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  3. Researchers just mathematically proved that AI can't recursively self-improve its way to superintelligence.

Researchers just mathematically proved that AI can't recursively self-improve its way to superintelligence.

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machinelearningllmresearch
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  • devsimsek@universeodon.comD devsimsek@universeodon.com

    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/

    #AI #MachineLearning #LLM #Research

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    #86

    @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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    • devsimsek@universeodon.comD devsimsek@universeodon.com

      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/

      #AI #MachineLearning #LLM #Research

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      schrieb am zuletzt editiert von
      #87

      @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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      • ? Gast

        @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.

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        #88

        @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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        • devsimsek@universeodon.comD devsimsek@universeodon.com

          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/

          #AI #MachineLearning #LLM #Research

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          schrieb am zuletzt editiert von
          #89

          @devsimsek
          "Touch grass." It is not just a reminder to take a break or get some fresh air.

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          • ? Gast

            @troed @devsimsek

            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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            #90

            @resuna

            Everything in your post was wrong - so why did you post it?

            @devsimsek

            ? devsimsek@universeodon.comD 2 Antworten Letzte Antwort
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            • ? Gast

              @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.

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              #91

              @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

              ? 1 Antwort Letzte Antwort
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              • devsimsek@universeodon.comD devsimsek@universeodon.com

                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/

                #AI #MachineLearning #LLM #Research

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                schrieb am zuletzt editiert von
                #92

                @devsimsek

                So. That kind of "AI" - if not refused by us - shall vampirize humanity forever. It is build to suck our data forever. It is the perfect tool for control freaks. By design.

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                • devsimsek@universeodon.comD devsimsek@universeodon.com

                  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/

                  #AI #MachineLearning #LLM #Research

                  ? Offline
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                  schrieb am zuletzt editiert von
                  #93

                  @devsimsek It's logical really as AI simply doesn't have any intelligence. It only regurgitates what it has stolen and learnt.

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                  • ? Gast

                    @devsimsek Not a developer, but that was my first thought when I understood how LLMs were trained and how they worked: What happens when there's so much AI generated content on the internet that the LLM is harvesting and recycling its own output? That's like a high school history class having their own essays as research material. #LLMs

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                    #94

                    @anne_twain @devsimsek
                    This reminds me of some right-wing Youtube channels or Telegram groups. For years they're feasting on their own output and in the process are getting intellectually shallower but more agitated and radical...

                    ? 1 Antwort Letzte Antwort
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                    • devsimsek@universeodon.comD devsimsek@universeodon.com

                      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/

                      #AI #MachineLearning #LLM #Research

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                      schrieb am zuletzt editiert von
                      #95

                      @devsimsek the problem is: absolutely nothing you and I, all the world's scientists or anyone left with a sane mind says will stop the AI hype train because there's too much money in it already. 😒

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                      • ? Gast

                        @devsimsek Nobody ever claimed that llms get better by being trained on their own synthetic data. This blog post is very misleading.

                        The idea of self-improvement and singularity is that llms write improved versions of their own codebase and perform the research and experiments for coming up with better models themselves.
                        The idea of singularity is interesting but also full of hidden assumptions. I'm always confused when people act like singularity would exist. It's just science fiction.

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                        #96

                        @kaidu @devsimsek though wireless phones were seen as science fiction back in 1926... And considered laughably unreasonable. 🤔

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                        • devsimsek@universeodon.comD devsimsek@universeodon.com

                          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/

                          #AI #MachineLearning #LLM #Research

                          ? Offline
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                          schrieb am zuletzt editiert von
                          #97

                          @devsimsek

                          Interesting article about how AI cannot grow into a super intelligence because the more systems grow, the more they rely on information generated by themselves and the more ....

                          'it forgets what reality looks like'.

                          #AI #AGI #RSI
                          (RSI = Recursive Self-Improvement)
                          https://smsk.dev/2026/04/26/ai-cannot-self-improve-and-math-behind-proves-it/

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                          • ? Gast

                            @Quantensalat @devsimsek Yes.

                            They have also never had a machine crash because a recursive operation overran the stack or used up all the memory.

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                            #98

                            @drwho

                            You forgot the '/s' indicator 😉.

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                            • devsimsek@universeodon.comD devsimsek@universeodon.com

                              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/

                              #AI #MachineLearning #LLM #Research

                              ? Offline
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                              schrieb am zuletzt editiert von
                              #99

                              @devsimsek

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                              • ? Gast

                                @resuna

                                Everything in your post was wrong - so why did you post it?

                                @devsimsek

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                                #100

                                @troed @devsimsek

                                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".

                                ? 1 Antwort Letzte Antwort
                                0
                                • ? Gast

                                  @troed @devsimsek

                                  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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                                  schrieb am zuletzt editiert von
                                  #101

                                  @resuna

                                  How much have you studied human cognition - as well as the emergent effects shown by LLMs?

                                  I've studied both. So far I haven't come upon a single anti-AI fanatic that has any.

                                  @devsimsek

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                                  • ? Gast

                                    @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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                                    #102

                                    @Quantensalat @devsimsek oh gotcha, yes agreed.

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                                    • ? Gast

                                      @resuna

                                      Everything in your post was wrong - so why did you post it?

                                      @devsimsek

                                      devsimsek@universeodon.comD This user is from outside of this forum
                                      devsimsek@universeodon.comD This user is from outside of this forum
                                      devsimsek@universeodon.com
                                      schrieb am zuletzt editiert von
                                      #103

                                      @troed Just to make you angry.

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                                      • ? Gast

                                        @devsimsek I'd be interested to see the same analysis of human consciousness. It is well understood that complexity is a regime on the absolute edge of chaos.

                                        devsimsek@universeodon.comD This user is from outside of this forum
                                        devsimsek@universeodon.comD This user is from outside of this forum
                                        devsimsek@universeodon.com
                                        schrieb am zuletzt editiert von
                                        #104

                                        @onekind I would be interested in this as well.

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                                        • ? Gast

                                          @Quantensalat @devsimsek For something more formal on this subject see

                                          https://arxiv.org/abs/2601.03220

                                          The abstract starts "Can we learn more from data than existed in the generating process itself?"

                                          devsimsek@universeodon.comD This user is from outside of this forum
                                          devsimsek@universeodon.comD This user is from outside of this forum
                                          devsimsek@universeodon.com
                                          schrieb am zuletzt editiert von
                                          #105

                                          @dpiponi @Quantensalat Thanks, will check.

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