So where’s the return? Outside of annualized numbers I haven’t even heard people pretend that OAI or Anthropic are profitable. If this is all about ROI there’s sure been a lot of I for as yet unrealized R.

IMO the top end goal is to allow capital to access skill without allowing skill to access capital. IF they can make these products work as advertised (big if, very very big if) the corpos can fire shitloads of low-end workers and give their middle managers access to these AI models and nothing else really has to change.

Workers lose their ability to earn a living, but OpenAI and Anthropic become the gatekeepers to effectively all productivity.

I know I sound tinfoil hat here but I don't see how else the numbers work. The only thing full-priced, profit-earning AI can possibly be cheaper than is, in my mind: as much of the workforce's salaries and cost of benefits as it can manage to offset, put together.

It's a great plan if you're a CEO who can't see beyond the next quarter's earnings call. Less so if you want things like, just pulling from a hat here, a functioning economy, a stable society, the ability for humans at large to live. But it's not like the owning class hasn't been undermining all of that for the better part of 50 years anyway.

Who (what) would all these middle managers manage? Agents? Why? If agents were so capable, they'd sure be capable of managing themselves or each other...

I mean I did word that carefully, "as much of the workforce as possible." So yes entirely possible that the middle managers get automated out too.

I genuinely don't get what the endgame here is, just AI's talking to AI's everywhere and somehow they think everything just keeps on making money I guess? But then again our current crop of oligarchs are pretty mediocre all around, so calling any of this a "plan" at all feels a stretch. Just cut costs every quarter, make the products worse, fire everyone who knows anything and sail off into the sunset making more money than any human being can actually spend in the process.

Have you seen the numbers for public companies?

We can't discuss the finance of private companies so we have to wait for their IPO, acquisition by some public company, or bankruptcy to find out more.

The story written in the public numbers, from corporations or government statistics, is one of rise in factor productivity, rise in capital returns, and decline in wage participation in overall income.

I'm merely observing that it seems to be the latest chapter in the development of the capitalistic corporation.

I'm asking a legitimate question, and only two people have actually tried to make an argument.

Most, like you, have nothing useful to contribute.

please explain how you have discerned that people earnestly disagree with me?

Man there really isn’t a criticism that won’t lead to a booster saying you’re holding it wrong

It matches the reality of my experience using a good frontier like Sol on high to ultra thinking. If it has any way to verify its work whatsoever, it eventually gets to a working and sanely-engineered solution. Blatant hallucinations making it to the final stages have become extremely rare in my use cases, nonexistent if the model has a valid feedback loop. So yes, I will insist someone is likely "holding it wrong" if they still think SOTA AI is spewing out garbage at this stage when I can have it do something like write entire working kernel module fixes for old MacBooks on a whim with no crashes or flaws observed after months of use.

I think this is the issue others are having, when you say:

> when I can have it do something like write entire working kernel module fixes for old MacBooks on a whim

They’re not saying it can’t do that, and that’s not proof it doesn’t hallucinate. In fact, having used 6-8 agents at a time for a year plus while writing AI tooling for an AI startup, I can definitely surely tell you that they’re almost inversely correlated as in models that hallucinate a lot sometimes also put out the best most impressive solutions.

I’m definitely not anti AI and I definitely have found a way to make it work very well and I’m content with the work I get out of it (again maxing out several max 20x subs), but I have had sol definitely hallucinate this week and I’m a bit shocked you’re trying to say otherwise.

Listen I know it’s going to be I’m holding it wrong too, but I’ve been reading white papers and research on LLMs for a long time and was definitely at the cutting edge of context engineering, implementing features in our tooling harness a year before they were in codex or Claude.

maybe I am holding it wrong still but but like at some point if I’m holding it wrong who else will be holding it right? Dozens of people? At some point, the technology has to be approachable enough for everyone to have your point of view automatically.

What do we mean by hallucinate? I'm not counting it making a mistake that it fixes on its own without intervention.

I'm no expert on the inner workings/harnesses/etc beyond a basic understanding of the architecture. Maybe I've just developed a good sense for effective prompts? I could share some recent sessions.

> I believe a perfect solution exists. With one big caveat: you need a very clear set of requirements. Every constraint on the table. Tighten those enough and something interesting happens, you end up with only one possible solution.

This is the kind of naive thinking people are actually pushing back on when they’re telling you not to build perfect products. One of the constraints that the author refuses to acknowledge is the social constraint of leading people to a shared goal- if people keep telling you your perfect solution isn’t viable and they do not want to do it, then it’s not perfect, is it?

In general, any approach that believes there’s a One True Answer is either looking at trivial problems or naive egocentrism, in my experience.

If it makes you feel better, most people don’t think they’re real intelligences

The only way to mitigate the damage an LLM can do because of prompt injection is to limit what that LLM can do in the first place. That’s what they mean by limiting its usefulness. If an LLM has access to an api and I want it to abuse that API in some way, I can attack its prompt and eventually get it to use the api the way I want

All apis have to authorize and authenticate if they do sensitive stuff. Otherwise youre asking for it.

Yes, but whatever the LLM has authenticated access to, an attacker can convince it to mess with on their behalf.

This is strictly a San Francisco tech problem. This isn’t happening to most people

First thought was this sounds like a hyperlocal sf gripe

You think people in Austin or Denver or Atlanta don't have the same Zoom app, with the same AI helper as the one they give to San Francisco people?

I think they have the same app, but they don’t use it like this. It seems like you’re confident this happens a lot- do you live in San Francisco?

Yes! In the Ad Hominem district.

I don’t think asking if someone lives in SF is ad hominem, but go off

That you know of.

You’re the poster- do you live in the bay?

I do not. I live in fly-over country. I still see it happening.

The styling on the website makes me feel like my phone is a cylinder

It's quite distracting and frustrating. No idea why you'd want the beginning and ends of lines of text to be darker than the center.

Sorry about that, the vignette was mainly meant for the desktop view only but is indeed much more invasive/disruptive in the mobile layout.

Should be better now.

Way better- thank you!

While being slow to pass judgment or disregard an approach is a valuable trait in a senior Eng, I think 3 years is plenty of time to wait for proof of concept to pan out. It’s not panning out, it doesn’t seem on the verge of panning out, and soon the real cost is going to be passed on and the subsidies will end. LLMs see ripe to be the new IDEs, but not the new Engineers

To acquire new knowledge and build your understanding. They don’t understand so they can’t learn

Thank you for saying succinctly what I could not. If your consciousness and knowledge fundamentally does not change from your ongoing experience, then you are not learning. This is how the LLM currently functions.

You’re describing the problem of continual learning. As I said their “consciousness” for lack of a better term and knowledge does already change from ongoing experience in context which is another of saying for only a short window, today. They are ephemeral, sort of, but that’s a temporary limitation.

I think if your definition of consciousness can fit these things then you’re more open minded than I care to be. Consciousness isn’t really guessing the next thing to say- it’s hard to say what it is, obviously, but blindly feeling forwards with each new conversation doesn’t seem like consciousness or learning to me.

We aren't talking about consciousness, we're talking about learning.

> Consciousness isn’t really guessing the next thing to say-

I don't know what consciousness is either and these debates are a dumpster fire when they happen, but it sounds like you're pulling forward this "LLMs are just predicting the next token" (true by construction) implies that they can't learn or reason or be conscious (2/3 are wrong, the last one isn't falsifiable without a useful definition).

Yes, I think we simply disagree. I think you know what LLMs are based on our other thread and if you think something important happens when you get a large enough context vector I don’t think there’s much I can say to change your mind. It seems unlikely to me!

“They don’t understand” is a strong statement, maybe true but depends on what you mean by understand. What is your definition of this? I can’t think of a meaningful definition of “understand” that doesn’t apply to LLMs

We’re in all the same threads lately!