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Comment by danielhanchen | Hacker News Reader

Sorry about that - I'm super new to pricing and stuff so it might seem off since I'm literally making the plans with my bro as we go along.

If you don't believe the timings, I was the author of Hyperlearn https://github.com/danielhanchen/hyperlearn which makes ML faster - I also listed the papers which cite the algos.

I also used to work at NVIDIA making TSNE 2000x faster on GPUs and some other algos like Randomized SVD, sparse matrix multiplies etc.

If you have any suggestions on a more appropriate pricing strategy - I'm all ears!!

I really don't know much about pricing and the open core model, so I'm making stuff up literally.

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If this is all legit, you’re best trying to get an in somehow with a16z. They’re throwing money left and right at people doing this kind of stuff.

Oh my A16z? Do you have any contacts? :))

But for now - our goal is somehow to get revenue ourselves via some cool AI products, and trying to shrink the expenses to 0 (like via our fast training methods)

One approach you could take is to license the code (or simply the tricks) to big tech companies. They can use the tricks, but must pay you x amount. You can provide technical support for implementation and benchmarking.

That's how I would make profit from what you're doing as many big tech companies have already achieved (and more) of what you claim.

I know this as I work in such a company. However, I'd bet they'd pay a fair amount for new solutions that differ from their own.

Hmm the main issue sounds like the market capture is limited - I highly disagree bigtech companies have achieved what we already have - maybe OpenAI or other AI companies might have done it - but it's all "might" have.

I worked myself in the past at NVIDIA making algos faster, so it's not a done deal big tech companies have all the tips and tricks. They have the best hardware, but software not so much.

The issue with licensing code is your revenue capture is minimal - maybe a training platform which provides everyone and not just big tech companies a cheap and efficient implementation sounds much better.

The issue with licensing is how much do you charge? How do you monitor usage? Etc

Pro says single GPU some places and multi-GPU others. I really hope it is multi-GPU because basically every enthusiast making finetunes is using 2-4 3090s locally or renting 8x GPU boxes on Vast for finetuning. If multi-GPU is enterprise only you will miss out on basically the largest customer segment as far as I can tell.

Apologies on the confusion - I'm still trying to flesh stuff out on the differentating factors with my bro - I'll update it once we're fully sure - sorry again!

> Apologies on the confusion

You might want to get some distance from talking to language models.

Are the 30x claims comparing full update training vs qlora/4bit weights?

Sorry about the confusion - the 30X is comparing QLora with QLora - all benchmarking is QLoRa bsz=2, ga=4

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