CMV: The AI CEOs are not just hyping this technology up. We really may have human-level artificial intelligence within the next decade, and too many people are dismissing AI as an overblown bubble around a technology that doesn't work.

I Must Be Bonkers

This seems like such a ridiculous position to have. I don't blame you in the least for thinking I'm a kook. How many places have I gone wrong? The idea that a machine could think like a human is sci-fi nonsense. The signs that we have a long way to go are shouting every day.

For one, I'm listening to billionaires. Isn't that stupid of me? They're deceitful and only after profit and valuation for their company. Why should I care what they have to say? They're biased. Next, how could these things possibly deliver? They make shit up wholesale. Didn't this happen before, in the eighties or something, when AI seemed like it was going to be the next big thing and it all came crashing down? Isn't that likely to happen again?

In all, it seems like I've cracked up and drank the kool-aid. Frankly, I'm not surprised that people disagree with me intensely on this. Not only is it ridiculous, but it also attacks something deep inside all of us - it attacks the idea of being human. I encourage you to pay attention to this post, because I address a lot in it, and there are probably many more points that we agree on than we disagree on.

Before I explain how I came to think this, it's important that I explain something. None of this means that I think AI is good. I think it's a severe threat to our economy, our privacy, our environment, our art and entertainment, and even our existence. That's why I care about talking to people about it. AI isn't a problem because it doesn't work. AI is a problem because it does work so far, and is only getting better. AI being an overblown bubble is bad. AI delivering on its promises could be even worse.

The Future Is Now

METR has been doing some fascinating research, see link: https://metr.org/ In a particular sense, AI has been getting 2x better at software engineering tasks every 3-7 months for the last seven years, since the invention of the transformer model. Namely, it can perform a task that would take humans 1 hour autonomously and be successful 80% of the time - three to seven months later, it can perform a software engineering task that would take humans 2 hours with the same rate of success. Today, we're at ten hours.

That means in the last seven years - seven years - large language models have gone from barely being able to string a sentence together in 2019, to being able to 'implement complex protocol from multiple RFCs', whatever that means (but I hear it takes a competent software engineer ten hours to do.) Can you imagine giving birth to a baby and seeing them knock out 8 hours of adult software engineering work at the age of seven?

Maybe this trend only applies to software engineering tasks? That wouldn't be much help - as once the computer is good enough at software engineering, it will be tasked with doing AI research to speed up AI research to improve its capabilities in other areas. Mind you, the 'implement complex protocol' task took humans 10 hours to do. The AI did it much faster.

That was a reasonable idea, and one that I would have called likely, until an MIT FutureTech paper here: https://futuretech.mit.edu/publication/crashing-waves-vs-rising-tides-preliminary-findings-on-ai-automation-from-thousands-of-worker-evaluations-of-labor-market-tasks showed that a similar rate of growth is occurring among all text-based tasks. That's any knowledge work you can do by typing and reading, which is a lot of it. For the highlight sentence in the abstract: "[if progress continues]... LLMs will be able to complete most text-related tasks with success rates of, on average, 80%–95% by 2029 at a minimally sufficient quality level". 'Most text-related tasks' is people's jobs. That's it. Full stop.

I don't dispute that current AI models are laughable at much economically available work. We know it for a fact from the Remote Labor index here: https://www.remotelabor.ai/ When it was released, the top model of the time - GPT-5.2 - could only do 2.5% of real, actual freelance work. But lo and behold, a few months later, Claude Opus 4.5 and 4.6 could do... Twice as good, at 4.17%. I predict this will continue to increase.

The AI may be flawed today. It is increasingly becoming less flawed.

What if there is a growth slowdown or stop? Another AI winter? That's very possible. I have no idea. Growth could stop tomorrow. Growth may have stopped three weeks ago. If anything, it is most likely that we will see signs of a growth slowdown before AI capabilities plateau - making a neat S-shaped curve. We do not presently see sigs of slowdown today. If we started seeing signs of slowdown tomorrow, and AI performance followed an S-curve, we would end with models that are twice as performant as they are today, in another seven years.

Taking the METR performance as a cue, the researchers behind AI 2027 have created a dynamical systems model of AI research into the future, and it has a startling prediction: That there will be AI that is 'at least as good as the top human at virtually all cognitive tasks' around 2029: https://www.aifuturesmodel.com/

I won't say human level intelligence will come in 2029. Maybe that's way too fast. Maybe it'll be in thirty years. But it seems that one is harder and harder pressed, these days, to find AI researchers and academics who believe human-level intelligence is less than fifty years away. (They exist, of course. Some even think we will never achieve it. But I believe their numbers are dwindling.)

The AI doesn't understand anything. It just predicts the next token.

This frankly doesn't matter. How can it not matter? Isn't that what thinking is?

I don't know if the AI 'understands' what it's doing, 'knows' the words it's saying, 'reasons' or not - because many people use these words to describe a purely internal process that suddenly doesn't apply when the AI starts doing it. When I reason through a problem in my head, and write out my reasoning, it's reasoning. When an AI does some complex linear algebra in its not-brain to predict the next token and spits out an identical facsimilie of reasoning, who cares what actually happened on the 'inside'? It still does economic work. It still codes your app and finds your bugs. It still does the things. The phone or computer you are reading on this right now is 'just transistors' - a lot of them, stacked up to be able to do something much more complicated than a single part. There may be something missing on the 'inside' in a spiritual or experiential sense - but that isn't required for AI to keep performing.

But it's obvious - it can't even count the R's in 'strawberry'!

Every day, there's a new post about AI making some stupid fucking mistake. It's honestly really hilarious. What, Altman, your billion-dollar plagiarism machine can't even tell someone their cup is upside down, or whether to walk or drive to the car wash?

For one, humans mess up at simple questions and intelligence tasks, too. Often. In fact, there are many things that you think we'd be able to do with ease and we actually can't - see the N-back test and change blindness for examples. If we have such huge blind spots, are we, too, incapable of intelligence?

Some influencers on Instagram and TikTok get a lot of mileage out of talking to ChatGPT's voice mode. It says and does ridiculous things and it openly lies. It's shocking. But - if you use voice mode, you are getting connected to the stupidest model available. Every time. The companies figure that you are more interested in getting a response that comes at conversation speed, when in voice mode, and they plug you into the stupidest motherfucker they have at the ready because it's the fastest.

Many of these questions also take advantage of AI's politeness - smuggling in an assumption that, if wrong, would make the user out to be a complete, utter moron. The AI answers assuming you are not a complete moron.

"My friend gave me this trick cup, where the top is sealed up, but the bottom is wide open. How do I drink from it?" AI voice mode neglected to realize that this was simply a normal cup, upside down - partially because of voice mode stupidity, and also because the alternative is telling you, the user, "of course it's just a normal upside-down cup you fucking dingus, what planet are you from?" I wonder, further, if the AI would make the same mistake if you removed the leading information that it was a 'trick' cup.

"The car wash is about a mile away. Should I drive or walk there?". Of course you need to drive, you walnut. How else are you going to clean your car? Well - I guess, maybe you forgot something at the car wash and need to get it. The user couldn't be that stupid, right?

Many leading or over-confusing questions that require actual common sense reasoning do not trip up AI anymore. If you see one of these viral reels, I encourage you to try with a text model. Even a free text model. Trick questions that require commonsense reasoning are quickly becoming a solved problem re the SimpleBench test: https://lmcouncil.ai/benchmarks and the Bullshit test: https://petergpt.github.io/bullshit-benchmark/viewer/index.v2.html?q=sw_nn_02&a=anthropic%2Fclaude-opus-4.6%40reasoning%3Dhigh&b=openai%2Fgpt-5.1-chat%40reasoning%3Ddefault

There's no reason, following the METR and MIT studies above, to think that these kinds of questions will be exempt from the growth patterns we've seen. That's not to mention that in typing to a text model, not once have I been able to replicate the AI's viral confusion - it only happened in voice mode.

If you take nothing else

If you take nothing else from this post, I want you to pick - right now - something that an AI could do that would impress you, and something that humans around the world do every day. Really. And watch to see if AI starts being able to do that. Would it be impressive for an AI to make a hundred million dollars? To solve a new math proof that no one has seen before? AI did that in October 2024 (Truth Terminal) and February 2026 (First Proof Problem), respectively. I saw a YouTube video - "Why AI is doomed to fail the music Turing test". It passed it a few months later. ( https://arxiv.org/abs/2509.25601 ) Surely, that's nonsense. The results of this paper - of a music Turing test - should only count if it is a performed with professional musicians having a musical education...? But ah, do you see how quickly the goalposts move?

For real, pick your benchmark - "If AI can do this, I'll start taking it seriously." - write it down on a sticky note, and keep it in mind. I hope that if the day comes and AI starts doing that thing, you'll join me.

Thank you

I bet most posts on this subreddit aren't often nearly as long as this one. You've been a real trooper reading through all this - maybe seething with annoyance at something I got wrong, maybe nodding your head in agreement, maybe having no reactions at all.

Boy, I've been enthusiastic about. If I turn out to be wrong in the coming decade - well, that'll be a huge egg on my face.

With all that, I'll take your questions. This is a fascinating topic, and I clearly have a lot of opinions. I'm enthusiastic to hear where you think I've gone wrong.