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AI 2040: Plan A

ai-2040.com

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Re: AI 2040: Plan A

#421

Post by 27183 »

kalkin wrote: post #402
27183 wrote: post #389

Earlier quoted context omitted.

> Imagining something in advance is not necessary at all for scientific advancement. This is particularily true in AI, and no one expects to imagine what superintelligence is until after it is created. Then why does anyone expect to create it? I'll take a stab at an answer: they think an LLM is some kind of "incremental improvement" and therefore a step along the inevitable path to discovering AI. But that seems delu…

> actually intelligent It's reasonable to doubt that LLMs are a path to AGI, but I don't understand how this is still a matter of dispute in 2026. What's your definition of intelligence that doesn't cover an entity that can translate fluently between dozens of languages and also solve open problems in mathematics? And be real-if you have one, is it a definition you or anyone would have given a decade ago, or are we d…

I can't give you or your sibling a better answer than "you'll know it when you see it". Some people see it now. I think they're wrong, because it seems like the results you're describing are easily explained by fuzzy search in the space of embeddings and then forming strings of plausible tokens related to the resulting region of embeddings space. In other words, the things we know LLMs actually do.

That's more or less looking for interesting patterns in a jpeg or another lossy compression result. It's interesting that the models seem to be able to (fairly) reliably return relevant chunks of the image. Even more interestingly, they seem to be able to invent plausible chunks of image that aren't even there. That doesn't meet my bar for intelligence though. I'd need to see it learn and adapt. I'd need to see it be clever, not merely "knowledgeable". I'd need to see it capably analyze itself. I'd need to see it reasonably estimate uncertainty and know itself in the sense that it has some idea how right or wrong it is about something. I'd need to see it exercise judgment.

I don't think I'd give a different answer a decade ago but who knows.

[edit] For all we know, one of the salient features of intelligence is that intelligent beings are incapable of precisely defining it. I'm not sure how productive it is to attempt to do so.

Re: AI 2040: Plan A

#422

Post by HDThoreaun »

grey-area wrote: post #419
fwipsy wrote: post #381

Earlier quoted context omitted.

I remember thinking exactly the same thing around 5-7 years ago, in the GPT-2/GPT-3 era. "Oh sure they can produce semi-coherent output, but truly intelligent behavior is still far away. This isn't science fiction, they're just falling prey to Pascal's Mugging same as my religious friends did." Now I'm not so sure. I give the AI safety subculture as a whole a lot of credit for putting it on my radar back when it was…

Effective altruism is also very attractive to manipulative sociopaths who want to maximise their power over others whilst appearing virtuous and hoarding wealth and power. Poster boy for this movement is the convicted fraudster SBF. I believe Altman is also a fan. As to a better world or super intelligence, I’ll believe it may be possible when I see some signs of intelligence from what people are calling AI, instead…

And what movement isn’t attractive to manipulative sociopaths who want to maximize their power? That’s unavoidable when dealing with humans.

Re: AI 2040: Plan A

#423

Post by fulafel »

BurningFrog wrote: post #92
a_vanderbilt wrote: post #24

I found the AI 2027 paper to be overly optimistic, but not wholly fantastical. This paper feels wildly speculative, and relies on premises I am not confident even pass surface reasoning. Even under optimistic conditions, we are not going to see robots "capable of 95% of all cognitive and physical tasks" by 2035. Nor do I think a 74% unemployment rate is even remotely possible. Economic collapse would implode AI devel…

> Nor do I think a 74% unemployment rate is even remotely possible 250 years of constant automation has never produced large scale unemployment, despite obsoleting everyone's jobs several times over.

It has. For example mechanization of argiculture in places where it didnt coincide with a manufacturing boom (latin america, india, africa) resulted in shantytowns and long term unemployment.

Re: AI 2040: Plan A

#424

Post by exizt88 »

KaiserPro wrote: post #251

The biggest issue with 2027 was that it didn't understand the economy. For AI2027 to be real, the money has to come from somewhere to carry on building the economy. If >10% of the workers suddenly become unemployed, and the rest taking paycuts, then money supply dries up. (unless central banks do something, but then that can be highly inflationary) Without massive amounts of investment, AI development stops dead. In…

> For AI2027 to be real, the money has to come from somewhere to carry on building the economy. If >10% of the workers suddenly become unemployed, and the rest taking paycuts, then money supply dries up. (unless central banks do something, but then that can be highly inflationary)

Why would it be inflationary?

Re: AI 2040: Plan A

#425

Post by HDThoreaun »

romanhounds wrote: post #368
MichaelDickens wrote: post #366

Earlier quoted context omitted.

I would rather see you engage with the substance of the article rather than skipping right to insulting the authors. I don't think this sort of comment is up to the standard I have come to expect from HN.

> I intend to donate (at least) 20% of my lifetime income to effective charities. I publish my donations on my Donations page. From your bio I suspect you're already in the cult.

Imagine thinking someone donating money is evidence of something bad

Re: AI 2040: Plan A

#426

Post by kalkin »

27183 wrote: post #421
kalkin wrote: post #402

Earlier quoted context omitted.

> actually intelligent It's reasonable to doubt that LLMs are a path to AGI, but I don't understand how this is still a matter of dispute in 2026. What's your definition of intelligence that doesn't cover an entity that can translate fluently between dozens of languages and also solve open problems in mathematics? And be real-if you have one, is it a definition you or anyone would have given a decade ago, or are we d…

I can't give you or your sibling a better answer than "you'll know it when you see it". Some people see it now. I think they're wrong, because it seems like the results you're describing are easily explained by fuzzy search in the space of embeddings and then forming strings of plausible tokens related to the resulting region of embeddings space. In other words, the things we know LLMs actually do. That's more or les…

I appreciate the straightforwardness, but you probably understand that's pretty unsatisfying.

Actually, stronger - it's valid in some circumstances to say something is infeasible to precisely to define and you'll just know it when you see it. But I don't think it's reasonable to take that stance and then assert that "anyone sound of mind who knows how an LLM works" must agree with what you see. You gotta pick between striving for rigor and denying your opponents' soundness of mind.

Re: AI 2040: Plan A

#427

Post by gabriel-uribe »

wastedpotencial wrote: post #275
gabriel-uribe wrote: post #73

Earlier quoted context omitted.

I remember being blown away by o1-o3 family of models finally stringing together coherent agentic tool calls to write and execute scripts semi-reliably for workloads in the several minutes before they would start hallucinating/flailing. GPT 5 was a bit ahead of that, but barely Now we take for granted that the latest models can juggle between multiple browser tabs, applications, databases, simulators, docker etc to w…

Can you share what's your setup for all that orchestration? I feel way behind just asking Claude Code for code edits. Is there any site where people share different AI setups, besides youtube?

Fwiw, don't buy into all the hype that you're falling behind. Yes, AI does cool things now, but I would say the impact is still unproven past indie hackers or early-stage startups. And a lot of the esoteric setups people have created with things like OpenClaw have become outdated as quickly as they were conceived.

The popular thing is now to setup loops (eg I setup hourly integrations for Claude/Codex to 1) scrape my Linear, claim achievable tasks, and push PRs or 2) do root cause analysis on customer issues that evaded automated filters, to name a few)

Though for me, my setup still feels mundane. I have AGENTS.md, CLAUDE.md etc and a few skill files. These are purposefully light - tons of examples online you can pull from online. Mine are fairly personal to my setup and products.

Importantly, I also allow Claude and Codex to bypass permissions. Yes, there is a risk they wipe my machine. The productivity upside has been worth it, for me (haven't been burned yet, ~9+ months into running models this way, I have backups, use cloud etc).

As far as maintaining quality, one of the most helpful guardrails over the past year, for me, has been requiring my agents to pipe their changes to local reviewers through OpenCode, Cursor, etc agents to have a council of models with different biases reviewing the changes, and autonomously working towards a completed objective. No matter how good Claude or Codex gets, for example, I will probably always want a different model checking its work. Like GLM, (now with 4.5) Grok, Composer.

Several OpenAI, Anthropic, xAI employees, and popular AI engineers post on X and share helpful tips & updates. Highly recommend for keeping a pulse on startups and AI. I haven't found something close, honestly, other than when I spend time in SF talking to people.

Re: AI 2040: Plan A

#429

Post by leoc »

reasonableklout wrote: post #205
leoc wrote: post #131

Earlier quoted context omitted.

Things like https://www.tobyord.com/writing/hourly-costs-for-ai-agents and https://www.tobyord.com/writing/mostly-inference-scaling seem in line with other accounts like https://www.youtube.com/watch?v=aR20FWCCjAs ?

The author of the posts you linked also wrote https://www.tobyord.com/writing/inference-scaling-reshapes-a... which posits: > AI labs may also be able to reap tremendous benefit from these inference-scaled models by using them as part of the training process. If so, the large scale-up of compute resources could go into post-training rather than deployment. This would have very different implications for AI governance…

> So "inference scaling is required to scale capabilities" doesn't mean that we're reaching the top of the S-curve in intelligence.

On its own it wouldn't. But that article came before the later article https://www.tobyord.com/writing/hourly-costs-for-ai-agents which adds the claim that inference (along with everything else being employed at present) is scaling poorly with increasing task lengths. Now maybe the December 2025 claim is wrong, or maybe things will change soon, but the February 2025 article surely doesn't establish either of those.

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