Earlier quoted context omitted.
You may be forgetting that ChatGPT has 10M paying customers. Not to mention everyone that pays for Claude Pro, Perplexity Pro, and so on.
The math on this doesn't work.
…go on?
Do AI companies work?
51–60 of 457 posts
Re: Do AI companies work?
#52> If the proprietary models stop moving forward, the open source ones will quickly close the gap. This is the Red Queen hypothesis in evolution. You have to keep running faster just to stay in place. On it's face, this does seem like a sound argument that all the $$ following LLMs is irrational: 1. No matter how many billions you pour into your model, you're only ever, say, six months away from a competitor building…
> it seems irrational to start putting in even the fewer billions of dollars now, knowing the above two points
This doesn’t follow. One, there are cash flows you can extract in the interim—standing in place is potentially lucrative.
And two, we don’t know if the curve continues until infinity or asymptotes. If it asymptotes, being the first at the asymptote means owning a profitable market. If it doesn’t, you’re going to get AGI.
Side note: bought but haven’t yet read The Red Queen. Believe it was a comment of yours that lead me to it.
Re: Do AI companies work?
#53I've found that everything that works stops being called AI. Logic programming? AI until SQL came out. Now it's not AI. OCR, computer algebra systems, voice recognition, checkers, machine translation, go, natural language search. All solved, all not AI any more yet all were AI before they got solved by AI researchers. There's even a name for it: https://en.m.wikipedia.org/wiki/AI_effect?utm_source=perplex...
I think when things get really good, which I've no doubt will happen, we'll call it SI; Synthetic Intelligence
But it may be a while.
Re: Do AI companies work?
#54I've found that everything that works stops being called AI. Logic programming? AI until SQL came out. Now it's not AI. OCR, computer algebra systems, voice recognition, checkers, machine translation, go, natural language search. All solved, all not AI any more yet all were AI before they got solved by AI researchers. There's even a name for it: https://en.m.wikipedia.org/wiki/AI_effect?utm_source=perplex...
On an amusing note, I've read something similar: Everything that works stops being called philosophy. Science and math being the two familiar examples.
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Re: Do AI companies work?
#55I've found that everything that works stops being called AI. Logic programming? AI until SQL came out. Now it's not AI. OCR, computer algebra systems, voice recognition, checkers, machine translation, go, natural language search. All solved, all not AI any more yet all were AI before they got solved by AI researchers. There's even a name for it: https://en.m.wikipedia.org/wiki/AI_effect?utm_source=perplex...
I think when things get really good, which I've no doubt will happen, we'll call it SI; Synthetic Intelligence But it may be a while.
Bert is already not an LLM and the vector embedding it generates are not AI. It is also first general solution for natural language search anyone has come up with. We call them vector databases. Again I'd wager this is because they actually work.
Re: Do AI companies work?
#56This is like when VCs were funding all kinds of ride share, bike share, food delivery, cannabis delivery, and burning money so everyone gets subsidized stuff while the market figures out wtf is going on. I love it. More goodies for us
Where I live the ridesharing/delivering startups didn't bring goodies, they just made everything worse.
They destroyed the Taxi industry, I used to be able to just walk out to the taxi rank and get in the first taxi, but not anymore. Now I have to organize it on an app or with a phone call to a robot, then wait for the car to arrive, and finally I have to find the car among all the others that other people called.
Food delivery used to be done by the restaurants own delivery staff, it was fast, reliable and often free if ordering for 2+ people. Now it always costs extra, and there are even more fees if I want the food while it's still hot. Zero care is taken with the delivery, food/drinks are not kept upright and can be a total mess on arrival. Sometimes it's escaped the container and is just in the plastic bag. I have ended up preferring to go pickup food myself over getting it delivered, even when I have a migraine, it's just gone to shit.
Re: Do AI companies work?
#57I've found that everything that works stops being called AI. Logic programming? AI until SQL came out. Now it's not AI. OCR, computer algebra systems, voice recognition, checkers, machine translation, go, natural language search. All solved, all not AI any more yet all were AI before they got solved by AI researchers. There's even a name for it: https://en.m.wikipedia.org/wiki/AI_effect?utm_source=perplex...
> Logic programming? AI until SQL came out. Now it's not AI. logic programming is not directly linked to SQL, and has its own AI term now: https://en.wikipedia.org/wiki/GOFAI .
The original SQL was essentially Prolog restricted to relational algebra and tuple relational calculus. SQL as is happened when a lot of cruft was added to the mathematical core.
Re: Do AI companies work?
#58>Therefore, if you are OpenAI, Anthropic, or another AI vendor, you have two choices. Your first is to spend enormous amounts of money to stay ahead of the market. This seems very risky though Regarding point 6, Amazon invested heavily in building data centers across the US to enhance customer service and maintain a competitive edge. it was risky. This strategic move resulted in a significant surplus of computing pow…
No, this an incorrect analogy on most points. Amazon retail marketplaces are absolutely not correlated with distributed data centers. Most markets are served out of a single cluster, which is likely to be in a different country; eg historically all of Europe from dublin, the americas from virginia, and asia pacific from seattle/portland.
The move of the retail marketplace hosting from seattle to virginia happened alongside, and continued long after, the start of AWS.
It is an utter myth, not promoted by Amazon, that AWS was some scheme to use “surplus computing power” from retail hosting/operations. It was an intentional business case to get in to a different B2B market as a service provider.
Re: Do AI companies work?
#59I've found that everything that works stops being called AI. Logic programming? AI until SQL came out. Now it's not AI. OCR, computer algebra systems, voice recognition, checkers, machine translation, go, natural language search. All solved, all not AI any more yet all were AI before they got solved by AI researchers. There's even a name for it: https://en.m.wikipedia.org/wiki/AI_effect?utm_source=perplex...
I think when things get really good, which I've no doubt will happen, we'll call it SI; Synthetic Intelligence But it may be a while.
Totally agree!
Re: Do AI companies work?
#60> If the proprietary models stop moving forward, the open source ones will quickly close the gap. This is the Red Queen hypothesis in evolution. You have to keep running faster just to stay in place. On it's face, this does seem like a sound argument that all the $$ following LLMs is irrational: 1. No matter how many billions you pour into your model, you're only ever, say, six months away from a competitor building…
> it seems irrational to start putting in even the fewer billions of dollars now, knowing the above two points This doesn’t follow. One, there are cash flows you can extract in the interim—standing in place is potentially lucrative. And two, we don’t know if the curve continues until infinity or asymptotes. If it asymptotes, being the first at the asymptote means owning a profitable market. If it doesn’t, you’re goin…
Why would being the first at the (horizontal) asymptote mean owning a profitable market? In six months, somebody else is at the asymptote as well. If different models are mostly interchangable quality-wise, then the decision will mostly be made on price.
For a market to be both winner-take-all as well as lucrative, you need some kind of a feedback cycle from network effets, economies of scale, or maybe even really brutal lock-in. For example, for operating systems applications provide a network effect -- more apps means an OS will do better, a higher install base for an OS means it'll attract more apps. For social networks it's users.
One could imagine this being the case for LLMs; e.g. that LLMs with a lot of users can improve faster. But if the asymptote has been reached, then by definition there's no more improvement to be had, and none of this matters.