation.

fintex

15,604 görüntüleme • 1 ay önce

As someone who ships LLM systems in production, this hairy ball theorem video is the closest thing to a "why positional encoding in 3D robotics always breaks" explainer I've ever seen released for free. Everyone thinks orientation in 3D space is a solved problem. A theorem from 1912 proves there is always at least one direction where any continuous vector field hits zero — the exact reason every robotics LLM glitches at certain angles. 25 minutes. Bookmark & watch today. The math is older than the airplane.

As someone who ships LLM systems in production, this hairy ball theorem video is the closest thing to a "why positional encoding in 3D robotics always breaks" explainer I've ever seen released for free. Everyone thinks orientation in 3D space is a solved problem. A theorem from 1912 proves there is always at least one direction where any continuous vector field hits zero — the exact reason every robotics LLM glitches at certain angles. 25 minutes. Bookmark & watch today. The math is older than the airplane.

Eron

58,608 görüntüleme • 1 ay önce

As someone who ships LLM systems in production, this double pendulum video is the closest thing to a "why one changed word breaks Claude and GPT-5" explainer I've ever seen released for free. Everyone thinks LLMs are deterministic machines. They're not. Every prompt to GPT-5 is a chaotic double pendulum - a tiny perturbation in the initial state (one comma, one whitespace) sends the entire response into a completely different attractor. Bookmark this 26-min video and watch tonight. Same butterfly-effect chaos that broke Poincaré's math, now the exact reason your API calls to Claude feel unreliable.

As someone who ships LLM systems in production, this double pendulum video is the closest thing to a "why one changed word breaks Claude and GPT-5" explainer I've ever seen released for free. Everyone thinks LLMs are deterministic machines. They're not. Every prompt to GPT-5 is a chaotic double pendulum - a tiny perturbation in the initial state (one comma, one whitespace) sends the entire response into a completely different attractor. Bookmark this 26-min video and watch tonight. Same butterfly-effect chaos that broke Poincaré's math, now the exact reason your API calls to Claude feel unreliable.

fintex

51,856 görüntüleme • 1 ay önce

As someone who ships LLM systems in production, this backpropagation video is the closest thing to a "why GPT actually learns" explainer I've ever seen released for free. Everyone thinks training a neural network is calculus. It's not. It's 175 billion weights getting nudged proportionally to how much each one caused the mistake. PyTorch does this backwards pass on every single training step. 20 minutes. Bookmark & watch today. The algorithm is older than the iPhone.

As someone who ships LLM systems in production, this backpropagation video is the closest thing to a "why GPT actually learns" explainer I've ever seen released for free. Everyone thinks training a neural network is calculus. It's not. It's 175 billion weights getting nudged proportionally to how much each one caused the mistake. PyTorch does this backwards pass on every single training step. 20 minutes. Bookmark & watch today. The algorithm is older than the iPhone.

Eron

20,078 görüntüleme • 1 ay önce

As someone who's spent 3 years fine-tuning ML models, this lecture on neural networks from a Stanford math grad is the closest thing to a no-bullshit "day one of ML" briefing I've ever seen released publicly for free. Everyone thinks neural nets are magic. They aren't. They're 13,000 dials - a matrix multiplication, a sigmoid squish, done. Once you see the math, "AI" stops feeling mysterious. 18 minutes. Bookmark & watch today.

As someone who's spent 3 years fine-tuning ML models, this lecture on neural networks from a Stanford math grad is the closest thing to a no-bullshit "day one of ML" briefing I've ever seen released publicly for free. Everyone thinks neural nets are magic. They aren't. They're 13,000 dials - a matrix multiplication, a sigmoid squish, done. Once you see the math, "AI" stops feeling mysterious. 18 minutes. Bookmark & watch today.

fintex

332,082 görüntüleme • 2 ay önce

As someone who trains and fine-tunes LLMs, this double descent video is the closest thing to a "why every ML textbook was wrong about GPT-5" explainer I've ever seen released for free. Everyone thinks bigger models overfit worse. They don't. Past a certain scale the test error dives again - the exact reason OpenAI and Anthropic keep scaling up instead of down. Bookmark & watch this weekend. The 2019 discovery that quietly forced Stanford professors to rewrite their textbooks and reshaped how every frontier LLM gets trained.

As someone who trains and fine-tunes LLMs, this double descent video is the closest thing to a "why every ML textbook was wrong about GPT-5" explainer I've ever seen released for free. Everyone thinks bigger models overfit worse. They don't. Past a certain scale the test error dives again - the exact reason OpenAI and Anthropic keep scaling up instead of down. Bookmark & watch this weekend. The 2019 discovery that quietly forced Stanford professors to rewrite their textbooks and reshaped how every frontier LLM gets trained.

fintex

68,769 görüntüleme • 1 ay önce

As someone who trains and fine-tunes LLMs, this backpropagation video is the closest thing to a "the calc 1 rule that trains every LLM on earth" explainer I've ever seen released for free. Everyone thinks training GPT-5 requires exotic math. It doesn't. The entire $500B AI industry runs on the chain rule from freshman calculus - the exact rule Marvin Minsky said would never work. Bookmark this 30-min video and watch tonight. Same math your high school teacher taught you, now updating every weight in Claude, GPT-5, and Llama.

As someone who trains and fine-tunes LLMs, this backpropagation video is the closest thing to a "the calc 1 rule that trains every LLM on earth" explainer I've ever seen released for free. Everyone thinks training GPT-5 requires exotic math. It doesn't. The entire $500B AI industry runs on the chain rule from freshman calculus - the exact rule Marvin Minsky said would never work. Bookmark this 30-min video and watch tonight. Same math your high school teacher taught you, now updating every weight in Claude, GPT-5, and Llama.

fintex

50,749 görüntüleme • 1 ay önce

As someone who ships LLM systems in production, this billiards video is the closest thing to a "why every stable LLM behavior is just a lucky island in a sea of chaos" explainer I've ever seen released for free. Everyone thinks GPT-5 always behaves the same way. It doesn't. Every consistent Claude answer lives on a tiny island of stability inside an infinite chaotic plane - the exact "winning zone" this video maps by bouncing balls off polygons. Bookmark this 11-min video and watch tonight. Same emergent stability math from 2007 chaos research, now the reason a single prompt tweak can drop your LLM into total gibberish.

As someone who ships LLM systems in production, this billiards video is the closest thing to a "why every stable LLM behavior is just a lucky island in a sea of chaos" explainer I've ever seen released for free. Everyone thinks GPT-5 always behaves the same way. It doesn't. Every consistent Claude answer lives on a tiny island of stability inside an infinite chaotic plane - the exact "winning zone" this video maps by bouncing balls off polygons. Bookmark this 11-min video and watch tonight. Same emergent stability math from 2007 chaos research, now the reason a single prompt tweak can drop your LLM into total gibberish.

fintex

42,313 görüntüleme • 12 gün önce

As someone who ships LLM systems in production, this sliding puzzle video is the closest thing to a "why sampling harder never finds the answer" explainer I've ever seen released for free. Everyone thinks a hard problem means a huge search space. It doesn't. Klotski has just 25,955 states, yet random search dies in the same pit every time. That's the exact reason OpenAI and Anthropic pay for guided search instead of more samples. Bookmark & watch this weekend. Same graph traversal, from a wooden toy on a coffee table to every reasoning model burning test-time compute today.

As someone who ships LLM systems in production, this sliding puzzle video is the closest thing to a "why sampling harder never finds the answer" explainer I've ever seen released for free. Everyone thinks a hard problem means a huge search space. It doesn't. Klotski has just 25,955 states, yet random search dies in the same pit every time. That's the exact reason OpenAI and Anthropic pay for guided search instead of more samples. Bookmark & watch this weekend. Same graph traversal, from a wooden toy on a coffee table to every reasoning model burning test-time compute today.

fintex

57,343 görüntüleme • 1 ay önce

As someone who ships LLM systems in production, this scaling video is the closest thing to a "why 96% of Claude and GPT-5's weights are literally useless" explainer I've ever seen released for free. Everyone thinks trillion-parameter models need every parameter. They don't. A 2019 pruning experiment proved you can delete 96% of a neural net's weights with zero performance loss - meaning most of Claude and GPT-5 is empty scaffolding around a tiny "winning lottery ticket" network doing all the real work. Bookmark this 18-min video and watch tonight. Same lottery ticket math from 2019 MIT research, now the reason every AI lab wastes 90%+ of its Nvidia budget.

As someone who ships LLM systems in production, this scaling video is the closest thing to a "why 96% of Claude and GPT-5's weights are literally useless" explainer I've ever seen released for free. Everyone thinks trillion-parameter models need every parameter. They don't. A 2019 pruning experiment proved you can delete 96% of a neural net's weights with zero performance loss - meaning most of Claude and GPT-5 is empty scaffolding around a tiny "winning lottery ticket" network doing all the real work. Bookmark this 18-min video and watch tonight. Same lottery ticket math from 2019 MIT research, now the reason every AI lab wastes 90%+ of its Nvidia budget.

fintex

788,103 görüntüleme • 21 gün önce

The secret of how Anthropic build their models like Claude is revealed in this 2 hour Stanford lecture. Stanford released the complete foundation covering transformers, LLM architecture, training & put it out for free. Bookmark & watch this today before someone takes it down.

The secret of how Anthropic build their models like Claude is revealed in this 2 hour Stanford lecture. Stanford released the complete foundation covering transformers, LLM architecture, training & put it out for free. Bookmark & watch this today before someone takes it down.

Roan

14,057 görüntüleme • 4 ay önce

Anthropic pays $750,000+ a year for engineers who can build LLM architectures from scratch. Stanford taught the entire thing in 1 hour lecture & released it for free. Bookmark & watch this today before someone takes it down.

Anthropic pays $750,000+ a year for engineers who can build LLM architectures from scratch. Stanford taught the entire thing in 1 hour lecture & released it for free. Bookmark & watch this today before someone takes it down.

Roan

2,595,185 görüntüleme • 5 ay önce

Anthropic pays $750,000+ a year for engineers who can build LLM architectures from scratch. Stanford taught the entire thing in 1 hour lecture & released it for free. Bookmark & watch this today before someone takes it down.

Anthropic pays $750,000+ a year for engineers who can build LLM architectures from scratch. Stanford taught the entire thing in 1 hour lecture & released it for free. Bookmark & watch this today before someone takes it down.

shobhanai

29,255 görüntüleme • 25 gün önce

A Stanford professor just gave a public lecture on exactly how GPT, Claude, and LLaMA are built under the hood no insider access required just the clearest breakdown of modern LLM architecture I've seen this lecture reveals the framework professors are paid up to $750K a year to teach the gap between "I use ChatGPT" and "I understand how it works" is smaller than most people think the most complete public breakdown of modern LLM architecture I've seen this year

A Stanford professor just gave a public lecture on exactly how GPT, Claude, and LLaMA are built under the hood no insider access required just the clearest breakdown of modern LLM architecture I've seen this lecture reveals the framework professors are paid up to $750K a year to teach the gap between "I use ChatGPT" and "I understand how it works" is smaller than most people think the most complete public breakdown of modern LLM architecture I've seen this year

rewind

165,059 görüntüleme • 3 ay önce

Met a guy making $1.6 million/year as an LLM engineer. I asked him how he learned LLMs from scratch. He sent me the exact video that got him in. A 1 hour course on how LLMs actually work. He shows how transformers inside LLMs like ChatGPT & Claude are actually built. I watched it last night. Halfway through, I realized LLM architecture is way simpler than they make it look. Bookmark this and read the article below. • 00:00 - LLM foundations • 04:21 - LLM tokenization • 05:43 - LLMs vector embeddings • 22:16 - attention mechanism of LLM • 43:42 - LLM multi head attention

Met a guy making $1.6 million/year as an LLM engineer. I asked him how he learned LLMs from scratch. He sent me the exact video that got him in. A 1 hour course on how LLMs actually work. He shows how transformers inside LLMs like ChatGPT & Claude are actually built. I watched it last night. Halfway through, I realized LLM architecture is way simpler than they make it look. Bookmark this and read the article below. • 00:00 - LLM foundations • 04:21 - LLM tokenization • 05:43 - LLMs vector embeddings • 22:16 - attention mechanism of LLM • 43:42 - LLM multi head attention

Roan

81,649 görüntüleme • 2 ay önce