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tims457

129 karmajoined 5 tahun yang lalu
https://tims457.github.io/ https://twitter.com/tims457

Submissions

Yi Ma – Pursuing the Nature of Intelligence

youtube.com
1 points·by tims457·3 hari yang lalu·0 comments

NeuroMechFly v2: simulating embodied sensorimotor control in adult Drosophila

nature.com
2 points·by tims457·4 bulan yang lalu·1 comments

Neural Algorithmic Reasoning

algo-reasoning.github.io
3 points·by tims457·tahun lalu·0 comments

Ask HN: Alternative to Causal for probabilistic spreadsheet models

2 points·by tims457·2 tahun yang lalu·1 comments

The Thinking Game

tribecafilm.com
1 points·by tims457·2 tahun yang lalu·0 comments

[untitled]

1 points·by tims457·2 tahun yang lalu·0 comments

Friends from the Old Neighborhood Turn Rivals in Big Tech's A.I. Race

nytimes.com
2 points·by tims457·2 tahun yang lalu·0 comments

CS224W: Machine Learning with Graphs – Notes

snap-stanford.github.io
3 points·by tims457·2 tahun yang lalu·0 comments

Graph Convolutional Networks

tkipf.github.io
3 points·by tims457·2 tahun yang lalu·0 comments

Collective intelligence for deep learning: A survey of recent developments

journals.sagepub.com
2 points·by tims457·2 tahun yang lalu·0 comments

Ask HN: What are the best resources you've found on improving your writing?

1 points·by tims457·3 tahun yang lalu·1 comments

comments

tims457
·4 bulan yang lalu·discuss
https://www.biorxiv.org/content/10.1101/2023.09.18.556649v4
tims457
·3 tahun yang lalu·discuss
No transparency here. What is it considering to come up with these scores? Are they prioritizing growth, value, financial health, or something else?
tims457
·3 tahun yang lalu·discuss
Haven't read the paper yet, but it's clear that the brain is much more sample efficient than artificial neural networks. We should be spending more time on figuring out why than scaling up LLMs.
tims457
·3 tahun yang lalu·discuss
I'm risking just posting another process that you might have seen, but I thought it was helpful. Maybe you or someone else will too.

Farnam Street annual review https://fs.blog/annual-review/ (Direct link without giving your email: https://fsmisc.s3.ca-central-1.amazonaws.com/2022+AR.pdf)