Jan Bauer

PhD student at @GatsbyUCL and @ELSCbrain. Studying the mechanisms behind of intelligence 🧠🤖

[Jan Bauer @japhba]

@tkipf Got mine to London at the beginning of this week, perhaps it's worth reaching out again...

[Thomas Kipf @tkipf]

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.

[Misha Teplitskiy | Science of Science @MishaTeplitskiy]

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
https://t.co/EzQL7WI71Q

[Kording Lab 🦖 @KordingLab]

We often discuss if the brain does something like gradient descent. Here is me discussing the issue for @OpenNeuroMorph. I focus on exposing the weaknesses of the hypothesis as well. Should be particularly useful for newly interested people. https://t.co/pCaBdmQLKI

[Prof. Karl Lauterbach @Karl_Lauterbach]

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

[Peyman Milanfar @docmilanfar]

never seen a graphic so wrong, but so useful

[Randall Munroe @xkcd]

Outdated Periodic Table https://t.co/MvlGGo3dG0

[Andrej Karpathy @karpathy]

@gdb 💯 reminds me of MAML meta-learning (https://t.co/H9CIfVdxHd) 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.

[English Grammar @GrammarUpdates]

Did you know? Grammar Checker: https://t.co/Hdx6C5fjdS

[Jan Bauer @japhba]

@AlexanderDerve @GaryMarcus @MetaAI @ylecun Seems like people were expecting to handle a nail with a screwdriver. Let alone the ability to run your work through the model to include missing references seems valuable.