341–350 of 460 posts
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Next up: CEO level model to run your company. Pricing starts at $800k/month plus stock options
That no one is offering this says something very profound to me. Either they don't work and are too risky to entrust a company to, or leadership thinks they are immune and are entitled to wield AI exclusively, or some mix of these things.
"Microsoft has poured over $13 billion into the AI firm since 2019..." My understanding is that this isn't really true, as most of those "dollars" were actually Azure credits. I'm not saying those are free (for Microsoft), but they're a lot cheaper than the price tag suggests. Companies that give away coupons or free gift certificates do bear a cost, but not a cost equivalent to the number on them, especially if they…
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That implies learning. Solve continual learning and you have agi. Wouldn't it amaze you if you learned 10 years ago that we would have AI that could do math and code better than 99% of all humans. And at the same time they could barely order you a hotdog on doordash. Fundamental ability is lacking. AGI is just as likely to be solved by Openai as it is by a college student with a laptop. Could be 1yr or 50yrs we canno…
Strictly speaking I'm not sure if it does require learning if information representing the updated context is presented. Though it depends what you define as learning. ("You have tried this twice, and it's not working.") is often enough to get even current LLM's to try something else. That said, your second paragraph is one of the best and most succinct ways of pointing out why current LLM's aren't yet close to AGI i…
RAG is a basically a perfect example to understand the limits of in context learning and AI in general. It's faults are easier to understand but the same as any AI vs AGI problem.
I could go on but CL is a massive gap of our knowledge and likely the only thing missing to AGI.
I think they have realized that even if OpenAI is first, it won't last long so really its just compute at scale, which is something they already do themselves.
There is no moat in models (OpenAI). There is a moat in infra (hyperscalers, Azure, CoreWeave). There is a moat in compute platform (Nvidia, Cuda). Maybe there's a moat with good execution and product, but it isn't showing yet. We haven't seen real break out successes. (I don't think you can call ChatGPT a product. It has zero switching cost.)
Look at Coca Cola, Google, both have plausible competitors, zero switching cost but they maintain their moat without effort.
Being first is still a massive advantage. At this point they should only strive to avoid big mistake and they're set.
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There is no moat in models (OpenAI). There is a moat in infra (hyperscalers, Azure, CoreWeave). There is a moat in compute platform (Nvidia, Cuda). Maybe there's a moat with good execution and product, but it isn't showing yet. We haven't seen real break out successes. (I don't think you can call ChatGPT a product. It has zero switching cost.)
Is anyone other than Nvdia making money from this particular gold rush?
Just look at how much money Google lost in that failed AI demo from 2003.
The stock would be worth 50% less if the invested nothing in AI. Even the founders are back because of it.
It's clear that OpenAI has peaked. Possibly because the AI hype in general has peaked, but I think moreso because the opportunity has become flooded and commoditized, and only the fetishists are still True Believers (which is something we saw during the crypto hype days, but most at the time decried it). Nothing against them, but the solutions have become commoditized, and OpenAI is going to lack the network effects…