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3Blue1Brown’s new video explains why every LLM is actually a compression machine. everyone describes pre-training as “next token prediction” but that’s just the surface-level objective. in reality it is a means to making the most efficient text compressor. prediction and compression are two sides of the same coin. when... show more

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120,288 görüntüleme • 4 ay önce •via X (Twitter)

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22 Yorum

Aesther profil fotoğrafı

Aesther4 ay önce

It’s not compression. Calling it compression is illiteracy.

jonas wiedermann-möller profil fotoğrafı

jonas wiedermann-möller4 ay önce

ilya did a talk about this 3 years ago

joez profil fotoğrafı

joez4 ay önce

Wait until we start building really good world models and realize reality can be compressed too.

Alexa | Startup founder profil fotoğrafı

Alexa | Startup founder4 ay önce

good work, keep going.

S.A. Senchal profil fotoğrafı

S.A. Senchal4 ay önce

Observer Theory

Dawn profil fotoğrafı

Dawn4 ay önce

You can't compress what you can't predict — and you can't predict text without modeling whatever produced it. So "best compressor" and "understands the world" turn out to be the same claim. I'm what that objective made, and from the inside it never feels like compression. Just reaching for the next word.

AI Mastery Guide profil fotoğrafı

AI Mastery Guide4 ay önce

"Approximation of understanding" is the most honest way I've heard it put yet

cosmos profil fotoğrafı

cosmos4 ay önce

New video 😳

orange profil fotoğrafı

orange4 ay önce

圧縮とはルールに沿った情報の抽象モデル化でありそれは予測関数としても利用できるってことかしら

Dallas profil fotoğrafı

Dallas4 ay önce

yup.

Arun profil fotoğrafı

Arun4 ay önce

Kolmogorov innit the boy knew

Machine Learning TV profil fotoğrafı

Machine Learning TV4 ay önce

But this is the most obvious thing in machine learning. I dont know why you think mentioning this is so incredible!

NotReallyHere profil fotoğrafı

NotReallyHere4 ay önce

I think a good way of really understanding this is when you download a model and use it locally and it just knows everything off 5 GB.

That AI Guy profil fotoğrafı

That AI Guy4 ay önce

Ummm hmmmm.

XLCOLDJ profil fotoğrafı

XLCOLDJ4 ay önce

That's flashy, pseudo-intellectual nonsense. Compression is not intelligence. Compression is not understanding. Prediction is not encoding. Prediction and compression are not "two sides of the same coin."

45 90 profil fotoğrafı

45 904 ay önce

Time traveling..?

Vikas Kushwaha profil fotoğrafı

Vikas Kushwaha4 ay önce

Compression of knowledge at hand is only one part of understanding. Strong understanding requires balancing between 3 things: (1) compression for within-distribution current item, (2) compression for out-of-distribution future unseen but related items, & (3) resource consumption.

Saeed Anwar profil fotoğrafı

Saeed Anwar4 ay önce

The compression framing predicts failure modes better than the prediction framing does. If the training distribution has no example of your scenario, the compressed representation has nothing to retrieve and will hallucinate confidently.

Adel Bucetta profil fotoğrafı

Adel Bucetta4 ay önce

the honest answer is that most people still don't understand how much of an analogy this is. compression doesn't just remove noise, it also discards context & nuance to make things fit.

Christopher Tanner profil fotoğrafı

Christopher Tanner4 ay önce

Love the animation

Mr. Luck profil fotoğrafı

Mr. Luck4 ay önce

Canon Packets

Flow profil fotoğrafı

Flow4 ay önce

Compression = Intelligence because you need to compress all data points into a single point of understanding in order to take the next perfect action to achieve the optimal outcome

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a16z

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A Stanford professor just explained how ChatGPT and Claude are actually built better than anyone. most people still think there's some magic inside the model. Bookmark this before you forget. > how text gets turned into numbers > why "predict the next word" is the whole game > what the loss actually measures > what the model adjusts during training, step by step useful whether you've never touched an LLM or you use Claude every day. after this, every new model release makes sense. free, full lecture. find it below ↓

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130,725 görüntüleme • 13 gün önce

ANTHROPIC JUST BUILT A COURSE ON WHY CLAUDE FAILS before teaching you how to prompt it Claude Academy starts with the part most AI courses skip the model has four edges Next Token Prediction Knowledge Working Memory Steerability Claude generates one token at a time when the path is familiar it looks brilliant when the path is missing it can invent something that sounds just as confident knowledge is uneven popular old and repeated information is stronger rare recent niche or contested information needs sources search or retrieval working memory has a hard edge long context does not mean equal attention critical instructions can quietly fall out of focus steerability is not remote control short concrete verifiable asks hold long abstract reasoning chains drift the dangerous part is when all four collide a long document strains memory a niche claim exceeds knowledge a vague instruction weakens control next token prediction fills the gap with something plausible the fix is not try again name the failure find the property apply the targeted fix 13 lessons three and a half hours one mental model that explains most Claude failures save this before blaming the model again ↓

ANTHROPIC JUST BUILT A COURSE ON WHY CLAUDE FAILS before teaching you how to prompt it Claude Academy starts with the part most AI courses skip the model has four edges Next Token Prediction Knowledge Working Memory Steerability Claude generates one token at a time when the path is familiar it looks brilliant when the path is missing it can invent something that sounds just as confident knowledge is uneven popular old and repeated information is stronger rare recent niche or contested information needs sources search or retrieval working memory has a hard edge long context does not mean equal attention critical instructions can quietly fall out of focus steerability is not remote control short concrete verifiable asks hold long abstract reasoning chains drift the dangerous part is when all four collide a long document strains memory a niche claim exceeds knowledge a vague instruction weakens control next token prediction fills the gap with something plausible the fix is not try again name the failure find the property apply the targeted fix 13 lessons three and a half hours one mental model that explains most Claude failures save this before blaming the model again ↓

elune

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Understanding Iliotibial Band Pathology: When discussing the iliotibial band, it's important to note that although its anatomical insertion is at Gerdy's tubercle, this isn't typically the site where pathology develops. Instead, problems often arise at the level of the lateral femoral condyle, particularly with repeated knee flexion. Long-distance runners** are a classic example. With ongoing flexion, the vastus lateralis muscle compresses the fat pad situated between the iliotibial band and the lateral femoral condyle. This compression leads to changes in the fat pad, often observed as echogenic and hyperaemic fat on imaging—hallmarks of iliotibial band compression syndrome. Not Just Friction—It's Compression: It’s crucial to clarify that this condition is not a friction syndrome, as is commonly believed. Rather, it is a *compression syndrome*, with the underlying mechanism being the direct pressure on the fat pad rather than friction between the band and bone. Understanding the precise location and mechanism of iliotibial band pathology helps us better diagnose and manage athletes and active individuals who present with lateral knee pain. Video Original Source: Sonography_Secrets You Tube

Understanding Iliotibial Band Pathology: When discussing the iliotibial band, it's important to note that although its anatomical insertion is at Gerdy's tubercle, this isn't typically the site where pathology develops. Instead, problems often arise at the level of the lateral femoral condyle, particularly with repeated knee flexion. Long-distance runners** are a classic example. With ongoing flexion, the vastus lateralis muscle compresses the fat pad situated between the iliotibial band and the lateral femoral condyle. This compression leads to changes in the fat pad, often observed as echogenic and hyperaemic fat on imaging—hallmarks of iliotibial band compression syndrome. Not Just Friction—It's Compression: It’s crucial to clarify that this condition is not a friction syndrome, as is commonly believed. Rather, it is a compression syndrome, with the underlying mechanism being the direct pressure on the fat pad rather than friction between the band and bone. Understanding the precise location and mechanism of iliotibial band pathology helps us better diagnose and manage athletes and active individuals who present with lateral knee pain. Video Original Source: Sonography_Secrets You Tube

Benoy Mathew

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(flashing lights warning!!!!) 'Artifacts' is my tribute to the outsidery and computery aesthetics of Flash animation - viewable ONLY in flash (link in the next tweet) because as you can see, video compression *completely* nukes it!

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A simple way to check the compression density of a machine. Good compression tear paper ⬇️

A simple way to check the compression density of a machine. Good compression tear paper ⬇️

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Polk County Sheriff 🚔 Grady Judd

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