Blake Richards

A tale of the need for flexible cognition... 😂

AGI is just astrology for smart computer boys

PSA to academics posting threads about your paper here: you can (and should) post the link to the paper in the first post. Your X/Twitter brain rot have have you thinking otherwise, but please free yourself of that. (Also you can call them 'blue-prints' if you want).

Big +1 to this! The current strategy of always mixing them is sub-optimal - for both research and education.

I think almost all scientific projects should be planned carefully. And I think an app can dramatically improve that. So I wrote an app for that (free for now, if you can fund this let me know). I tested it quite a bit (>8000 users in beta so far). try it: planyourscience.com

Y'all should just do like we do in Canada and move Thanksgiving to early October!

my little take on whole-brain neurophysiology and what it tells us about global coordination of neural activity on behavioural timescales

(I steered clear of tasteless analogies for this one...)

authors.elsevier.com/a/1m7H5_LsQS...

We went back to the drawing board to think about what information is available to the visual system upon which it could build scene representations.

The outcome: a self-supervised training objective based on active vision that beats the SOTA on NSD representational alignment. 👇

Putting the figures at the end of your preprint is one thing, but separating the CAPTIONS from the figures (with both at the end of the paper) is just plain cruel

Congratulations @sueyeonchung.bsky.social !

South Korean decision to close all coal-fired power plants by 2040 sounds alarm for Australian exports Decision announced at Cop30 climate conference signposts risks for Australia’s reliance on fossil fuel exports, analysts say

Coal isn't cost-effective anymore, and countries recognize it. Huge, since South Korea has been relying on coal for ~30% of their electricity.

www.theguardian.com/environment/...

I don't know much about Schmitt's theories... But my wife and I have long discussed how the current incarnation of left-wing politics resembles Nietzsche's slave morality. There is definitely an undercurrent of thought which posits, essentially, that to be oppressed is to be virtuous.

This is an excellent blueprint on a very fascinating use of AI scientist! And the results and super cool and interesting! 🤩
I have been asked this when talking about our work on using powerlaws to study representation quality in deep neural networks, glad to have a more concrete answer now! 😃

Characterizing neuronal population geometry with AI equation discovery The visual cortex contains millions of neurons, whose combined activity forms a population code representing visual stimuli. There is, however, a discrepancy between our understanding of this code at ...

1. New preprint resolving a conundrum in systems neuroscience with an AI scientist, and humans Reilly Tilbury, Dabin Kwon, @haydari.bsky.social, @jacobmratliff.bsky.social, @bio-emergent.bsky.social, @carandinilab.net, @kevinjmiller.bsky.social, @neurokim.bsky.social
www.biorxiv.org/content/10.1...

WeatherNext 2: Our most advanced weather forecasting model The new AI model delivers more efficient, more accurate and higher-resolution global weather predictions.

GDM WeatherNext 2

8x faster than v1, it can compute extreme situations and game out scenarios in one minute flat on a single TPU (as opposed to hours of supercomputer time for traditional algorithms)

will be available in all of Google’s weather apps

blog.google/technology/g...

But, does that require the data to be opened? Is it just scraping it from the figures?

I largely agree with this, with one caveat:

Algorithms/AI *are* a key barrier to progress in neuro-engineering and neuro-tech.

But, for actually *understanding* the brain, indeed, our major barrier is the inability to measure the things we could use to test our computational theories.

It is actually an incredibly frustrating time to be a theoretical neuroscientist right now imo, for this reason

Can’t argue with that.

In non-white-collar jobs, it will usually be something physically repetitive (see factory automation).

Note: to support my claim here, if AI could do your dishes, I am 100% sure you would be using it for that purpose!

When do I not want to do a task?

Answer: when I feel my input on the task serves no real purpose, because it doesn’t require my expertise or insights. Though not exactly the same, this will more often than not be a brainless exercise.

In white collar jobs, that’s usually something bureaucratic.

Yeah, and I suppose as an add-on: I want publishing something more like a poster to be sufficient from a career development perspective.

In principle, though, all this can really do is uncover patterns that exist across multiple papers, right? Or is there something more to the system than I’m clocking…

I’m genuinely curious about this. The numbers in the blog are quite impressive.

Has anyone tried it and would like to share their $200 experience?

YouTube video by dotconferences Clean code in Data Science - Gael Varoquaux - Skrub DataOps, Probabl:

@skrub-data.bsky.social: better data-science primitives for clean code on dataframes

Watch my dotAI talk, it's fun (live coding)!
www.youtube.com/watch?v=bQS4...
skrub really makes it easy to do machine learning with dataframes

lol... so you say! Hot take Blake remains unconvinced...

I think academics spend too much time writing and not enough time thinking/doing.

Ah, but this gets to the rub of it:

Should be "arguing a case"?

Part of what I'm getting at is precisely that a lot of papers have weak data, but lots of well-crafted prose, to make some case.

I'm not sure that's always beneficial. Maybe that should be reserved for perspective articles, in fact.

Large-language models are bureaucracy flashlights.

Sometimes... I wouldn't want all papers to be bullet point format. But, I think some papers would actually be more effective if they were.

I would argue that good bullet points have clear flow!