this post was submitted on 11 Aug 2026
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Disagree.
It is true there were massive strides in the last 8 years. But fundamentally, the tech is still the same large language model it was before, just bigger and better optimized.
It's like going from an ancient, slow, Ford Model T that topped out at 45mph to a Bugatti that can do 260mph in 8 short years. It's impressive, it boosts productivity, it is a marvel of modern technology, but that's not my point of contention.
The issue is that AI companies have been funded on the promise that with enough advancements and upgrades this tech will achieve AGI. Which is an absurd statement to anyone in the field actually developing these things. That is the equivalent of promising that this 260mph Bugatti, with a few years of upgrades and advancements, will become a Harrier Jump Jet!
It's just not happening, a fundamental shift in model architecture or technology used is needed. And from what we've seen so far, no one has discovered any.
They're not even better optimized. Hallucination rates are up. Inference costs are up. There's only an AI industry at all because they're selling a highly subsidized product, but when they try to raise prices even a little the market collapses. Companies that were encouraging employees to up their AI use are now rationing tokens like chocolate in wartime. This isn't like Uber where they can push out the old providers and then obtain market capture on something everyone needs. AI is not, and cannot be, essential, because you can always just get a human to do it.
A better analogy is promising that a toddler will, with enough knowledge and training, eventually become a heart surgeon.
15 years ago the assumption with AGI was that we needed some paradigm shift in technology to create it, but after transformer technology was invented (the T in GPT), and it was trained on a lot of information, we discovered an emergent property that it could take natural language queries and answer them with its knowledge base-- which was unexpected and unintended.
While science can always end up going down the wrong path, the current mainstream stance is that we were wrong about needing new technology for AGI; it seems that AGI may be a function of information and training, on hardware we already have. Hence all the data centers being built.
Anyone who says with certainty that it will result in AGI is just as wrong as someone who says with certainty that it won't.
We have math PHDs with proofs current LLMs can't become AGI, because they'll always have a context issue
I would love it if you'd point me at these mathematical proofs.
You genuinely believe that the people in frontier labs under such severe NDAs we've had articles about how unusual they are believe it's absurd to think that what they're working on could lead to "AGI"?
What would the goal of that be in your mind? Getting as much investment as humanly possible before everyone figures out the leading specialists have been being paid insane amounts of money just to act like what they're doing matters and the valuations all plummet to nothing over night? Why?
With all the money poured in to this from all the sources it's coming from that would end in a lot of the most powerful companies, government bodies, and individuals in the world extremely unhappy and blaming the people running those frontier labs.
Getting a lot of news and attention and then saying "psych, lol" and being imprisoned for life or murdered doesn't seem like a great long term plan.
Exactly this, especially the last sentence.
I only have pretty basic machine learning knowledge, based on a few Master's classes at college while I was doing gamedev, and even with that I can tell that the way they are expecting to get AGI by just feeding more data into a language model is simply not happening.
I remember a comparison from one of the AI-pilled tech-bros when AI was starting to get attention, and his metaphor about AGI was something along the lines of "Imagine a difference between a medieval commoner and Albert Einstein, that's the difference in inteligence AI will soon have to the smartest people we know now".
But that doesn't make sense with the current approach. Imagine Einstein writing his cutting-edge theories, and the commoner is watching him behind his shoulder and vetting anything he does. Scratching his ideas, forcing him to redo it, if he doesn't like it, pointing to a reddit thread about why. There's no way he would ever finish anything new.
Unless they figure out a completely new way how to do AI reasoning, there is no way we're getting anywhere near AGI. And that is also becoming more unlikely the longer we go with this approach, because every AI-pilled company is heavily outsourcing all of development to the current models, reducing their employee (and the whole worlds) innovation potential and skill. This is probably the last generation that can do serious academia, unless there are drastic measures done to limit access to AI in education. It's fucked.