331–340 of 429 posts
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Huggingface are also the real actual openAI
How? What models have they put out that are relevant?
Their platform for easy distribution and management of models has sped up the ecosystem more so.
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decentralization != coinshit
https://en.wikipedia.org/wiki/Emad_Mostaque Read his Wikipedia page and tell me he doesn’t sound like your run of the mill crypto scammer. > He claims that he holds B.A. and M.A. degrees in mathematics and computer science from the University of Oxford.[7][8] However, according to him, he did not attend his graduation ceremony to receive his degrees, and therefore, he does not technically possess a BA or an MA.[7]
At the start of 2021, according to their website, it was a 55 year old bank. By the end of 2021, it was a 70 year old bank!
The bank's website is a WordPress site. And their customers must be unhappy - online banking hasn't worked for nearly two years at this point.
Anyway, their Deputy CEO gave this hilarious interview from his gaming rig. A 33 year old Deputy CEO, who by his LinkedIn claimed to have graduated HEC Lausanne in Switzerland with a Master of Science at the age of 15... celebrating his graduation by immediately being named Professor of Finance at a university in Lebanon. While dividing his spare time between running hedge funds in Switzerland and uhh... Jacksonville, FL.
The name of his fund? Indepedance [sic] Weath [sic] Management. Yeah, okay.
In this hilariously inept interview, he claimed that people's claims about Deltec's money movements being several times larger than all the banking in their country was due to them misunderstanding the country's two banking licenses, the names of which he "couldn't remember right now" (the Deputy CEO of a bank who can't remember the name of banking licenses), and he "wasn't sure which one they had, but we might have both".
Once the ridicule and all this started piling on, within 24 hours, he was removed from the bank's website leadership page. When people pointed out how suspicious that looked, he was -re-added-.
The bank then deleted the company's entire website and replaced it with a minimally edited WordPress site, where most of the links and buttons were non-functional and remained so for months thereafter.
I mean fuck it, if the cryptobros want to look at all that and say "seems legit to me", alright, let em.
6 months ago, I expressed my doubt about the viability of Stability business model on HN News. Mostaque answered the questions with a resounding yes and claimed the business of Stability.AI is better than ever. Today he resigned.
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Mixtral 8x7b is better than both of those and runs on a top spec M3 Max wonderfully.
Indeed! Also, Mixtral 8x7b runs just as well on older M1 Max and M2 Max Macs, since LLM inference is memory bandwidth bound and memory bandwidth hasn't significantly changed between M1 and M3.
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Midjourney is the most popular discord channel by far with 19.5M+ members, $200M in revenue in 2023 with 0 external investments and only 40 employees. The problem has nothing to do with commercializing image gen AI and all to do with Emad/Stability having seemingly 0 sensible business plans. Seriously this seemed to be the plan: Step 1: Release SD for free Step 2: ??? Step 3: Profit The vast majority of users couldn'…
Leonardo.ai have basically done exactly this and seem to be doing OK. It’s a shame because they’re literally just using stable diffusion for all their tech but built a nicer front end and incorporated control net. No-where else has done this. Controlnet / instantID etc are the really killer things about SD and make it way more powerful than Midjourney, but they aren’t even available via the stability API. They just d…
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The `big' AI models are trillion parameter models. The medium sized models like GPT3 and Grok are 185b and 314b respectively. There is no way for _anyone_ to run these on a sub $50k machine in 2024, and even if you can the token generation speed on CPU is under 0.1 tokens per second.
You can get registered DDR4 for ~$1/GB. A trillion parameter model in FP16 would need ~2TB. Servers that support that much are actually cheap (~$200), the main cost would be the ~$2000 in memory itself. That is going to be dog slow but you can certainly do it if you want to and it doesn't cost $50,000.
2 x 32GB: $142
2 x 64GB: $318
8GB: $16
2 x 16GB: $64
2TB of 128GB DDR4 ECC: $9,600 (https://www.amazon.com/NEMIX-RAM-Registered-Compatible-Mothe...)
> Servers that support that much are actually cheap (~$200)
What does this mean? What motherboards support 2TB of RAM at $200? Most of them are pushing $1,000. With no CPU.
It may not hit $50K, but it's definitely not going to be $2K.
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> Business minded folks are already starting to deeply question where the value is relative to the amount of money spent on training. Not just training but inference too, right? They have to make money off each query.
Yes. Each query needs to generate enough revenue to pay for the cost of running the query, a proportional cost of the cost to train the original model, overhead, SG&A, etc. just to break even. Few have shown a plan to do that or explained in a defensible way how they’re going to get there. A challenge at the moment is a lot of the AI movement is led by folks that are brilliant technologists but have little to no expe…
This is saying nothing about "technologists" (or as they're starting to become derided as "wordcels": people that communicate well, but cannot execute anything themselves).
It would be... not trivial, but straightforward to map out the finances on everything involved, and see if there is room from any standpoint (engineering, financial, product, etc.) to get queries to breakeven, or even profitable.
But at that point, I believe the answer will be "no, it's not possible at the moment." So it becomes a game of stalling, and burning more money until R&D finds something new that may change that answer (a big if).
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> Business minded folks are already starting to deeply question where the value is relative to the amount of money spent on training Kinda. In my experience, the bigger issue is the skillset has largely been diffused. Overtraining on internal corpora has been more than enough to enable automation benefits, and the ecosystem around ML is very robust now - 10 years ago SDKs like Scikit-learn or PyTorch were much less r…
I agree with you. My reference in business questioning value was on the flood of money going into building new models. That’s where we will see a significant and painful culling soon as it’s all becoming quite commoditized and there’s only so much room in the market when that happens. Tooling, security services and other things to build on top of a commoditized generative AI market opens up other doors for products t…
In my experience, there really hasn't been that significant of a flood of money in this space for several years now, or at least not to the level I've seen based on discussion here on HN.
I think HN tends to skew towards conversations around models for some reason, but almost all my peers are either funding or working on either tooling or ML driven applications since 2021.
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I've found HN to have a horrible noise to value signal nowadays, and people with experience (eg. My friends in the YC community) deviating towards Bookface or in person meetups instead now.
There was a flood of new accounts in the 2020-22 period (my hunch is it's LessWrong, SSC, and Reddit driven based on the inside jokes and posts I've been seeing recently on HN) but they don't reflect the actual reality of the industry.
2024 is going to shift into a tough year for AI. Business minded folks are already starting to deeply question where the value is relative to the amount of money spent on training. Many/most of the GenAI companies have interesting ideas but no real business plan. Many of the larger AI companies look very shaky in terms of their governance and long term stability. Stability is showing itself to be very unstable, OpenA…