Aucun recoupement sur 24 h pleines : ni un lien ni un tweet n'est relayé par
deux membres (2 liens, 19 tweets relayés). Le recul est
suffisant, donc cette fois le constat porte : ces comptes diffusent au lieu de
converger, et c'est la composition de la liste qu'il faut revoir — pas la patience
qu'il faut allonger.
We’re presenting VisionSIM as a spotlight at @corl_conf #CoRL2026!
VisionSIM is a Blender-based multi-sensor simulator for RGB, thermal, event cameras & more—with realistic sensor effects and pixel-perfect ground truth.
Paper + code:
🧵 1/n
I had my second baby ~6 months ago 😊 missing CoRL to send time with my family 🫶🏻 but here's a quick look at our lab's recent work, an extended version of last week's BARS talk!
My students are all at CoRL, please say hi! Enjoy👢🦿:
Nice DeepSWE score! Does it survive a lowercase filename?
Introducing MaxxBench: 89 DeepSWE tasks with small changes to the instructions or starting code. Same engineering problem, slightly different requirement.
Models clustered around 74% on DeepSWE end up 23 pp apart.
Good
Evidently you can only choose 2: {correctly predicted where AI is now, has evidence-based opinions about where it goes next, knows anything about AI at all}
how come before every deadline I find myself begging for 80 GPUs on here? the GPU models change, but the count stays more or less the same.
so… anyone? 🥲
I am a professor at the @UofCalifornia. I am appalled by the conduct of one of its Regents, Scott Galloway, appointed in August by Governor Newsom.
@profgalloway is one of only 26 voting Regents entrusted with governing a university system serving hundreds of thousands of
Looking into the pension system of Sweden, in short, it penalize people who work hard. Say what you will about US, the 401K contribution is a great gift to working individuals. The financial freedom that country offered to its tax payers are unmatched.
We’re introducing Shizuku-Duplex, the world’s first full-duplex audio synthesis model built specifically for AI characters. See how our models are built for natural human-AI interaction:
Unfortunately most truly consequential projects require 10x this much money right out of the gate, preseed VC as presently structured is built to back incremental nibbling around the technoeconomic frontier
Capital access is better now than before, but still underinvested
Can't stop thinking how much stuff Jev is doing to save AI engineers asses from stupid systems design patterns while the rest of the domain keeps pushing tool calling loops everywhere
How the hell does Jev cost $0.00 after using more than 1M tokens (on my new search site)
an LLM would have charged me $3-5 already. Jev pricing is incredible, pricing is per *billions* of tokens not millions
huge reason this spreads like wildfire. great work @CompleteSkeptic
our eng team got #1 on HN today!
they tested if fast + cheap decision models like Jev @typesafeai could grade complex data-matching tasks as well as frontier models.
Jev with Claude Opus got close to Opus-level accuracy for a fraction of the cost.
super cool. post below:
there are literally hundreds of preseed funds writing $250k - $500k checks. like, inception stage investment. if you can’t find or raise from these folks who are purpose-built to back your stage, it’s probably a you issue, not a “reliable sources of funding” issue
can gaussian splats be used to render interfaces?
I've seen a lot of incredible spatial demos coming out of the labs (@theworldlabs has been blowing my mind ~weekly), but they've mainly been focused on static 3D environments. I woke up today wondering: are splats any good for UI
If any elected leader opposes data centers or the reindustrialization of America, just say you support them in Chinese. Make every reply below their posts in Chinese.
They will eventually go insane.
I really encourage those who haven't read Sutherland's Wheels of Incarnation to do so.
The history of our industry is not necessarily specialized approaches being gobbled up by general approaches. But it's as much specialized approaches growing towards generality.
The
very sick! our guess on the first wave of jevons paradox-ing intelligence will be "dark data"
why don't we throw intelligence at the big data we already have? too expensive + too unreliable in map-reduces
but obviously jev changes both of those issues (:
I am an AC for ICLR 2026. One of the papers in my batch was just withdrawn. The authors wrote a brief response, explaining why the reviewers failed at their job. I agree with most of their comments. The authors gave up. They are fed up. Just like many of us. I understand. We
Great article on agent memory.
Amusing failure case: Claude “summarized” 115KB of text into 203KB of wiki pages.
I think anyone who has spent time working with agents knows exactly what that feels like.
My isometric map of Toronto now covers the whole City: all 630 km², from Etobicoke to Scarborough and from the lake up to Steeles. And all of it is redrawn in a new, crisper style. 🧵👇
I don’t agree. More money in private markets means more TAM and value created in private markets.
I just don’t understand zero sum thinking for VCs. Isn’t the entire belief structure that innovative tech creates net new value?
"Many of their conclusions match my own. AI is speeding up our research, but it’s hard to say exactly how much. While they conclude AI can't yet make the most important contributions to model training on its own, they think the pace of development could, by default, accelerate
This is exactly why sloppy, overly broad use of the term RSI is a very bad idea.
Many technologies have autocatalytic effects. That's not RSI. Fear mongering and pointing to basic shit like using AI to create GPU kernels as RSI is encouraging this sort of rhetoric.
So chatted with a researcher from one of the large labs who was arguing the LoC is a reasonable metric for RSI. And evidence for the RSI that AI is writing a lot more code (for building AI). How can this be a serious view?
It's quite interesting to watch Turing award winner Sutherland's "Wheel of Reincarnation" observation playing out with models. For example, how pixel models more and more look like language models.
I think a thread is needed here 🙂. VINO is a DINO-style self-distillation framework for 3D scenes: a student network learns to predict targets from a teacher, which is itself an EMA of the student.
1/10
If this proof holds, it means that quantum computers are only polynomially faster than classical computers for general problems. Shor's algorithm is an exception, not the rule.
The funny thing is, even if this nonsense _were_ widespread, it would result in some of the easiest “non-consensus but right” opportunities in the history of venture, and the equilibrium would reset.
wtf, this is excellent and actually somewhat scary. Thinky did this on a tiny compute and token budget, without any fancy architecture or RL tricks. This is the same level of achievement as 1017. Maybe better.
This is FINALLY what can be expected of top-tier ex-Frontier staff.
One of the most impressive things about Inkling-2-Small is its self verification capability with vision in the loop 👀 It builds 3D scenes in Blender, renders them, inspects the output, spots what’s wrong and keeps iterating until it’s right. Huge congrats to @du_peichao75719
You can create a high quality replica of any space now.
These scenes were captured with just a phone and reconstructed using Echo-3.
Look at the quality! 🤯
The dogma of the last decade in computer vision is that all classical algorithms should be replaced by neural networks. This has been very productive but, counterintuitively, with the latest frontier models, I find myself sometimes turning back to classical methods.
If you have
Case Management in Ambient platform turns scattered clips from every camera into one connected incident story, sorted chronologically, with an AI-written narrative you can edit.
Incident reporting in minutes, not days. #AgenticPhysicalSecurity
@martin_casado Looks like a ton of fun 🔥. So much left to do with memory and context --- esp domain-specific / project specific tricks. Having extensible is fantastic. Love the violent example :). Would be cool to fight harness against harness in an arena and see results.
I had to skim
It is important for robot to navigate in extreme circumstances such as underground and fire rescue. The ambient communication signal provide valuable sensing measurement for those circumstances.
After supervising 20+ papers, I have highly opinionated views on writing great ML papers. When I entered the field I found this all frustratingly opaque
So I wrote a guide on turning research into high-quality papers with scientific integrity! Hopefully still useful for NeurIPS
BREAKING: Inkling 2 Small by @thinkymachines takes 4th place overall on DesignArena and is 1st place among open weights models with an Elo of 1376!
At $0.30/$1.00 per 1M input/output tokens, Inkling 2 Small is 15× cheaper on output than Kimi K3 by @Kimi_Moonshot. This model also
Please apply to come be a postdoc at Cornell through this wonderful Empire AI Fellows program! I'll be looking to recruit a postdoc myself alongside the rest of the vision group at Cornell Tech in NYC.
Inkling 2 small is an extremely impressive release, especially for its size.
It is a Mixture-of-Experts model with 594B total parameters, 17B active, and supports image inputs and variable effort.
In coding benchmarks, it easily keeps pace with significantly larger models. What
First American Open Weight model that mogs all the Chinese Open weight models
Very impressive, inkling is my fav US lab.
Looking forward to optimizing this
A lot of algorithms, especially in geometry are difficult to code and very delicate.
Now, thanks to frontier models we can try those ideas out.
Not everything needs to be solved using a big hammer of neural networks.
Proud to release our new model, Inkling 2 Small. Check out our blog post -- it includes a lot of detail about our training process.
To me, the most interesting part of this release was what we learned about alignment, which you can read about in the sections "Safety and
ICLR reviews are out.
Reviewer 1: “The paper is well-written and addresses an important problem. However, the authors should consider additional baselines.”
Reviewer 2: “The paper is well-written and addresses an important problem. However, the authors should consider additional
I interact with dozens of GPs all the time in and out of the firm and no-one thinks this way or says stupid shit like this.
Yes, there is high variance in fund raising right now. But I don’t know any legit GP that makes decisions on current ARR or growth alone.
Today we're launching Physicl Studio, and we're really proud of this one.
Tell it the situation your model gets wrong. You get it back as images or video, varied thousands of ways, with exact depth, normals, segmentation, boxes and camera pose on every frame.
Got a 2-2-3 at ICLR 2027? You're not alone: it's the single most common rating set (18.9% of papers).
On the new 1–4 scale:
2-2-3 → top 37.8%
2-3-3 → top 15.1%
3-3-3 → top 4.1%
Median paper average: 2.0. 57% of all reviews are a 2.
#ICLR2027
We tested Pangram: "Unsure", yet the heatmap found the AI half. Small demo, not a benchmark.
Chess: Bubba73 (Jud McCranie), colour adj. Hohum. Cropped, Qwen-edited, composited, annotated. Video: CC BY-SA 3.0.
The dogma of the last decade in computer vision is that all classical algorithms should be replaced by neural networks. This has been very productive but, counterintuitively, with the latest frontier models, I find myself sometimes turning back to classical methods.
If you have
One of the craziest operating system lab presentation I've ever seen (or heard!).
For his 340lx midterm project @houjun_liu built his own custom bare metal synthesizer with attack curves, tuned decay, custom drivers, dma engines, hard realtime, effect keyboard all running on
The Princeton professor who also works as a research scientist at Google DeepMind is uploading an entire robotics course to YouTube this fall, and the full previous run is already online: 24 lectures, about 29 hours, free.
"Introduction to Robotics," Anirudha Majumdar
Reading all these replies while nodding my head in agreement.
Biggest bottleneck in AI right now is not doing the work but human understanding and verification of the work.
What the hell?!! I can't believe how far we've come. Atlas is so good. Look at this fucking splat!! Check out behind the DJ table. Totally consistent novel view. No ghosting. This is entirely generated from a single image.
I'm gonna turn this into such a sick VR experience.
Why don't we at TypeSafe call Jev a decision model?
If you think of Jev's questions as making *decisions*, I believe you'll use it at the wrong layer of abstraction and your reliability will suffer.
I wrote all about this on our site 🧵👇
an absolutely beautiful and informative blog post! one of the biggest anti-patterns we see with jev is just plugging it in to make Big Decisions instead of having code do what it's best at and jev for just the parts that require judgment 🤌
THIS is how we transform software!
Introducing Inkling 2 Small. Scoring 31 on the AA Intelligence Index, it's a big jump over its predecessor.
Inkling 2 Small is available for fine-tuning and inference on Tinker today, with full weight release planned soon.
This was one of the coolest and most fun projects I have ever worked on: mechanistic shaping. We introduce a new framework for shaping what concepts a model learns to rely on during training.
My favorite applications from the paper: medical imaging. 🩻
We've released a demo of real-time world generation powered by our new Atlas model!
This is a spiritual successor to our RTFM demo from last year. It's a vision for the future of interactive media might look like, with frames streamed directly from a powerful generative model
The frame boy demo is awesome but it has no physics. I hooked it up to a vision model so it can automatically adjust the camera so It can stop me from walking through walls and even walk up and down stairs
What if you evolved the harness alongside the solution in an agentic loop? Big reductions in the cost and time to generate state-of-the-art solutions. Check out Exo, our recent work, for more details.
Congrats @AlexKrentsel @martin_casado @ankrgyl! Exo is awesome. I've been experimenting with it for an agent that plays Celeste using Opus 5.5 and improves its strategy between runs and writes tools for solved rooms. Full writeup and gameplay videos here:
Great work by @AlexKrentsel and co!
35% reduction of diagnosis time on #SREGym with significantly lower model cost.
Love the principle and architecture,
> Inspired by OS work on separating policy from mechanism, particularly ExoKernels, we expose primitive interfaces that
A science of post-training can be built on interpretability.
Models know when they reward hack, and we see it, yet training ignores it. We propose Mechanistic Shaping: using the model’s own concepts to write training rules.
In vision, DPO & RL, and its effects on monitoring 🧵
We've released a demo of real-time world generation powered by our new Atlas model!
This is a spiritual successor to our RTFM demo from last year. It's a vision for the future of interactive media might look like, with frames streamed directly from a powerful generative model
We cut through the mystery around interpretability in training.
A single, mathematically rigorous framework transforms model internals into training feedback and works across domains, problems, and modalities.
We call this *mechanistic shaping*, and we’ve used it to mitigate
for completeness, i ran the same setup on a series of open-weight models. we see none are able to beat the PPO network baseline from the original blog post -- though Kimi K3.1 Pro gets closest
Working in o11y has led to a lot of time thinking about self-improvement. @AlexKrentsel @martin_casado and I have been working on researching how you design a system that can safely self-improve and embraces the bitter lesson.
Lots of cool results in Alex's write up
Can a frontier agent recursively improve the way it works?
We built Flex-RSI to measure exactly that: recursive self-improvement of frontier agents.
🔗👇
We are excited to share our #CoRL2026 paper, "Learning Visuomotor Quadrotor Flight Through Dynamic Narrow Gaps via Differentiable Simulation", where we demonstrate autonomous quadrotor flight through narrow moving gaps using exclusively onboard vision, with policies trained from
Agent harnesses are usually hand-tuned, or optimized offline against benchmarks. What if an agent could improve its own harness *while doing the work*?
Introducing Exo, a harness architecture for runtime self-improvement 🧵
(paper:)
Late update (finally located the certificate😅)
Honored to be selected as a Top Area Chair at #NeurIPS2026 (Evaluations and Datasets), after being recognized 4x as Top Reviewer at ML venues
This means a lot to me, especially during the era of most chaotic peer-review experience
Your boss, your colleagues, your clients and your team are all watching how you handle pressure, even when they never say it out loud.
They notice if you stay calm when plans change, if you take responsibility when something slips, and if you treat people with respect on a
We're opening 100,000+ 3D objects 🧊🤗, unified in one library, ready for LLM training.
Objaverse assets, CAD parts and articulated mechanisms, all in one language !
For years, 3D research has trained on Objaverse: messy triangle soups, broken meshes, objects with no parts.
The more I am looking at AI for semiconductor design, the more it seems to me that:
1. RTL generation is just coding
2. 100% of RTL will be generated by agents
3. This means frontier models will dominate
And to be clear, we still need specialized tools for those agents that do
I asked Qwen Image 2.1 Turbo to move a knight from g1 to f3. Count the white knights.
Chess: Bubba73 (Jud McCranie), colour adj. Hohum. Adapted, CC BY-SA 3.0
Clock: Envato Elements. Music: CorporationMusic.
Our friends at @Uni_Stuttgart have some open positions for ELLIS Independent Junior Research Group Leaders incl. one for Computer Vision: Deadline Nov 15th
If you know a good PostDoc who wants to grow his/her own group, please let them know.
So far I git Claude security flag twice - when discussing sheep/ram in Imagenet classes, and when tried to make more secure my mom's router.
Codex is fine with both.
Are you developing AI or technology to support older adults, including people living with Alzheimer's disease and related dementias? Stanford AITC has launched a research award competition, supported by the National Institute on Aging. Join a webinar to learn more: November 4 | 9
Did you like SuperGlue & LightGlue? You’ll love FlexGlue, our new model for image matching
1️⃣ It’s flexible: sparse & dense point tracking & matching, all in one model
2️⃣ It rejects negative pairs: it won’t match symmetries that often break SfM!
Available in COLMAP, try it out ↘️
The way I read research papers has changed a lot recently.
Before, when I read papers, I often tried to understand the researchers' personalities and ways of thinking through their research.
But now, because of AI, it is becoming difficult to tell how much of the research comes
Very proud of my son @cappucher for working for months (with his AI collaborator) to, for the first time ever, prove the asymptotic for E.P. Stein numbers (in the put-or-take-a-square game)
And thanks to @skominers for advice and counsel along the way!
New work with @kowshik_shreyas and my amazing advisors @max_simchowitz & @aviral_kumar2
We find that just one demonstration is enough to bootstrap autonomous learning in pretrained robot policies. With the right recipe, RL can learn reliable policies from brittle initializations!
My group at FAIR (Meta) is looking for a summer research intern. If you have experience with SAM/object segmentation, especially in microscopy images or similar domains, and are excited to contribute to the next generation of SAM models, apply here:
@Arjunjain Plot twist: I was Vapnik's Department Head between 1996 and 2002, and made sure he had the space, resources, and collaborators to do his best work.
To people who think I'm dogmatic: I famously disagreed with Vapnik about the best way forward in ML, but did what I could to
#hiring# Computer Science at Boston University invites applications for a tenure-track faculty position at the rank of Assistant Professor beginning July 1, 2027. We seek candidates in AI, broadly defined.
Can a frontier agent recursively improve the way it works?
We built Flex-RSI to measure exactly that: recursive self-improvement of frontier agents.
Check out more details below👇
1 hour writing about exp.: poof, gone. days until CVPR fly by like hours.
1 sec holding a plank: I swear I can count fractions of a sec, and each feels like at least a few sec.
I guess we all have our strengths, Margot Robbie* 😂
*Margot Robbie famously held a 4-min and 10-sec
TACL update: Papers which were submitted to ARR or xACL conferences within the past 9 months cannot be submitted to TACL. This includes papers which were unsuccessful in the ARR reviewer capacity lottery, or otherwise were desk rejected by ARR.
I wanted to understand the structural and philosophical differences between GPUs, TPUs and newer alternatives (like Groq LPUs) without getting drowned in specs and jargon.
Mispronunciation of the day: "soldered" 🤦♀️...
0:00 Intro
0:56 The origin story of TPUs
3:42 The first TPU:
Top 3 teams take home cash. And every member of the top 5 teams walks away with a Google product. 🏆
$𝟭𝟱𝗞 𝗽𝗿𝗶𝘇𝗲 𝗽𝗼𝗼𝗹 at Orbis Build Day:
💰 $4K / $2K / $1K cash
🎁 Pixel Buds, Fitbit Sense, Nest Learning Thermostat, and more from @googlecloud
🎟️ 2 free tickets to
My friend @vitalygordon made a good point on the question of market saturation for tokens.
Right now for most companies, tokens are still <5% of labor. So it doesn't makes sense to skimp on making the 95% productive. Somewhat like giving high paid cooks dull knives.
I gotta' say, the memes I'm seeing from the moderates/right on the election results are a lot funnier and more good natured than when similar happened last election cycle from the other side.
Today we’re announcing an $8.75M seed round for Phaze.
Companies aren’t ready for how many computers people and AI agents are about to need. And it’s happening just as computer prices are up 3x.
Chris and I spent years building Parsec to make a computer thousands of miles away
Principled SSL, simpler than DINOv3, and matching its performance?
Check our new SSL algorithm JEM on arxiv 🔥
A big effort led my @maxseitzer who has shown me that patient work still has it's place in today's world 🫶
If you liked LightGlue, you will like FlexGlue even more! It's better on all fronts (also beats RoMa & LoMa), sparse and dense matching, also uniquely suppresses matches between similar, but non-matching images. Best of all, it's already available in COLMAP.
Martin Casado (@martin_casado) explains his tweet on non-consensus investing:
"The idea that non consensus investing is where the alpha is, is actually quite dangerous in the early stage.
Follow on capital tends to be more and more consensus aligned."
"There's something tied
Studio notes — Wednesday, November 4
It's incredible how musical collaborations can take you into new territory: new ways of working, new sounds, places you hadn't explored yet. I think it's the best way to step out of your comfort zone and grow.
Martin Casado (@martin_casado) has been building and investing in technology for 30 years.
We distilled the most important lessons from our conversation on the craft of venture investing.
1. Private markets are efficient. If you believe in markets, you should believe private
My third conversation with Martin Casado (@martin_casado), general partner at @a16z.
- The case for consensus investing
- Why moats are overrated
- Frontier model economics
- What happens when AI growth slows
- Why private markets are efficient
- Lessons from Cursor, OpenRouter,
Our Claude maze agent reached 9.8 MB per request by move 100. Using message threads, that dropped to 104 KB: just the new screenshot and the previous response ID. Token use stays the same, and threads expire after 5 minutes. We measured upload size, not speed.
@Arjunjain Plot twist: I was Vapnik's Department Head between 1996 and 2002, and made sure he had the space, resources, and collaborators to do his best work.
To people who think I'm dogmatic: I famously disagreed with Vapnik about the best way forward in ML, but did what I could to
The whole downtown core of my isometric Toronto is drawn: Bathurst to the Don, Bloor to the harbour.
12.66 km² as one 256-megapixel image, about 2% of the city, made in one evening on my laptop.
Explore it:
As part of my campaign to point out that discussions on defensibility are generally pointless, here is a very classic theoretical result showing that you can't even efficiently compute Nash equilibrium states.
Even with billions in your bank account, you can’t buy enough compute to beat the majors head-on. What you can do is extract far more value from every MW you have.
That’s why key theme of 2026 and 2027 for us is post-training. Improving the quality of diffusion models while
OpenCV - Open Source Computer Vision Library@opencvofficial·03/11 20:45
OpenCV Live, Thu Nov 5, 9am PT: From Pixels to Physical AI. How OpenCV + RealSense depth + NVIDIA Jetson + ROS 2 + vision-language models become the Visual Cortex of robots. Live demos: spatial reasoning, navigation, natural-language robot control.
when LaMAria was introduced a year ago, Meta's closed-source Aria SLAM was far ahead of academic systems.
one year later, we've surpassed it in 3/5 categories: medium, long, and low light.
here's what closing that gap looks like:
To match or not to match?
FlexGlue 🐙, our new image-matching model, can match every pixel AND reject doppelganger pairs, tackling a common failure case in SfM.
➡️State-of-the-art SfM and matching, blazing fast
➡️Code:
➡️Paper:
1/
International Conference on 3D Vision (3DV)@3DVconf·03/11 17:15
📊 We've revisited the cities and the most-cited papers. Now, a look through the research archive: 1,351 papers across 17 topics, from 2013 to 2026.
We're excited to see the new ideas and directions our community brings to #3DV2027!
gece 2’de iyi sonuç alıp uyuyamayan öğrenciyle..
ben: bana niye haber vermedin, beraber sevinirdik.
Eray: hocam geç olmuştu, uyursunuz diye.
hoca durur mu, yapıştırmış cevabı: sen benim geceleri uyuduğumu mu zannediyorsun Memati 😂😂
Our own paper today. Kwak et al., "Solv3R: 3D Looped Transformer as a Multi-view Solver"
Multi-view geometry has traditionally been "solved" with steady-state solvers. We use a Loop-Transformer to do exactly that. What I like most is that you can pipeline for 16x+ throughput.
📢📢📢 Introducing 𝐒𝐨𝐥𝐯𝟑𝐑
Can geometric foundation models move beyond fixed-set prediction and keep solving like classical SfM?
We turn a looped Transformer into a reusable 𝐥𝐞𝐚𝐫𝐧𝐞𝐝 𝐠𝐞𝐨𝐦𝐞𝐭𝐫𝐢𝐜 𝐬𝐨𝐥𝐯𝐞𝐫
🌐 Project:
🧵👇
📢📢📢 Introducing 𝐒𝐨𝐥𝐯𝟑𝐑
Can geometric foundation models move beyond fixed-set prediction and keep solving like classical SfM?
We turn a looped Transformer into a reusable 𝐥𝐞𝐚𝐫𝐧𝐞𝐝 𝐠𝐞𝐨𝐦𝐞𝐭𝐫𝐢𝐜 𝐬𝐨𝐥𝐯𝐞𝐫
🌐 Project:
🧵👇
📢VoxLution: Real-world scans are noisy & partial, so 3D scene generators often rely on synthetic data.
@DaoyiGao & @xinyi092298 introduce a sparse voxel cascaded transformer trained on real scans, generating high-fidelity realistic scenes!
Check it out:
Narrative-Stye CVs? What new devilry is this?
We need another CV format for Canadian granting agencies, after the incompetently-implemented and infuriating-to-use CommonCV was supposed to solve the issue that there are too many CV formats?
@martin_casado RSI mostly won’t happen at the weight level! at most this is an interp team effort to make the models good at auto-interp. but given astra an opus both rise together, i assume this is just an emergent capability at scale
Sounds like a surprising result
Is it possible that GPT-6 Astra is aware of the target task and have access to some fine-tuned Qwen weights in some way (say 🤗) to cheat?
Some of the replies imply that it won't generalize well
You can't ship what you can't verify. Distributed systems are hard to verify because, like, 50% of the semantics have to be learned operationally. This is even true of something super vibe-able, like Raft. Here are some things prod will teach you the hard way:
* Raft's "correct
i've reproduced the results from the MIT blog post today on weight-space programming. but one additional result i have to add: this is a new, step-change emerging capability that's appeared in just the latest set of models.
📢 LucidLyra: Feed-Forward Generative 3D Scene Reconstruction and Joint Understanding via Multi-Task Distillation!
Generate a queryable 3D Gaussian scene from a single image! Our feed-forward decoder jointly predicts geometry, appearance, open-vocabulary semantics, and object
So great to be part of the Stanford Digital Brain Project! With @dyamins and an amazing team at @StanfordBrain, we're building a digital model of the human brain to learn how it works and, one day, better understand and treat brain and mental health disorders.
mmm discovering a bunch of papers that have added my name on without me being aware of it, seems difficult to get your name removed once they are out there.
Lately, there’s something so exhausting about attending a professional or academic session. Idk what to call it but everything feels so same now. PPTs used to reflect personality. People would actually put thought into the design, wording, little details. There was subjectivity.
📢 LucidLyra: Feed-Forward Generative 3D Scene Reconstruction and Joint Understanding via Multi-Task Distillation!
Generate a queryable 3D Gaussian scene from a single image! Our feed-forward decoder jointly predicts geometry, appearance, open-vocabulary semantics, and object
Finally
@CVPR thank you for removing hidden trap for the workshop organizers and exposing the Metadata submission deadline!
Next thing to dream about, is to move/remove it -- why do we need it like month before the actual paper?
Two people roll a cable reel away from a substation in the dark.
Camera that records keeps the footage. System that reasons flags the theft as it happens, with context to act. Ambient Threat Detection, on cameras you already run.
#CriticalInfrastructure #AgenticPhysicalSecurity
I have been teaching myself formal code verification, but as the practice becomes more widespread, we must remember that mathematical perfection is often *not* good enough.
Our systems need to be understandable to humans.
I promise you'll l earn something from this. It's one of the more in depth discussions I've ever had on end to end economics of robotics, why robotics cos tends to verticalize, the complication of the long tail, etc.
Tutor is my first "actual robots" investment (w/ Raghu). Complete, operational, robots w/ hundreds in production.
While being off the scale technical, the team is obsessive about pragmatic approaches to making the end to end economics work.
Very excited to be partnering.
We’re thrilled to lead Tutor Intelligence’s Series B.
@tutorintel is a robotics research and deployment company that builds generally capable robot hardware. They deploy into real production environments ahead of full autonomy, using human teleoperators (“tutors”) to train the
It now has LLM, internet, web search access and can show images, call tools; the responses would normally be over a speaker (not connected yet)
You don't get to hear my magnificent voice here but you do get a screen transcript. Mic/STT model seems to be working cleanly
📢 LucidLyra: Feed-Forward Generative 3D Scene Reconstruction and Joint Understanding via Multi-Task Distillation!
Generate a queryable 3D Gaussian scene from a single image! Our feed-forward decoder jointly predicts geometry, appearance, open-vocabulary semantics, and object
זה גרף די מדהים. הוא בחן 5000 סטארטאפים במטרה להבין מי מהם הצליח לגייס כסף מקרנות הון סיכון בשורה הראשונה.
הפרמטר החיובי הראשון: עובדים לשעבר של אותן קרנות
הפרמטר החיובי השני: עובדים לשעבר במעבדות המובילות
הפרמטר החיובי השלישי: בוגרים של הטכניון/אוניברסיטת תל אביב 🇮🇱 🇮🇱 🇮🇱
This is the lesson I am learning in the Swedish context as well. Many norms in Chinese working environment, such as building a record of the progress of the project, cc direct report on all correspondance, speak rather candidly on issues etc, doesn't fit western style.
Twitter is great but today a plane brutally crashed killing like ten people and all I’ve seen is mutuals making real dumb, poor-taste jokes or memeing about it
I get that most things aren’t sacred but I figured at least mass loss of life tragedies would be
Is it because you
Weekend hack: HackerTube. I was annoyed with YouTube's recommendations so I had Claude filter down 43M comments over 20 years of HN to 6,454 videos that keep being recommended. *Significantly* better viewing experience, ~2 hours with Opus 5.5:
- Excellent
Waterloo’s IP policy let's students and faculty own their IP. Its value is reinforced by the university’s commercialization expertise, entrepreneurship programs and industry relationships. Waterloo’s seventh-place global ranking in 2026 is a strong indicator of its ability to
Historical tenure rates in EE/CS across some well-known universities:
Caltech EAS (~100%)
Carnegie Mellon (~80%)
Pennsylvania (~75%)
Harvard/Yale (~60%)
Berkeley/UCLA EECS (~66%)
Stanford & MIT EECS (~50%)
Statistically speaking, at Caltech's Engineering division, the initial
New episode of The Information Bottleneck with Julian Togelius @togelius about AI and games 🎮🕹️🎲
Julian (NYU professor, co-founder of) has been working on AI for video games since 2004, back when people told him it wasn’t real research. Basically every
Day 28/ tibo's game has landed
i spent $5.99 on this domain, but i had a blast making it with grok bot and cursor! i hope you enjoy it and find all the easter eggs 🤍
if i did it right you should be able to play it inside of X too
We're hiring in Physical AI at UW–Madison!
The ECE department is recruiting faculty at all ranks, with interests spanning multimodal sensing, physical modeling, robotics, and autonomous systems.
Full consideration by Dec 14, 2026.
Proud of @liyuan_zz for World from Motion and its acceptance to #NeurIPS2026. With @shalinidemello, @alextrevith et al., an NVIDIA collab.
It reconstructs dynamic 3D scenes from monocular video by conditioning a video model on 4D Gaussians, filling in what the camera never saw👇
Finding an RCE in the Linux TCP stack is some 1990's shit. Wow.
Spelunking through kernel code just stopped being worth the effort with all the other attack vectors up the stack. But with AI, it's basically free.
So we're dredging up monsters lurking in the deep.
I redid the startup founder signals that lead to top tier VCs investing in the seed / A, after incorporating some feedback.
This added ex-frontier lab and cyber security near the top, IIT as a positive, and educated in China as a negative.
The main changes were;
- extended
With all the progress that's happening, anything but 4D YouTube in 2027 would be a disappointment. Unfortunately, most pipelines are closed source. Here's a teaser of how I'll try to do my part. Quite happy with how well extrapolation works.
(yes, this model is only 20% trained)
Is it just me or has a lot of the AI policy chatter died down? Perhaps having concrete issues to deal with (cyber) has taken the existential edge off much of the discourse?
. @bot is now the most used app on my phone and what I access most other apps from.
I need embodiment ideas ... thinking Holly from Red Dwarf. Any other thoughts?
Neural Thickets (@yule_gan @phillip_isola): add random noise to an LLM's weights, keep the best copies, let them vote. Reasoning jumps, no training.
Why does it work? It's sampling in disguise. Swap noise on billions of weights for one random vector on the logits: same gains 🧵
There is a "bug" in commonly used activation functions (ReLU/SiLU/GeLU etc.) ---- The mean of post-activations is not zero.
This bug, however small it seems, leads to pathologies of training dynamics, including loss spikes & representation overshooting.
By removing the bug,
Many of you are in the process of applying for jobs in academia and/or in industry.
As you prepare your job talks, consider giving it the following structure:
First, a short snippet of your overall set of technical accomplishments. For instance, you might spend the first 15
I wonder why Carm, Lace 2 and Phantom fights are feeling so great, that I am fine to lose them to experience indefintely, but Trobbio is so annoying.
#SilkSong
Good slides are extremely intentional. When someone presents a paper, the paper already has all the information. But the speaker would make deliberate choices about things like, what to say and what not to say, what to put on a slide and what to say only verbally.
What to frame
my hypothesis for why AI-generated slides for technical presentations are so awful:
people who don't have a lot of experience presenting think that to make a talk you just put all of the stuff you want to talk about on the slides, then you go through each slide and say the stuff
Can we trace an AI model's answers back to its training data?
Surprisingly, even when we know exactly which documents taught a model a fact, attribution methods often fail to find them.
Our CATT benchmark investigates why and uncovers two simple fixes🧵
The Platonic Representation Hypothesis is now a Theorem ◼️
Train JEPAs separately, on any modalities: they provably learn the same representation up to one rotation.
The result? A 109M JEPA-Text model that aligns with vision models better than 72B LLMs.
w/ @ylecun 🧵
🧵[1/4] Most 3D models assume a pinhole camera. What about a fisheye, GoPro, or 360° panorama?
Excited to share OmniRay: 3D reconstruction from a single image from any of these cameras, no intrinsics needed.
w/ @jai_abhayk, Cheng Peng, Rama Chellappa, @anand_bhattad
Several recent papers find that you can ~align image and text embeddings with just a rotation.
@randall_balestr and @ylecun released a cool demo of this here:
I tried it on a photo of my cat Moxie. I have to say, it is completely accurate!
Neural Thickets (@yule_gan @phillip_isola): add random noise to an LLM's weights, keep the best copies, let them vote. Reasoning jumps, no training.
Why does it work? It's sampling in disguise. Swap noise on billions of weights for one random vector on the logits: same gains 🧵
This insight is why so many software engineers seem depressed recently.
They can build anything they want now in 5% of the time, but it’s harder to make money because everyone else can do it too.
What if your office had a portal to a sacred world?
I built this on my Apple Vision Pro
Walk through the liquid portal → step into the sacred ruins
Huge thanks to Ian (@XRarchitect) for the amazing portal reference and examples. Such a creative mind, this wouldn't exist
Over the past few days, I dug into the geometry of LoRA to understand how exactly it constraints the geometry of the search space. There's a beautiful connection to the *intrinsic dimension* of a task.
Also learnt I'm saying "difficulty" wrong... 🤡
0:00 MNIST vs the walking
Yea, board and screen arrived yesterday, CAD cover and Rust firmware prototyped today
Mic, WIFI incl. TLS connections, bluetooth etc
A lot of work went also to cryptography/security so nothing is stored plaintext and not even the cpu can read your root key
Firmware test:
A silent CV bug: swap RGB and BGR, and YOLO11s recall fell from 67.9% to 57.4% on COCO128. No crash.
Google says Gemini 4 Carbon can tackle long debugging tasks; we haven’t tested it. My checklist for any fix: reproduce, inspect the diff, retest on held-out data.
Ever since Thomas’ JIT-fusion update for Instant-NGP, I was wondering how fast a fully fused Zip-NeRF could be. Finally gave it a shot with Opus:
36 min training, 300 ms per megapixel on a 5090, same quality as the official code (~6-7x/10x faster).
Code:
NSF invests more than $110 million to improve next-generation wireless technology through the first-ever NSF Verticals-enabling Intelligent Network Systems investment. 🛜
This is apparently not fully autonomous (a remote human is supervising; not sure how much) but if it's real it's still some of the best robotics I've seen.
Why Fewer CPU Threads Made YOLO 2x Faster (ONNX Runtime)
In Ultralytics’ benchmark, limiting PyTorch to two threads cut the time to process 1,000 images from 58.8 s to 27.1 s on an 8-vCPU machine. Same model, no retraining.
PyTorch handles preprocessing and postprocessing while
SAM3 now runs offline on your GPU.
An ONNX export of Meta's SAM3 that runs on NVIDIA CUDA and Apple CoreML. Besides text, it takes several example boxes, negative boxes and clicks as prompts.
A text prompt takes 0.37 s on an M5 MacBook Pro and 0.08 s on an RTX 3080 Ti.