Paul Linton

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Paul Linton

Paul Linton

@LintonVision

Visual Experience / NOMIS Fellow @ItalianAcademy / Presidential Scholar @columbiacss / @KriegeskorteLab + @ZuckermanBrain / AVA David Marr Medal 2025

New York, NY เข้าร่วม Aralık 2017
1.4K กำลังติดตาม1.4K ผู้ติดตาม
Paul Linton
Paul Linton@LintonVision·
@andpru @ZuckermanBrain Thanks Andrew. Unfortunately not, but I think this requires Roland to give the talk (at least virtually) at Western as well!
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Paul Linton
Paul Linton@LintonVision·
Absolutely wonderful talk by Roland Fleming on “Grasping: measuring and modeling how we use our hands to pick things up” at @ZuckermanBrain
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Akiyoshi Kitaoka
Akiyoshi Kitaoka@AkiyoshiKitaoka·
Anstis先生キタ―――(゚∀゚)―――― !!
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Paul Linton
Paul Linton@LintonVision·
@guido_maiello So sorry to hear Guido, sending lots of love to you and Sara ❤️
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Guido Maiello
Guido Maiello@guido_maiello·
Dear friends, we have some difficult news. Sara’s cancer has progressed despite treatment, and we’re moving to palliative care. Thank you for standing with us through this. We love you.
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Jascha Achterberg
Jascha Achterberg@achterbrain·
Super excited that @jeremyakahn from @FortuneMagazine sat down with @DanAkarca and me to discuss our vision for how @CallosumAI can transform how we build intelligent systems across algorithms and hardware through co-evolution of the entire system level architecture!
Jeremy Kahn@jeremyakahn

Exclusive: Callosum, a startup founded by two Cambridge-trained neuroscientists who are looking to break Nvidia's stranglehold on AI workloads, has raised $10.25 million in VC funding. Its system optimizes AI tasks across different types of chips. fortune.com/2026/02/26/sta…

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tyler bonnen
tyler bonnen@tylerraye·
excited to share some recent work! tldr; models trained on multi-view sensory data are the first to match human-level 3D shape perception—all zero shot, with no training on experimental data/images project page: tzler.github.io/human_multiview 1/🧠
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Zhuofan Josh Ying
Zhuofan Josh Ying@zfjoshying·
🔍Truthfulness probes and their causal effects vary widely: some generalize, others are domain-dependent. Why? We propose Truthfulness Spectrum Hypothesis: truth directions of varying generality coexist! Probe geometry predicts generalization, and post-training reshapes it! 🧵⬇️
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Hokin Deng
Hokin Deng@DengHokin·
#VideoReason We are open-sourcing the entire VBVR stack to speed-up the arrival of video reasoning as the next fundamental paradigm of intelligence - 150+ synthetic generators - 1 million training clips - Cloud-scale data factory - Unified EvalKit - 100 rule-based evaluators - Strong baseline model Checkout at video-reason.com
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Seth Lazar
Seth Lazar@sethlazar·
One of the things I loved about Oxford as an undergraduate was just this feeling, that the tutors were never there to provide answers, but to challenge you to think more deeply about what were the right questions. I think in my entire degree I never wrote an essay to a prompt, but always followed my nose (including doing some digital humanities work [in 2001-2] almost before it was technically feasible to do so... AI would have been useful for *that*). I attended three lectures total; I didn't even have my allotted weekly meetings with tutors. I'd disappear for a couple of weeks, resurface with a paper, and talk about it for a couple of hours with a world-famous expert in the field. It was such a blast. The temptation to outsource one's thinking and to treat university as an answer machine, is a real challenge for us, now. But in another sense I think the challenge will be quite surmountable, and it points to the enduring value that universities can provide. It's surely clear to any motivated student, now, that allowing AI to write your outputs deprives you of almost everything that matters. There can *definitely* be ways in which AI can help as a research tool, and as an interlocutor, but writing is where you really wrestle with the problem, where you discover (especially in philosophy) the hidden premises in your half-articulated thoughts, which now require defence. If I'd done that as an undegrad, the tutorial would have been a walk of shame (and if my tutor outsourced grading to the AI, they'd have been equally embarrassed—though some had a higher toleration for that than others...) More generally, the central challenge that we're seeing with the ability to get AI agents to produce research outputs of many different kinds is that there's no plug in the back of our heads that allows us to just do a Neo in 'The Matrix' and instantly cognise all that information and analysis that has been generated. In 'Accelerando' the protagonist can fork his identity into an AI agent, send it off to do something, and then merge the branch back in with his principal cognition. But that isn't possible for us (whether it would be a good thing if it ever was is an interesting question). If you're in a domain where all you care about is the product (some forms of software writing, for example), then that might be fine. But anybody who wants to be a thinker is going to know that that isn't something that can be outsourced. And there will always be people who want to be thinkers (after all, Aristotle wasn't completely off the mark when he described it as one of the central elements in the good life). And society will continue to need institutions whose primary function is to teach young people how to think.
Brendan McCord 🏛️ x 🤖@Brendan_McCord

Every polished essay that arrives without a trace of struggle feels like an epitaph: Did anyone ever think here? My reflections in @FinancialTimes

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Kording Lab 🦖
Kording Lab 🦖@KordingLab·
Psychophysics to understand the visual cortex: frontiersin.org/journals/syste… - another paper by a great group from Tehran whose webpage is gone now.
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