5 ms·
Surprisingly low valuation, even in this market. Possibly because of the bizarre terms and structure of other past rounds
by nylonstrung 3y ago
Surprisingly low valuation, even in this market.
Possibly because of the bizarre terms and structure of other past rounds
- runnerup 3y agoWhat are the largest IPO's so far? Have we had many go public over $30B of market cap?
- blitzar 3y agoSaudi Aramco - 1.7tn and Facebook - 100bn spring to mind.
- MichaelRazum 3y agoAgree, somewhere it was mentioned that you get kind of a bond or limited time equity.
- PostOnce 3y agoThat's up for debate. They have yet to prove it profitable/viable/useful, and 100,000 companies are working on eating their lunch. Others are walling off their data (e.g. reddit). It'll be interesting, at least.
- drumhead 3y agoThere might be doubts about how it's actually going to make any money. A sense of reality is starting to force it's way into the capital markets maybe.
- davidatbu 3y agoI'm curious, why would there be doubts? GPT-4 is incredibly useful, and it's clear there's so much straightforward bits of additional product development on top of it in various verticals that will be incredible productivity multipliers in the respective verticals.
- _hypx 3y agoThere's a real danger that people will just run LLMs on their local GPUs. It's not a guarantee that an online service is a profitable idea.
- fafqg 3y agoYou could say the same about many SaaS projects. Why pay for an expensive GPU upfront and then some guy who can install it, configure it, create some sort of interface for you to talk to it... when you can just pay openai to do it for less money?
- awesomeMilou 3y agoBecause GPU-Servers that can run a typical LLM are less than 5k, which includes installation. Really, running an LLM seems to be no more complicated than running a NAS from a system administrators perspective. Emphasis on running, not training.
- MichaelZuo 3y ago5k can't even get you 80 GB of VRAM on a GPU. How is that possible?
- nullsense 3y agoGoing to need some insanely beefy GPU cluster at your house to run anything close to GPT-4. The best I can run is either LLaMa 65B at 1 token per second (too slow) on my CPU or LLaMa 30B on my GPU at quite a fast ~30 tokens a second. Nowhere near the usefulness of GPT-4.
- _hypx 3y agoGPUs in the future will get more powerful. Especially if they are designed with LLMs in mind.
- 3y ago
- Loic 3y agoIt is making money now. The really big difference with respect to all the other search engines, cat pictures websites, etc. is that the current users expect to pay and pay to have access to the API. This is for me the key difference between something like Google Search and OpenAI/ChatGPT, from the start, people are paying to get answers to their questions.
- neel8986 3y agoThey have absolutely no moat. Trained on published architecture using publicly available data. By the end of 2023 all companies including meta, Google, and Amazon will be have similar models. Only moat they currently have is tons of specially curated data for rlhf which other companies are catching up.
- revelio 3y agoGPT-4 is pretty clearly not just public data + public papers. It's a lot of optimizations and other things on top of what is itself a lot of optimizations and other things that led to GPT-3. We're going to have to wait and see if OpenAI has a moat. You could have argued in 2001 that Google had no real moat. All they were doing was indexing public data with an algorithm they'd already published in a research paper, after all. But it turned out to be a deep space with an endless potential for optimizations and improvements, combined with the need for great expertise in scalable computations and ad optimization that other companies just weren't able to catch up with even after trying hard for years.
- wodenokoto 3y agoWe’ve seen “sweat-shops” in African countries where hordes of people are annotating video for training self driving cars. Id be surprised if the same thing isn’t true for chatgpt.
- thdespou 3y agoCompetition is rumping up.