Short proofs in combinatorics and number theory Alexeev et al.: https://
arxiv.org/abs/2603.29961 #ArtificialIntelligence
RESEARCH
-
AI Discovers Short Proofs in Combinatorics and Number Theory
By
–
-
AI Engineer Europe Conference Schedule with DeepMind Content Released
By
–
Find the schedule here! There will be tons of DeepMind goodies, workshops, talks, and demos! Kudos @swyx and the entire team for pulling this together! 🫶 ai.engineer/europe
-
VLMgineer: AI-Powered Robots Design Their Own Tools
By
–
Can AI truly empower robots to invent their own solutions? George Jiayuan Gao, Tianyu Li, and colleagues from UPenn present VLMgineer. This framework leverages Vision Language Models (VLMs) to brainstorm initial tool designs and action plans. It then refines these ideas using evolutionary search in simulation, optimizing both the tool's geometry and how the robot uses it. VLMgineer consistently outperforms existing human-crafted tools and VLM-generated designs from human specifications across diverse, challenging everyday manipulation tasks, transforming complex robotics problems into straightforward executions. VLMgineer: Vision Language Models as Robotic Toolsmiths Project: vlmgineer.github.io Paper: arxiv.org/abs/2507.12644 Our report: mp.weixin.qq.com/s/FXdeQhAeq… 📬 #PapersAccepted by Jiqizhixin
→ View original post on X — @jiqizhixin, 2026-04-03 14:45 UTC
-
Possible Candidate for the First Major Discovery
By
–
https://reddit.com/r/accelerate/comments/1sb04u2/we_may_already_have_a_contender_for_the_first/
… + NYT -
τ³-bench: Interactive Agent Evaluations for Knowledge and Voice
By
–
Really excited for the release of 𝜏³-bench, which brings interactive agent evals ever closer to real-world use cases across two dimensions: 1. 𝜏-knowledge evaluates agents that need to operate over noisy knowledge bases to figure out the correct policies/tools to use while serving a user 2. 𝜏-voice tests voice agents in interactive customer service style settings. If you are developing embedding or voice models for AI agents, 𝜏³ is a great testbed for you to see how your models would perform in a realistic downstream use case. Blog: sierra.ai/blog/bench-advanci… Tweets from @BenShi34 and @keshav_57: nitter.net/benshi34/status/203436… nitter.net/keshav_57/status/20346…
-
LeWorldModel: Teaching AI to Simulate and Understand World
By
–
LeWorldModel: Teaching AI to Simulate and Understand the World
— Satya Mallick (@LearnOpenCV) 3 avril 2026
In this episode of Artificial Intelligence: Papers and Concepts, we explore LeWorldModel, a new approach to building AI systems that can model and simulate real-world environments. Instead of reacting to inputs… pic.twitter.com/Jlf3hbSIfvLeWorldModel: Teaching AI to Simulate and Understand the World In this episode of Artificial Intelligence: Papers and Concepts, we explore LeWorldModel, a new approach to building AI systems that can model and simulate real-world environments. Instead of reacting to inputs step-by-step, world models aim to learn underlying dynamics—allowing AI to predict outcomes, plan actions, and reason about future scenarios. We break down why traditional models struggle with long-term reasoning and planning, how world models enable a deeper understanding of cause and effect, and what this means for applications like robotics, gaming, and autonomous systems. If you’re interested in world models, reinforcement learning, or the future of AI systems that can think ahead and simulate reality, this episode explains why LeWorldModel represents an important step toward more general and intelligent AI. Resources: Paper Link: arxiv.org/pdf/2603.19312v1 Interested in Computer Vision and AI consulting and product development services? Email us at contact@bigvision.ai or visit us at bigvision.ai
→ View original post on X — @learnopencv, 2026-04-03 14:30 UTC
-
Google DeepMind Adopts Apache 2.0 License for Open Models
By
–
Love that Google DeepMind is following OpenAI’s suit w/ using Apache 2.0 license for their open weights models – congrats! but, can we please stop using Arena Elo as the de facto measure of performance?
-
AI Coding Agents Reach Inflection Point in November 2025
By
–
My biggest takeaways from @simonw
: 1. November 2025 was an inflection point for AI coding. GPT 5.1 and Claude Opus 4.5 crossed a threshold where coding agents went from “mostly works” to “almost always does what you want it to do.” Software engineers who tinkered over the
