Tootfinder

So arguably the Pac-Man ghost logic is the exact opposite of “AI”.
It’s extremely well defined behavior based on very basic deterministic algorithms that are so simple a 8-year old player can understand them and anticipate them correctly for those high-scores.
The game actually is famous for the simple enemy logic and studied by games designers for it.
Pac-Man enemy behavior:
deterministic, well-defined algorithm that can easily be executed on the most primitive* computer hardware
“AI”:
black-box algorithm with indeterministic behavior that requires a metric shitload of compute
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*By “primitive computer hardware” I mean that the Pac-Man arcade machine runs on a Zilog Z80 CPU with 8,500 transistors.The CPU in the phone you are reading this on has (latest iPhone as example) 15 billion transistors or so (almost 2 million times more) and runs tens of thousands of times faster.

Smooth Trade-off for Tensor PCA via Sharp Bounds for Kikuchi Matrices
Pravesh K. Kothari, Jeff Xu
https://arxiv.org/abs/2510.03061 https://arxiv.org/pdf/25…

Smooth Trade-off for Tensor PCA via Sharp Bounds for Kikuchi Matrices
In this work, we revisit algorithms for Tensor PCA: given an order-$r$ tensor of the form $T = G+λ\cdot v^{\otimes r}$ where $G$ is a random symmetric Gaussian tensor with unit variance entries and $v$ is an unknown boolean vector in $\{\pm 1\}^n$, what's the minimum $λ$ at which one can distinguish $T$ from a random Gaussian tensor and more generally, recover $v$? As a result of a long line of work, we know that for any $\ell \in \N$, there is a $n^{O(\ell)}$ time algorithm that succeeds whe…