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Problems the AI industry is not addressing adequately

thealgorithmicbridge.com

131–140 of 243 posts

Re: Problems the AI industry is not addressing adequately

#131

My question is this - once you achieve AGI, what moat do you have, purely on the scientific part? Other than making the AGI even more intelligent. I see a lot of talk that the first company that achieves AGI, will also achieve market dominance. All other players will crumble. But surely when someone achieves AGI, their competitors will in all likelihood be following closely after. And once those achieve AGI, academia…

> The only things that will be out of reach for most, is compute - and probably other expensive things on the infrastructure part.

That is the moat. That, and training data.

Even today, compute and data are the only things that matter. There is hardly any secret software sauce. This means that only large corporations with a practically infinite amount of resources to throw at the problem could potentially achieve AGI. Other corporations would soon follow, of course, but the landscape would be similar to what it is today.

This is all assuming that the current approaches can take us there, of which I'm highly skeptical. But if there's a breakthrough at some point, we would still see AI tightly controlled by large corporations that offer it as a (very expensive) service. Open source/weight alternatives would not be able to compete, just like they don't today. Inference would still require large amounts of compute only accessible to companies, at least for a few years. The technology would be truly accessible to everyone only once the required compute becomes a commodity, and we're far away from that.

If none of this comes to pass, I suspect there will be an industry-wide crash, and after a few years in the Trough of Disillusionment, the technology would re-emerge with practical applications that will benefit us in much more concrete and subtle ways. Oh, but it will ruin all our media and communication channels regardless, directly causing social unrest and political regression, that much is certain. (:

Re: Problems the AI industry is not addressing adequately

#132

Earlier quoted context omitted.

Being part of the team that achieved AGI first would be to write your name in history forever. That could mean more to people than money. Also 10m would be a drop in the bucket compared to being a shareholder of a company that has achieved AGI; you could also imagine the influence and fame that comes with it.

"The grass is greener elsewhere" isn't inconsistent with a belief that AGI will happen somewhere. It means you don't have much faith that the company you're working at will be the ones to pull it off.

With a salary of $10m/year, handwave roughly half of that goes to taxes, you'd be making just shy of $100k post-tax per week. Call me a sellout, but goddamn. For that much money, there's a lot of places I could be convinced to put my faith into that I wouldn't otherwise.

Re: Problems the AI industry is not addressing adequately

#133
post #36

Earlier quoted context omitted.

>your best move is to do whatever is most profitable in the near-term Unless you’re a significant shareholder, that’s almost always the best move, anyway. Companies have no loyalty to you and you need to watch out for yourself and why you’re living.

I read that most of the crazy comp Zuck is offering is in stock. So in a way, going to the place where they have lots of stock reflects their belief about where AGI is going to happen first.

Facebook is already public, so they can sell the day it vests and get it in cold hard cash in their bank account. If Facebook weren't public it would be a more interesting point as they couldn't liquidate immediately, but they can, so I wouldn't read anything into that.

Re: Problems the AI industry is not addressing adequately

#134
post #75

Earlier quoted context omitted.

Related to your point: if these tools are close to having super-human intelligence, and they make humans so much more productive, why aren't we seeing improvements at a much faster rate than we are now? Why aren't inherent problems like hallucination already solved, or at least less of an issue? Surely the smartest researchers and engineers money can buy would be dogfooding, no? This is the main point that proves to…

> if these tools are close to having super-human intelligence, and they make humans so much more productive, why aren't we seeing improvements at a much faster rate than we are now? Why aren't inherent problems like hallucination already solved, or at least less of an issue? Surely the smartest researchers and engineers money can buy would be dogfooding, no? Hallucination does seem to be much less of an issue now. I…

> Hallucination does seem to be much less of an issue now. I hardly even hear about it - like it just faded away.

Last week I had Claude and ChatGPT both tell me different non-existent options to migrate a virtual machine from vmware to hyperv.

Week before that one of them (don't remember which, honestly) gave me non existent options for fio.

Both of these are things that the first party documentation or man page has correct but i was being lazy and was trying to save time or be more efficient like these things are supposed to do for us. Not so much.

Hallucinations are still a problem.

Re: Problems the AI industry is not addressing adequately

#135
"A disturbing amount of effort goes into making AI tools engaging rather than useful or productive."

Right. It worked for social media monetization.

"... hallucinations ..."

The elephant in the room. Until that problem is solved. AI systems can't be trusted to do anything on their own. The solution the AI industry has settled on is to make hallucinations an externality, like pollution. They're fine as long as someone else pays for the mistakes.

LLMs have a similar problem to Level 2-3 self-driving cars. They sort of do the right thing, but a human has to be poised to quickly take over at all times. It took Waymo a decade to get over that hump and reach level 4, but they did it.

Re: Problems the AI industry is not addressing adequately

#136
post #57

I keep seeing this charge that AI companies have an “Uber problem” meaning the business is heavily subsidized by VC. Is there any analysis that has been done that explains how this breaks down (training vs inference and what current pricing is)? At least with Uber you had a cab fare as a benchmark. But what should, for example, ChatGPT actually cost me per month without the VC subsidy? How far off are we?

It depends on how far behind you believe the model-available LLMs are. If I can buy, say, $10k worth of hardware and run a sufficiently equivalent LLM at home for the cost of that plus electricity, and amortize that over say 5 years to get $2k/yr plus electricity, and say you use it 40 hours a week for 50 weeks, for 2000 hours, gets you $1/hr plus electricity. That electrical cost will vary depending on location, but let's just handwave $1/hr (which should be high). So $2/hr vs ChatGPT's $0.11/hr if you pay $20/month and use it 174 hours per month.

Feel free to challenge these numbers, but it's a starting place. What's not accounted for is the cost of training (compute time, but also employee and everything else), which needs to be amortized over the length of time a model is used, so ChatGPT's costs rise significantly, but they do have the advantage that hardware is shared across multiple users.

Re: Problems the AI industry is not addressing adequately

#137

Earlier quoted context omitted.

"The grass is greener elsewhere" isn't inconsistent with a belief that AGI will happen somewhere. It means you don't have much faith that the company you're working at will be the ones to pull it off.

With a salary of $10m/year, handwave roughly half of that goes to taxes, you'd be making just shy of $100k post-tax per week . Call me a sellout, but goddamn. For that much money, there's a lot of places I could be convinced to put my faith into that I wouldn't otherwise.

It might buy loyalty for a while, but after it accumulates, for many people it would be "why am I even working at all" money.

And if they don't like their boss and the other job sounds better, well...

Re: Problems the AI industry is not addressing adequately

#138
post #36

Earlier quoted context omitted.

>your best move is to do whatever is most profitable in the near-term Unless you’re a significant shareholder, that’s almost always the best move, anyway. Companies have no loyalty to you and you need to watch out for yourself and why you’re living.

I read that most of the crazy comp Zuck is offering is in stock. So in a way, going to the place where they have lots of stock reflects their belief about where AGI is going to happen first.

But maybe the salary is also higher?

Re: Problems the AI industry is not addressing adequately

#139

Also, AGI is not just around the corner. We need artificial comprehension for that, and we don't even have a theory how comprehension works. Comprehension is the fusing of separate elements into new functional wholes, dynamically abstracting observations, evaluating them for plausibility, and reconstituting the whole - and all instantaneously, for security purposes, of every sense constantly. We have no technology th…

Translation Between Modalities is All You Need

~2028

Re: Problems the AI industry is not addressing adequately

#140

"A disturbing amount of effort goes into making AI tools engaging rather than useful or productive." Right. It worked for social media monetization. "... hallucinations ..." The elephant in the room. Until that problem is solved. AI systems can't be trusted to do anything on their own. The solution the AI industry has settled on is to make hallucinations an externality, like pollution. They're fine as long as someone…

When you say “do anything in their own”, what kind of things do you mean?
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