miklel

I swear to god I’m not a llm bot

[Mike Sapiton 🇺🇦 @sapitonmix]

Finland has finally taken over the world

[miklel @miguelcece_]

Rovaniemi circular rainbow

[Minh Nhat Nguyen @menhguin]

Drake, waar is de EUV-lithografiemachine?

[doomer @uncledoomer]

in portugese, to "post a gem" simply means to post. to them, all posts are gems. portugese posters go through life in a perpetual state of posting gems. we should all be so lucky.

[cowboy @nextokens]

guy who faked-it-until-he-made-it but was starting to get in over his head can’t believe his luck when llms launched

[Odenzio @Odenzi0]

@AliceSuffererGr

[miklel @miguelcece_]

@Gddtlx @NXT4EU 🤣

[Bark🪵 @stammebark]

Listen to the Finnish 🇫🇮 commentators lose their minds on Helenius' golden goal winner! 🤣

Gold returns to the Nordics🏆

[miklel @miguelcece_]

@stammebark 🇫🇮

[miklel @miguelcece_]

@YgorIsm @VictorTaelin acho uqe é o numero máximo de blocos(cuda)

[NVIDIA Newsroom @nvidianewsroom]

A statement from NVIDIA CEO Jensen Huang.

[sahaj @sahaj__b]

What should I name this plugin?

[the tiny corp @__tinygrad__]

Or maybe LLMs simply can't code. They can only copy/paste from the project that's 95% the same -- they can't write anything new.

[@levelsio @levelsio]

What in the F is an AI factory?

I had to investigate what the unelected @EU_Commission is talking about today

So according to them, it's some data centers (which they call supercomputers) in 6 different EU countries

I checked out the most powerful one: Karolina, a Czech data center, it mostly has CPUs though (see pic) not GPUs, so mostly useless for AI

The GPUs it does have are 72x 8x NVIDIA A100 GPU, so 576x A100, or equivalent of 240x H100s

(H100 is about 2.4x the compute power of A100)

So let's compare that:

@xAI has 200,000x H100 GPUs

So the xAI data center has 800x more compute than the Czech one

If we combine xAI, Meta, AWS, etc. it's about 750,000 H100s

If we assume the other 5 data centers in the EU are equivalent to the Czech one (which is massive stretch because most of the others seem AI consultacny services, they don't even HAVE chips!), the EU's new "AI factories" have a total of 1,440x H100 GPUs, let's round up to 1,500 to be nice

So the EU is trying to compete with 750,000 GPUs with their own 1,500 GPUs, so 500x less??

Correct me if I'm wrong but it's just seems very low impact and another ridiculous idea and burning of EU tax payers money that will end up in local cronies and bureaucrats and will do NOTHING to improve the AI business climate for Europe

The best way to improve it is to deregulate, make it super easy and low tax (especially when starting out) to start AI companies in Europe

[stash @stash_pomichter]

Introducing Spatial Memory for your robots. Spatiotemporal RAG. Open source. Coming soon.

[Andrej Karpathy @karpathy]

I quite like the new DeepSeek-OCR paper. It's a good OCR model (maybe a bit worse than dots), and yes data collection etc., but anyway it doesn't matter.

The more interesting part for me (esp as a computer vision at heart who is temporarily masquerading as a natural language person) is whether pixels are better inputs to LLMs than text. Whether text tokens are wasteful and just terrible, at the input.

Maybe it makes more sense that all inputs to LLMs should only ever be images. Even if you happen to have pure text input, maybe you'd prefer to render it and then feed that in:
- more information compression (see paper) => shorter context windows, more efficiency
- significantly more general information stream => not just text, but e.g. bold text, colored text, arbitrary images.
- input can now be processed with bidirectional attention easily and as default, not autoregressive attention - a lot more powerful.
- delete the tokenizer (at the input)!! I already ranted about how much I dislike the tokenizer. Tokenizers are ugly, separate, not end-to-end stage. It "imports" all the ugliness of Unicode, byte encodings, it inherits a lot of historical baggage, security/jailbreak risk (e.g. continuation bytes). It makes two characters that look identical to the eye look as two completely different tokens internally in the network. A smiling emoji looks like a weird token, not an... actual smiling face, pixels and all, and all the transfer learning that brings along. The tokenizer must go.

OCR is just one of many useful vision -> text tasks. And text -> text tasks can be made to be vision ->text tasks. Not vice versa.

So many the User message is images, but the decoder (the Assistant response) remains text. It's a lot less obvious how to output pixels realistically... or if you'd want to.

Now I have to also fight the urge to side quest an image-input-only version of nanochat...

[Henrick Johansson @compliantvc]

@florinpop17 Pay a 60% VAT to the European Union and take the $40