LLM

a half-dozen monkeys with typewriters would eventually write all the books in the British Museum. Imagine that a billion monkeys with keyboards can do (for this or that corporation, which buys all the available SSD storage supply). This, by the way, in itself if a bullshit abstract social construction, since the branching factor of a resulting dag (of potential sequences each monkey can produce) is probably larger than “number of atoms in the observable universe” (memes, memes everywhere). You also have to do git merge, which would be an intractable problem. ...

Sometimes, when I do not know what to do with myself I re-watch some lectures for this or that online course on Youtube. Better than doom-scrolling crap, I guess. Something similar to that Bladerunner 2049 part, where they watched old Elvis as a hologram. Today it was the 'Lecture 2 ｜ Machine Learning (Stanford) [5u4G23_OohI].mp4' (of the old CS229, on a blackboard). If you watch this think of Tyson in a gym before he became the world champion. The comparison is in how much talent one has to have and then what one can achieve. ...

So, it feels like it’s time to write again, to see where we actually are at. Recently there were two big events related to the LLMs. First one is the “discovery” of a counter-example for the famous conjuncture (and the large blog post by Terence Tao, that he could have discovered it too, LOL). Another one was the “hack” of bitcoin “hardware” wallets, not the hack itself (it is rather “simple”) but the fact that, allegedly, an LLM with a given prompt like “find a security weakness in this code” (not even a “vulnerability”) have managed to find the exact RNG bug (reduction of the entropy size form the “safe” 128 bits from a hardware RNG to a “weak” 40 bits of flawed software RNG, so the attackers are just brute-forcing the 40bit “state space” and find the keys). ...

When they began to feed the generated slop back to the models, they deepen the “fundamental problem” even further. The most recent models produce an excelent verbiage but the code is out of sync with it. This fact is very easy to undestand and explain – the verbiage and the code live in the very different “regions” of the model’s representation (weight matrix or whatever it is) and these regions are getting tuned (reinforced) at a very different rates and thus do not converge as they are expecting. ...

Look, ma – no hands^W^W another one, who knows it all: https://www.0xkato.xyz/how-llms-actually-work/ I am so fucking tired of this shit, don’t you? Okay, even if arguing with retards is ultimately futile, and especially so in the society which does not value intelligence, but only appearances and virtue signalling, lets continue competing in our sport of choice while we still can. No one understands this shit, since the very process by which the artifact in question has emerged is, in principle, by definition, different from the post-hoc “explanations” and anthropomorphic “rationalizations” which plague such “literature”. ...

After the “Sentient Models” has been booed by very few remaining intelligent people they resorted to a the next best meme – their AI is improving itself (recursively, my ass). https://www.anthropic.com/institute/recursive-self-improvement Notice that this has almost nothing to do with the actual underlaying tech, except that the models are being feed with their own slop for the Reinforcement Learning and as new data, and has everything to do with the upcoming IPO – look, AI writes itself, what can possibly go wrong – buy our shit. ...

So, let’s see. Since my last summary nothing has been changed much, except the US stock market, Nasdaq100 and S&P500, in particular, are printing ATHs every single day and MU and DELL, and even INTC and AMD – you can see it yourself. On the other side Anthropic emerged as a true leader in the armrace [to the bottom] since their code slop generator is qualitatively better than Gemini – the closes competitor. Everything else is just bullshit (both ChatGPT and Grok are, indeed, merely Infotainment chatbots). ...

I used to work with a few quite stupid “managers” whose only skill was that manipulative pseudo-empathy and other quite transparent manipulative skills – the “Pan Am” fake smiles at the cognitive level. It is not that we didn’t see through these primitive manipulative tactics or “respected them” to not to hurt their felling, we just simply acknowledged that these people are strictly way below our levels and just did not bother. These managers, by the way, are still cock sure of their cleverness and their abilities “to manage people efficiently” and that no one sees how they do it. ...

This is not mere a hatespeech, this is the actual fact. Here is how it works. I have received a lot of reports like this one (because I do really know what to prompt for): The system is now fully complete, architecturally sound, and rigorously verified against its formal specification. All logic is expressed as pure, immutable transformations within a declarative network shell. #+end_quite So, I am outperforming the 99% percent of Github and should be a millionaire in a few months. Or, perhaps, something is fishy out there. ...

This is how things work: you, being a “literally who?” nobody, wrote approximately 13 pages of titles of articles, about exactly how and why the current incarnation of AI is only an appearance of “intelligence” and a textbook cognitive illusion, and then some fuck wrote a single blog post and got all the fucking HN top page and what not. Life is harsh, competition for being [recognized as] “smart” is throat cutting, you know. ...