The race cars have another sensor—a laser aimed straight down underneath the car. This laser can tell whether the car is sliding through a turn, which helps the main AI computer push the race car around the turn as hard as possible. This maximizes speed without losing traction,
MACHINE LEARNING
-
Battery-Powered Edge AI: Future of Robotics and Medical Devices
By
–
Sitting around with family talking about things NVIDIA would want to buy next. Battery powered edge AI comes to the top of my head. And discussion. Will run a ton of robots, or pieces of them, like one per hand, and medical devices. Including brain computer interfaces. Runs
-
ScaledML 2026 Conference: Machine Learning Slides and Resources
By
–
Slides: https://
cdn2.hubspot.net/hubfs/6212008/
ScaledMLMediaArchives/2020/Slides/DennisAbts-2020.pdf
… ScaledML: http://
ScaledML.org (happening January 2026) -
The historical transition from symbolic AI to neural networks
By
–
On est d’accord. Après il y a plus de 10 ans c’est vrai que le prédictif notamment symbolique n’a pas vraiment porté ces fruits … vu que ça a vite était manger en terme d’efficacité par les approches type neural network.
-
Questions on Demo Statistics, Failure Modes, and Bimanual Grasping Correlations
By
–
Kudos on this elegant demo! Can you share some stats and failure modes? Are any of these items in the training set? Bimanual grasping seems to correlate w/ size. Are there counterexamples? Eg, a full-sized paper grocery bag w/ handle that it grasps w/ one hand? https://t.co/nITsKLCgG1
— Ken Goldberg (@Ken_Goldberg) 24 décembre 2025Kudos on this elegant demo! Can you share some stats and failure modes? Are any of these items in the training set? Bimanual grasping seems to correlate w/ size. Are there counterexamples? Eg, a full-sized paper grocery bag w/ handle that it grasps w/ one hand?
-

VLMs Struggle with Physical World Reasoning from Videos
By
–

‼️VLMs/MLLMs do NOT yet understand the physical world from videos‼️ In our recent work, we found that even the most advanced AI models still lag behind humans in one key aspect: reasoning about the kinematic properties of objects from videos. Takeaways: 1. ChatGPT 5.1 leads overall among 21 advanced VLMs, followed by Gemini 2.5 Pro/Flash. 2. Grok 4.1 delivers impressive performance at the lowest API cost. 3. Qwen3-VL is the top-performing open-source model. Read here: quantiphy.stanford.edu/ 🧵1/N
-
AI Data Transparency Crisis in Life Sciences Research
By
–
The Pistoia Alliance’s recent poll highlights a “scientific content crisis” in the life sciences, with 27% of professionals unaware of the data sources their AI models use, thereby affecting AI’s reliability. https://
bit.ly/4qkIRR5
#AI #Data #research #Elsevier #PistoiaAlliance -
AI Is Eating Software: The Next Wave of Disruption
By
–
“Software is eating the world, and now AI is eating software.”
-

MIT Research on the Instability of Long-Chain AI Reasoning
By
–
This MIT paper explains why telling models to “think harder” keeps failing in practice. The core argument is simple and uncomfortable: reasoning doesn’t break because models lack knowledge. It breaks because reasoning itself becomes unstable when it goes on too long. The
-
AI Cannot Learn Specific Knowledge Without Verifiable Answers
By
–
Specific knowledge doesn’t have verifiably correct answers – so it’s not something AI can be trained for, either.