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Do AI companies work?

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Re: Do AI companies work?

#201

Post by LtWorf »

bhouston wrote: post #189
HillRat wrote: post #166

Earlier quoted context omitted.

LLMs are a utility, not a platform, and utility markets exert a downward pressure on pricing. Moreover, it's not obvious that -- once trained models hit the wild -- any one actor has or can develop significant competitive moats that would allow them to escape that price pressure. Beyond that, the digital marginal cost of services needs to be significantly reduced to keep these companies in business, but more efficien…

> LLMs are a utility, not a platform, and utility markets exert a downward pressure on pricing. I think competition exerts a downward pressure on pricing, not being a utility personally. But I guess I agree with the utility analogy in that there are massively initial upfront costs and then the marginal costs are low. > more efficient models leads to pushing inference out to end-user compute, which hollows out their b…

I'm running on a decade old computer and it is just fine. 10 years ago a decade old computer vs a current one would have made a huge difference.

Re: Do AI companies work?

#202

Post by bangaroo »

pavlov wrote: post #140
ActionHank wrote: post #122

Earlier quoted context omitted.

The car wasn't a horse that was better, but a car has not changed drastically since they went mainstream. They've gotten better, more efficient, loaded with tech, but are still roughly 4 seats, 4 doors, 4 wheels, driven by petroleum. I know that this is a massive oversimplification, but I think we have seen the "shape" of LLMs\Gen AI\AI products already and it's all incremental improvements from here on out with more…

Feels like someone might have said this in 1981 about personal computers. "We've pretty much seen their shape. The IBM PC isn't fundamentally very different from the Apple II. Probably it's just all incremental improvements from here on out."

the difference is a personal computer is a vaguely-shaped thing that has a few extremely broad properties and there is tremendous room inside that definition for things to change shape, grow, and improve. processor architecture, board design, even the methods of powering the machine can change and you still meet the basic definition of "a computer."

for better or worse, people saying AI in any capacity right now are referring to current-generation generative AI, and more specifically diffusion image generation and LLMs. that's a very specific category of narrowly-defined technologies that don't have a lot of room to grow based on the way that they function, and research seems to be bearing out that we're starting to reach peak functionality and are now just pushing for efficiency. for them to improve dramatically or suddenly and radically change would require so many innovations or discoveries that they are unrecognizable.

what you're doing is more akin to looking at a horse and going "i forsee this will last forever because maybe someday someone will invent a car, which is basically the same thing." it's not. the limitations of horses are a feature of their biology and you are going to see diminishing returns on selectively breeding as you start to max out the capabilities of the horse's overall design, and while there certainly will be innovations in transportation in the future, the horse is not going to be a part of them.

Re: Do AI companies work?

#203

Post by tovej »

sapphicsnail wrote: post #177
lostphilosopher wrote: post #134

Earlier quoted context omitted.

PhD itself is an abbreviation for "Doctor of Philosophy." The title is more about the original Greek "lover of wisdom" than about the modern academic discipline of philosophy. https://en.wikipedia.org/wiki/Doctor_of_Philosophy Doctor is similar - in the US, when someone says "Doctor" they usually mean "Medical Doctor" but "Doctor" just comes from the Greek "teacher" / "scholar" which is more broad and the title can s…

Just a little correction. Doctor is Latin and roughly means "someone who has learned a lot." Science also originally referred to knowledge. What we think of as "science" used to be called the natural sciences. Sometimes people get confused because I have a B.S. in Classics because science has lost that broader meaning.

It is still called natural science, but it used to be called natural philosophy.

And it is interesting, as you say, that when it comes to Bachelor/Master/Doctor of Science/Art/Philosophy (even professor), these are all titles formed from arbitrary terms that have been enshrined by the institutions that give people these titles.

Re: Do AI companies work?

#204

Post by snapcaster »

skydhash wrote: post #190
snapcaster wrote: post #155

Earlier quoted context omitted.

What do you think a dog or cat does that can't be replicated by LLMs?

Act on its own?

What does it mean for something to "act on its own"? Every action taken is in some part due to what's happening in the environment right? I would argue that nothing "acts on it's own"

Re: Do AI companies work?

#205

Post by aketchum »

pzs wrote: post #196
foobiekr wrote: post #104

Earlier quoted context omitted.

In particular: "There is, however, one enormous difference that I didn’t think about: You can’t build a cloud vendor overnight. Azure doesn’t have to worry about a few executives leaving and building a worldwide network of data centers in 18 months." This isn't true at all. There are like 8 of these companies stood up in the last three or four years fueled by massive investment of sovereign funds - mostly the saudi,…

"The real problem is the ROI on AI spending is.. pretty much zero. The commonly asserted use cases are the following: Chatbots Developer tools RAG/search" I agree with you that ROI on _most_ AI spending is indeed poor, but AI is more than LLM's. Alas, what used to be called AI before the onset of the LLM era is not deemed sexy today, even though it can still make very good ROI when it is the appropriate tool for solv…

AI is a term that changes year to year. I don't remember where I heard it but I like that definition that "as soon as computers can do it well it stops becoming AI and just becomes standard tech". Neural Networks were "AI" for a while - but if I use a NN for risk underwriting nobody will call that AI now. It is "just ML" and not exciting. Will AI = LLM forever now? If so what is the next round of advancements called?

Re: Do AI companies work?

#206

Post by Mistletoe »

aketchum wrote: post #205
pzs wrote: post #196

Earlier quoted context omitted.

"The real problem is the ROI on AI spending is.. pretty much zero. The commonly asserted use cases are the following: Chatbots Developer tools RAG/search" I agree with you that ROI on _most_ AI spending is indeed poor, but AI is more than LLM's. Alas, what used to be called AI before the onset of the LLM era is not deemed sexy today, even though it can still make very good ROI when it is the appropriate tool for solv…

AI is a term that changes year to year. I don't remember where I heard it but I like that definition that "as soon as computers can do it well it stops becoming AI and just becomes standard tech". Neural Networks were "AI" for a while - but if I use a NN for risk underwriting nobody will call that AI now. It is "just ML" and not exciting. Will AI = LLM forever now? If so what is the next round of advancements called?

https://en.wikipedia.org/wiki/AI_effect

Re: Do AI companies work?

#207

Post by w10-1 »

Two models to address how/why/when AI companies make sense:

(1) High integration (read: switching) costs: any deployment of real value is carefully tested and tuned for the use-case (support for product x, etc.). The use cases typically don't evolve that much, so there's little benefit to re-incurring the cost for new models. Hence, customers stay on old technology. This is the rule rather than the exception e.g., in medical software.

(2) The Instagram model: it was valuable with a tiny number of people because they built technology to do one thing wanted by a slice of the market that was very interesting to the big players. The potential of the market set the time value of the delay in trying to replicate their technology, at some risk of being a laggard to a new/expanding segment. The technology gave them a momentary head start when it mattered most.

Both cases point to good product-market fit based on transaction cost economics, which leads me to the "YC hypothesis":

The AI infrastructure company that best identifies and helps the AI integration companies with good product-market fit will be the enduring leader.

If an AI company's developer support consist of API credits and online tutorials about REST API's, it's a no-go. Instead, like YC and VC's, it should have a partner model: partners use considerable domain skills to build relationships with companies to help them succeed, and partners are selected and supported in accordance with the results of their portfolio.

The partner model is also great for attracting and keeping the best emerging talent. Instead of years of labor per startup or elbowing your way through bureaucracies, who wouldn't prefer to advise a cohort of the best prospects and share their successes? Unlike startup's or FAANG, you're rewarded not for execution or loyalty, but for intelligence in matching market needs.

So the question is not whether the economics of broadcast large models work, but who will gain the enduring advantage in supporting AI eating the software that eats the world?

Re: Do AI companies work?

#208

Post by tene80i »

datavirtue wrote: post #151
LASR wrote: post #147

I lead an applied AI research team where I work - which is a mid-sized public enterprise products company. I've been saying this in my professional circles quite often. We talk about scaling laws, superintelligence, AGI etc. But there is another threshold - the ability for humans to leverage super-intelligence. It's just incredibly hard to innovate on products that fully leverage superintelligence. At some point, AI…

"In my mind, already with GPT-4, we're not generating ideas fast enough on how best to leverage it." This is the main bottle neck, in my kind. A lot of people are missing from the conversation because they don't understand AI fully. I keep getting glimpses of ideas and possibilities and chatting through a browser ain't one of them. On e we have more young people trained on this and comfortable with the tech and under…

What was the demo? And what is the advantage of integrating local LLMs vs third party?

Re: Do AI companies work?

#209

Post by WhyOhWhyQ »

ToucanLoucan wrote: post #164
bhouston wrote: post #161

Earlier quoted context omitted.

> The big missing thing between both the metaphor in the OP's link and yours is that I just can't fathom any of these companies being able to raise a paying subscriber base that can actually cover the outrageous costs of this tech. It feels like a pipe dream. I suspect these companies will introduce ads at some point similar to Google and Facebook for similar reasons, and it will be highly profitable.

I mean that's quite an assertion given how the value of existing digital ad space is already cratering and users are more than ever in open rebellion against ad supported services. And besides which, isn't the whole selling point of AI to be an agent that accesses the internet and filters out the bullshit? So what, you're going to do that, then add your own bullshit to the output?

I agree with everything you said in your previous post. The LLM as a search engine might basically eat Google's lunch in the same way the internet ate cable tv's lunch. Cable tv was a terrible product due to the advertising, and you could escape the BS by watching stuff online. Now look where we are.

Re: Do AI companies work?

#210

Post by WhyOhWhyQ »

benrutter wrote: post #95
analog31 wrote: post #40

Earlier quoted context omitted.

On an amusing note, I've read something similar: Everything that works stops being called philosophy. Science and math being the two familiar examples.

Just in case anyone's curious, this is from Bertrand Russell's "the history of philosophy". > As soon as definite knowledge concerning any subject becomes possible, this subject ceases to be called philosophy, and becomes a separate science. I'm not actually sure I agree with it, especially in light of less provable schools of science like string theory or some branches of economics, but it's a great idea.

In college my Professor told me he was disappointed that the string theory hype was dying down because it made for a great subfield of algebraic geometry.
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