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Which systems come to mind when reading this? A lot seems to be vaguely familiar in terms of building complex software and testing…

Did you know? Grammar Checker: grammarcheck.net/editor/

Greg Brockman 💯 reminds me of MAML meta-learning (arxiv.org/abs/1703.03400) where the objective is to find weights of a network such that any new task finetunes fast. In Software 1.0 land, equivalent is writing code such that any new desired functionality is simple and doesn't need a refactor.

Outdated Periodic Table xkcd.com/2723

never seen a graphic so wrong, but so useful

Ich bin ⁦Rezo⁩ Fanbase. Heute gemeinsames Video gedreht. Die Antwort auf Philip A… Kommt bald.

We often discuss if the brain does something like gradient descent. Here is me discussing the issue for Open Neuromorphic. I focus on exposing the weaknesses of the hypothesis as well. Should be particularly useful for newly interested people. youtube.com/watch?v=E5hATe…

While remote, both science and hiking were very much on the edge! ⛰️

The longer people are in academia, the more they realize that when reading papers it's best to ignore Intro, Discussion etc. and just look at Methods and Results journals.plos.org/plosone/articl…

Couldn't agree more: we still don't have good solutions for scalable abstraction/concept learning from "raw" data (be it language, vision, or other sensory data). Solving this would likely unlock important new capabilities.

pip ⊂ conda ⊂ docker Choose the minimum feasible isolation, but no less (Lightweight but Brittle vs Involved but Stable).

"Even rocks, while not agents per se, track the state of their environment: the interior of a rock “knows” that the environment must be well below the melting point of rock. As systems become more elaborate, they can represent more about the things to which they couple."

Had a lot of fun thinking about the neural basis of cognitive flexibility with Alex, Kai, and Ali! Excited to see what other work bridging ML and Cognition will come out of the Analytical Connections summer school 🤖🧠