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Published · transcript-backed

Michal Tesnar: belief

1 Jul 2026 Machine Learning Street Talk The Benchmark With No Instructions — ARC-AGI-3 (winning team!)

“I just only I think I can base my answer on the on these examples and I completely agree with you that these that there are some abstractions like that.”

— Michal Tesnar

Source trail

Everything needed to verify it.

Speaker
Michal Tesnar
Attribution
Verified speaker
Claim type
belief
Recorded
1 Jul 2026
Publisher
Machine Learning Street Talk

Transcript context

…enough. Yeah. I think gaming's a really good example. Mean, a good friend of mine is called DDK and he does commentary on Counter Strike and stuff like that. And it's when I when I watch him do commentary, seems super situational. So like in in Quake 3, you know, there there's you gotta time the the mega health and then there's the red armor and then there's a there's a position over here. And what you get is like the emergence of these complex situational phenomena in the game. And this is this doesn't seem anything like what Charley is talking about, you know, because there's 2 worlds, right? There's the sort of the emergent complexity world and then there's the the sort of reductionist, you know, kind of core knowledge world. I think in this world, we can still use intelligence and we can still like acquire abstractions and descriptions for these high level phenomena. But but what do we do? Do do we analogize them in terms of low level knowledge we already have? Or are they something new? It it seems like a different modality. No. I don't really have a good answer to that. I just only I think I can base my answer on the on these examples and I completely agree with you that these that there are some abstractions like that. But I I don't know. I don't know. Like, but you know, like Conway's Game of Life. Mhmm. It is still path dependent. Right? You can still trace a path from the low level description to the high level phenomena. But the reason it's it's unintelligible and it's surprising is because the path is a long 1 and it's computationally irreducible so you have to perform every single intermediate computation to get there. And we just, it's confusing for us because we can't actually analyse or understand the path between the causal stuff that made this high level phenomena. So we just kind of see it on its own, like disconnected.…

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