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Dan Levenstein @dlevenstein.bsky.social · 56m

Language is a great example - not necessary for intelligence to emerge, but might be enough to bootstrap. Once you’re using language data you’re not building intelligence de novo.

I’d bet social interactions are the opposite - you need them for intelligence to emerge but not to bootstrap.

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Dan Levenstein @dlevenstein.bsky.social · 56m

Always find it an interesting question which ingredients are necessary for intelligence to emerge from scratch vs which are necessary if you only want to bootstrap from an existing intelligent system…

Ricard Solé @ricardsole.bsky.social · 1h

Moreover, AGI might also require social interactions to become a reality, where cultural evolution (and extended mind) play a major role. It is not by chance that brain and culture evolved together, allowing complex minds to emerge @anilseth.bsky.social @mitibennett.bsky.social

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Reposted by Dan Levenstein

Antonino Greco @agreco.bsky.social · 6h

here the trick is to unpack the word *understanding*

it’s not about what each neuron does, but the rules shaping the behaviour of biological systems!

"rules for development and learning in brains may be far easier to understand than their resulting properties"

👇👌
arxiv.org/abs/1907.06374

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Dan Levenstein @dlevenstein.bsky.social · 15h

It is possible that really appreciating this tweet requires having gone to college in the states around 2010 😅

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Dan Levenstein @dlevenstein.bsky.social · 15h

I’m at the restaurant and they’re playing my song and can you imagine anyone making a song right now called “Party in the USA”?

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Reposted by Dan Levenstein

Grace Lindsay @neurograce.bsky.social · 19h

That's what we're saying people should try to do here: www.sciencedirect.com/science/arti...

Testing methods of neural systems understanding

Neuroscientists apply a range of analysis tools to recorded neural activity in order to glean insights into how neural circuits drive behavior in orga…

www.sciencedirect.com

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Dan Levenstein @dlevenstein.bsky.social · 1d

Turns out @macshine.bsky.social scooped our title….

www.biorxiv.org/content/10.1...

Can Systems Neuroscientists Understand an Artificial Neural Network?

Network neuroscience has catalysed crucial insights into the systems-level organisation of the brain, however the lack of a ‘ground truth’ inherently limits direct interpretation. In parallel, deep le...

www.biorxiv.org

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Dan Levenstein @dlevenstein.bsky.social · 1d

The constraints and self-regulation are the special sauce. I like the point that understanding self-regulation could be a secret back door (“leverage”) to understanding computation (or maybe not needing to… 🥲)

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Dan Levenstein @dlevenstein.bsky.social · 1d

A human-comprehensible story about how the pattern of activations lead to a network’s competencies in real-world tasks, and how they come to do so with learning. Which we can back up with predictions and perturbations. TL;DR the dream of systems neuroscience.

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Dan Levenstein @dlevenstein.bsky.social · 1d

Because a deep RNN is a much simpler system than the brain, that also operates through the parallel/distributed activity of connected input/output units, where the efficacy of connections plays a key role in its operation. If we can’t understand that how can we hope to understand the brain?

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Dan Levenstein @dlevenstein.bsky.social · 1d

So I get that a Neuroscientist Couldn’t Understand a Microprocessor, and TBH I’m ok with that. But could a neuroscientist understand a deep RNN? Because that seems like a more pressing issue.

*assuming you think the brain operates through the parallel activity of many connected input/output units

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Reposted by Dan Levenstein

Shahab Bakhtiari @shahabbakht.bsky.social · 2d

Regardless of what explainability/mech interp in AI is actually after, and whether or not they know what they’re searching for, we can confidently say they’re pursuing what systems neuroscience has pursued for decades, with very similar puzzles and confusions.

Mel Andrews @bayesianboy.bsky.social · 2d

What problem is explainability/interpretability research trying to solve in ML, and do you have a favorite paper articulating what that problem is?

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Dan Levenstein @dlevenstein.bsky.social · 3d

And if you’re looking for a postdoc not a faculty position, we have those too 😉

Dan Levenstein @dlevenstein.bsky.social · 3d

Come do a postdoc at the Wu Tsai Institute!

WTI fellows have freedom to work with anyone at the institute, and preference is given to applicants who want to work on interdisciplinary projects with multiple faculty mentors.

If you’re interested to work with me, please reach out!

Wu Tsai Institute | Yale University @wutsaiyale.bsky.social · 4d

📣 Calling experimental, computational, or theoretical researchers!

WTI's Postdoc Fellowships application is now open, offering a competitive salary, structured mentorship, world-class facilities + more: wti.yale.edu/initiatives/...

Apply by November 10: apply.interfolio.com/174525

#KnowTogether

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Dan Levenstein @dlevenstein.bsky.social · 3d

Come do a postdoc at the Wu Tsai Institute!

WTI fellows have freedom to work with anyone at the institute, and preference is given to applicants who want to work on interdisciplinary projects with multiple faculty mentors.

If you’re interested to work with me, please reach out!

Wu Tsai Institute | Yale University @wutsaiyale.bsky.social · 4d

📣 Calling experimental, computational, or theoretical researchers!

WTI's Postdoc Fellowships application is now open, offering a competitive salary, structured mentorship, world-class facilities + more: wti.yale.edu/initiatives/...

Apply by November 10: apply.interfolio.com/174525

#KnowTogether

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Dan Levenstein @dlevenstein.bsky.social · 3d

The Wu Tsai Institute at Yale is hiring another faculty member in neurocomputation. Come work with us in a growing community at the interface of neuroscience and AI!

More info below 👇

Wu Tsai Institute | Yale University @wutsaiyale.bsky.social · 7d

📣 WTI is hiring faculty positions! Are you interested in advancing our understanding of the brain + how it gives rise to cognition?

Two calls are open:

Open-rank search, Neurocomputation, deadline: 12.1.25
Senior search, Neurodevelopment, rolling review

🔗 wti.yale.edu/opportunities

#KnowTogether

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Dan Levenstein @dlevenstein.bsky.social · 7d

Sounds like a…. bitter pill for them to swallow, eh? 😅🥁

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Dan Levenstein @dlevenstein.bsky.social · 7d

Kauffman Level 3 is when you get the superpowers 👍

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Dan Levenstein @dlevenstein.bsky.social · 8d

Ty! 🙏🙏🙏 We’ll have an updated preprint soon - with non-spatial representations (“splitter”, “lap”, etc cells), an orthogonalized manifold, spatial cell “type” quantification, and sparse-lognormal connectivity.

Also a package+tutorial so you can easily train sequential pRNNs in your own environment!

Reposted by Dan Levenstein

Ching-Lung Hsu @hiallen72.bsky.social · 9d

Beautiful work, as I'm thinking about the algorithmic functions of hippocampal theta!
doi.org/10.1101/2024...

Sequential predictive learning is a unifying theory for hippocampal representation and replay

The mammalian hippocampus contains a cognitive map that represents an animal’s position in the environment [1][1] and generates offline “replay” [2][2],[3][3] for the purposes of recall [4][4], planni...

doi.org

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Dan Levenstein @dlevenstein.bsky.social · 8d

📌 This feed to see what the people who like the same things you like like. 🫧

bsky.app/profile/spac...

spacecowboy @spacecowboy17.bsky.social · Aug 3

Welcome to the ✨For You✨ feed!

It finds people who liked the same posts as you, and shows you what else they've liked recently.

📌 Pin to add it to your top bar
❤️ Like the feed and repost to spread the goodness

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Dan Levenstein @dlevenstein.bsky.social · 8d

New feed based on your co-likers’ likes just dropped

bsky.app/profile/spac...

spacecowboy @spacecowboy17.bsky.social · Aug 3

Welcome to the ✨For You✨ feed!

It finds people who liked the same posts as you, and shows you what else they've liked recently.

📌 Pin to add it to your top bar
❤️ Like the feed and repost to spread the goodness

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Reposted by Dan Levenstein

spacecowboy @spacecowboy17.bsky.social · Aug 3

Welcome to the ✨For You✨ feed!

It finds people who liked the same posts as you, and shows you what else they've liked recently.

📌 Pin to add it to your top bar
❤️ Like the feed and repost to spread the goodness

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Reposted by Dan Levenstein

Shannon Vallor @shannonvallor.bsky.social · 8d

Since it resonated with the audience, I’ll recap my main argument against AGI here. ‘General intelligence’ is like phlogiston, or the aether. It’s an outmoded scientific concept that does not refer to anything real. Any explanatory work it did can be done better by a richer scientific frame. 1/3

Shannon Vallor @shannonvallor.bsky.social · 8d

This was a truly heartening day, with deeply thoughtful challenges to the dominant narrative framed around AGI, coming from across disciplines and perspectives. Felt like the tide might finally be turning a bit, at least among the scientific community. Thanks @royalsociety.org!

Anil Seth @anilseth.bsky.social · 10d

1/2 I'm looking forward to taking part in a panel on AGI and the Turing Test, tomorrow afternoon (Thurs 2nd Oct) at the @royalsociety.org, w/ Dame Wendy Hall, Shannon Vallor, William Isaac, & Sir Nigel Shadbolt. royalsociety.org/science-even...

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Reposted by Dan Levenstein

Shahab Bakhtiari @shahabbakht.bsky.social · 11d

On a broader note: Our ANN-based models should generate bold predictions with direct prescriptions for how to test them. This is how I believe #NeuroAI can avoid becoming an isolated, self-referential domain of neuroscience. This is the only way to flywheel NeuroAI into a theory of the brain (2/4)

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Dan Levenstein @dlevenstein.bsky.social · 12d

I liked it better when I thought it was Weird Al 🥲

Ken Chia, some guy online @kcchia80.bsky.social · 12d

All capital I's should have serifs to distinguish them from lowercase l's

Bill Grueskin @bgrueskin.bsky.social · 12d

To the Daily Beast staffer who put “79” into this headline, know this:

We salute you.

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