We don’t make space for flat-Earthers. We also do not make space for people who argue (explicitly or implicitly) that some of our students deserve to be murdered.
The reasons for those two things are not identical — the latter also has to do, for example, with the fact that education requires physical safety — but they rest on a shared principle: free speech means freedom to ignore speech, and freedom to choose which speech we amplify and how. Making such choices is, in fact, the •duty• of upholding free speech.
/end
Movie Magick
We have one mission with this podcast - To bring the joy of movies to as many people as possible, and create a space for all people and opinions to be shared and heard...
Great Australian Pods Podcast Directory: https://www.greataustralianpods.com/talking-flicks/
Will any of this actually happen? Let alone by the times written into this picture shared today? Whatever, the long press release #NASA tries to be heading now ...
I don’t know the individuals involved in this particular conference. What I do know is that there are people worldwide — including but not limited to a great many Jewish people — who have been working with all their might •not• to deny the trauma of others, to work toward true justice and peace. And I know that denying them space for their voices to be heard is a core part of how Netanyahu’s horrible war has been propped up for so long. Recognizing how multiple shared historical traumas shape present conflict seems to me like a good and essential first step.
Integrative neurocybernetic modeling in the era of large-scale neuroscience
Il Memming Park, Ayesha Vermani, Gonzalo G. de Polavieja, Juan \'Alvaro Gallego, Kathleen Esfahany, Shreya Saxena, Michael Orger, Auke Ijspeert, Matthew Dowling, Daniel McNamee, Srinivas C. Turaga, Zachary Mainen, Joseph J. Paton, Alfonso Renart
https://arxiv.org/abs/2604.23903 https://arxiv.org/pdf/2604.23903 https://arxiv.org/html/2604.23903
arXiv:2604.23903v1 Announce Type: new
Abstract: Large-scale neuroscience is generating rich datasets across animals, brain areas and behavioral contexts, yet our modeling efforts remains fragmented across isolated experiments. We argue that understanding behavior requires integrative neurocybernetic models: understandable dynamical models that capture the closed-loop coupling of brain, body and environment, treat the brain as a controller pursuing latent objectives, represent structured variation across scales, and scale to heterogeneous datasets. Such models shift the goal from predicting neural recordings in isolation to inferring the organizing principles that govern neural and behavioral dynamics. We outline a practical route toward this goal by combining nonlinear state-space models and meta-dynamical extensions with scalable inference, knowledge distillation, mixed open- and closed-loop training, and connectomics-informed architectures. By pooling complementary constraints from recordings, behavior, perturbations and anatomy, integrative neurocybernetic models can provide statistical amplification, few-shot generalization, and mechanistic insight into shared dynamical structure, individual variation, and the control objectives that govern behavior. This agenda offers a model-centric path from fragmented data to a mechanistic science of how brains produce behavior.
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