Researchers just mathematically proved that AI can't recursively self-improve its way to superintelligence.
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Researchers just mathematically proved that AI can't recursively self-improve its way to superintelligence.
Not "we think it's unlikely." Not "it seems hard." Formally proved.
The model doesn't climb toward AGI — it slowly forgets what reality looks like. They call it model collapse. The math calls it inevitable.
I wrote about it
https://smsk.dev/2026/04/26/ai-cannot-self-improve-and-math-behind-proves-it/
@devsimsek This & overall the bigger issue of forced overinclusion & attempted hyperteliance on machine learning systems, mostly done by governments & their private partners, like autoshutoff on cars, chatbots as talk therapists& biometric ID/digital ID instead of regular ID card systems, is destined to fail.... It's not so much that activists will win in court or public protests on how these things at least mostly violate civil liberties & are based on data & intellectual property theft.... It's that fundamentally none of these systems actually work!
They couldn't even write a specific mechanism or method for the vehicle one because nothing fitting the mandate has been developed & the nearest ones obviously dont work.
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Researchers just mathematically proved that AI can't recursively self-improve its way to superintelligence.
Not "we think it's unlikely." Not "it seems hard." Formally proved.
The model doesn't climb toward AGI — it slowly forgets what reality looks like. They call it model collapse. The math calls it inevitable.
I wrote about ithttps://smsk.dev/2026/04/26/ai-cannot-self-improve-and-math-behind-proves-it/
@devsimsek you have an awkward sentence here you might want to know about: “Even though I like to say yes, i neither have the enough research nor I want to comment on it”
I think you’re going for something like “even though I’d like to say yes, I have neither enough research nor any desire to comment on it”… but I’m not entirely sure.
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@Quantensalat @musicman @devsimsek depends on what you mean by far fetched, certainly nothing as easy as "their more compute at it' which is what made this jump in investment so dramatic.
@wronglang @musicman @devsimsek No, agreed, more compute with the same type of model and the same training data sounds totally unplausible to me as a long term strategy
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Researchers just mathematically proved that AI can't recursively self-improve its way to superintelligence.
Not "we think it's unlikely." Not "it seems hard." Formally proved.
The model doesn't climb toward AGI — it slowly forgets what reality looks like. They call it model collapse. The math calls it inevitable.
I wrote about ithttps://smsk.dev/2026/04/26/ai-cannot-self-improve-and-math-behind-proves-it/
@devsimsek
"Touch grass." It is not just a reminder to take a break or get some fresh air. -
Large language models are fundamentally different from mammals on every level. They do not build models or reason about them. A rat is more "intelligent".
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@Quantensalat @devsimsek the main issue is that unless you maintain an external signal (so human input in the form of token sequences that are actually carefully curated for coherence) the models become more and more incoherent. Sounds like you're on board with that. The next step is that we're quickly devaluing money spent on human creativity and the world is awash in LLM garbage. So the human signal *is* disappearing.
@wronglang @devsimsek Yes, sure. I mean I can imagine it improving somewhat still, like when you augment your training set for image recognition by adding noise to a smaller set, but only to a point before it goes downhill from feedback.
No, my gut feeling is rather that there have to be much more effective ways to train a model than to brute force funnel billions of pages of text to a transformer which blindly fits relations between words and structures without understanding them, that seems like doing it the hard way, even if I'm not expert enough to tell you what an alternative would look like
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T tokeriis@helvede.net shared this topic
