AI robotics startup Physical Intelligence claims vision-language-action models learn to align human videos and robot data as pre-training is scaled up (Physical Intelligence)
https://www.physicalintelligence.company/research/human_to_robot
“My oldest daughter had a lot of trauma as a child,” Andreatta said.
“Something really terrible happened to her when she was very young that I would hope never would happen to any other child.
And as a result of it, she's a lesbian.
She's gay, and she's married to a woman.
And sometimes that's a little bit of [an] internal struggle for me
because I believe that marriage is between a man and a woman.”
After the speech, Andreatta opened the …
With the emergence of more processors with 64 cores or more, I'm thinking more about whether it makes sense to implement a hypercube virtualised on a single chip with a single vector of memory, or as a literal hypercube of 64 (say) RP2350s. I understand the problems of transferring data across a hypercube, but I don't have a good feeling of how the bus contention on a multicore processor scales. What should I read?
Misplaced neurons reveal the brain's adaptability https://www.sflorg.com/2026/01/ns01162601.html Position-independent emergence of neocortical neuron molecular identity, connectivity and function
The emergence and proliferation of “influencers” reminds me of when the LaserWriter first appeared, and everybody went nuts with the fonts and formatting and printing all kinds of bullshit because now they could, cheaply, and then gradually it all died down and became just another useful tool, except the influencers are still shitting out their crap because they all see the few who are making bank at it and dream of being the next superstar. Humans are so fucking gullible. Oooh, shiny!
Drawing from a training with the Climate Psychology Alliance, I've been reflecting on the role of changemakers in our world.
Before, I saw activists as Sisyphus, straining to push the world uphill.
But what if we saw them as keeping the world steady?
https://www.brichapman.com/p/what-is-…
Had a lovely jam chat with Sarah Heneghan and Zebedee Budworth of Emergence Collective for this month's @… radio show on Resonance FM https://www.
Series C, Episode 13 - Terminal
ZEN: Emergence from matter belt in thirty-nine point zero one seconds.
TARRANT: Any damage yet?
ZEN: Hull sensors appear temporarily impaired. All other systems continue on full function.
https://blake.torpidity.net/m/313/139 B7B2
Emergence of Language in the Developing Brain
Linnea Evanson, Christine Bulteau, Mathilde Chipaux, Georg Dorfm\"uller, Sarah Ferrand-Sorbets, Emmanuel Raffo, Sarah Rosenberg, Pierre Bourdillon, Jean-R\'emi King
https://arxiv.org/abs/2512.05718
I’m reading Civilization Before Greece and Rome, by H. W. F. Saggs. Published in ‘89 so some interpretations are outdated, but a section on the emergence and rise of the god king in Mesopotamia for instance shows how the evangelical butt kissing of 🍊💩 and their efforts to sanctify him have been a part of human behavior for the past 5KY that we have written records of, and likely for a long while before that. Our constitution tries to buck the trend, but the odds for success look slim.
State and Parameter Estimation for a Neural Model of Local Field Potentials
Daniele Avitabile, Gabriel J. Lord, Khadija Meddouni
https://arxiv.org/abs/2512.07842 https://arxiv.org/pdf/2512.07842 https://arxiv.org/html/2512.07842
arXiv:2512.07842v1 Announce Type: new
Abstract: The study of cortical dynamics during different states such as decision making, sleep and movement, is an important topic in Neuroscience. Modelling efforts aim to relate the neural rhythms present in cortical recordings to the underlying dynamics responsible for their emergence. We present an effort to characterize the neural activity from the cortex of a mouse during natural sleep, captured through local field potential measurements. Our approach relies on using a discretized Wilson--Cowan Amari neural field model for neural activity, along with a data assimilation method that allows the Bayesian joint estimation of the state and parameters. We demonstrate the feasibility of our approach on synthetic measurements before applying it to a dataset available in literature. Our findings suggest the potential of our approach to characterize the stimulus received by the cortex from other brain regions, while simultaneously inferring a state that aligns with the observed signal.
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