Regarding latency.. https://www.cerebras.ai/blog/cerebras-kimi-k2-Enterprise
-----Original Message----- From: Friam <[email protected]> On Behalf Of glen Sent: Thursday, May 21, 2026 9:13 AM To: [email protected] Subject: Re: [FRIAM] More meat for the metavores Depending on what you mean by "this", I guess. I totally agree that LLMs "reason" ... and it's a bit reactionary to claim they don't. But my problem is with words like "learn", "train", "inference", "deep", etc. I forget which talking head said it, but they said something like "I'm not one to change my mind." LoL Do they even hear their self when they talk? Changing one's mind is *the* hallmark of intelligence. Defeasible reasoning is the only sign there's anybody in there. But, of course, there are those amongst us who do all their mind-evolution almost entirely alone ... like some schizophrenic wunderkind, deep learning from all their hallucinated voices. I'm told David Lewis (ala possible worlds) was like this ... speaking in fully formed worldclosureruntimes. But for the rest of us, more than half of what we know is only available through the APIs of the deeply interactive objects we have strewn about us. So even if I don't have a nickname for all the other nuanced concepts, I need some for "changing one's mind" versus "arbitrary pontification from which nobody learns". On 5/21/26 8:28 AM, Marcus Daniels wrote: > I don't understand why this continues to be a concern. It is only of > academic interest, it seems to me, to wonder how good native LLM reasoning is. > Yes, there is a small cost to dispatch from the LLM for MCP. Tokens need to > be generated, and tokens need to be absorbed. But for anything that is deep > reasoning it is a vanishingly small overhead. It is exactly what > computational scientists would do too. They'd reach for their Matlab or at > least a chalkboard. Let the LLM write the Lean 4, the Answer Set > Programming, the Mathematica, the Matlab, the Magma, whatever. If they do a > bad job, there will be correction cycles, if they do a good job, there won't. > But frontier models are good coders now. > > -----Original Message----- > From: Friam <[email protected]> On Behalf Of glen > Sent: Thursday, May 21, 2026 8:13 AM > To: [email protected] > Subject: Re: [FRIAM] More meat for the metavores > > What is "reasoning" if not a sequence of tokens, the latter depending on the > former in some way? I'd like to offer up 3 links that might help us > understand where the "reasoning" of LLMs is only kindasorta reasoning: > > • https://logicalintelligence.com/kona-ebms-energy-based-models > • https://github.com/SkyworkAI/Matrix-Game/tree/main/Matrix-Game-2 > • https://github.com/facebookresearch/vjepa2 > > The 1st one isn't quite like the other 2. But it's in the same vein, I think. > There's some kind of something to be said about cumulative puzzles or > meta-games. But I don't know quite what I'm trying to say. Although I loathe > the term, Systemic Games > <https://the-artifice.com/systemic-games-philosophy/> comes to mind. > > Reasoning engines have (at least) 2 modes, maybe akin to Kahneman's systems > 1&2, where some input simply clicks or doesn't and is tossed away, but other > inputs *modify* the lattice ... change the game. I say "at least" because > there's a distinction between something like self-modifying code - where an > execution can modify, add, or delete axioms or even the language - and > "emergent play" where nothing fundamental changes, but one plays games atop > or within the base game. So I guess there are at least 3 modes. > > All 3 are appropriately called "reasoning". But along with the gist of > Hullman's post, failing to distinguish them is lazy. But we need generalized, > non-jargonal nicknames for them, otherwise every mention requires a detailed > glossary ... or perhaps an entire, pickled runtimeworldclosure, attached to > every message passed. > > On 5/14/26 8:54 PM, Roger Critchlow wrote: >> https://statmodeling.stat.columbia.edu/2026/05/14/as/ >> <https://statmodeling.stat.columbia.edu/2026/05/14/as/> >> >> "Previously it didn’t feel like such a crime to talk about intelligence or >> learning in machines because nothing really worked that well, so the labels >> were clearly aspirational. But now it’s much easier to believe the >> simulacra. And so it becomes harder to tell when we are using human-oriented >> terms as a predictive convenience versus a scientific claim versus a >> marketing device." >> >> >> "Too much casualness with words is unscientific. There was no good reason in >> the first place to call the token sequences a model produces when we ask it >> to “explain its reasoning” reasoning, other than that’s what we wish we >> could see." > > -- 8647 ⊥ ɐןןǝdoɹ ǝ uǝןƃ ὅτε oi μὲν ἄλλοι κύνες τοὺς ἐχϑροὺς δάκνουσιν, ἐγὰ δὲ τοὺς φίλους, ἵνα σώσω. .- .-.. .-.. / ..-. --- --- - . .-. ... / .- .-. . / .-- .-. --- -. --. / ... --- -- . / .- .-. . / ..- ... . ..-. ..- .-.. FRIAM Applied Complexity Group listserv Fridays 9a-12p Friday St. Johns Cafe / Thursdays 9a-12p Zoom https://bit.ly/virtualfriam to (un)subscribe http://redfish.com/mailman/listinfo/friam_redfish.com FRIAM-COMIC http://friam-comic.blogspot.com/ archives: 5/2017 thru present https://redfish.com/pipermail/friam_redfish.com/ 1/2003 thru 6/2021 http://friam.383.s1.nabble.com/ .- .-.. .-.. / ..-. --- --- - . .-. ... / .- .-. . / .-- .-. --- -. --. / ... --- -- . / .- .-. . / ..- ... . ..-. ..- .-.. 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