🚀 Join us for the CAMEL-AI Live Talk on InferenceBench: A Benchmark for Open-Ended LLM Inference Optimization by AI Agents with Jehyeok Yeon @jehyeoky248, incoming PhD at the ELLIS Institute Tübingen & Max Planck Institute for Intelligent Systems. We will be sharing how InferenceBench evaluates AI agents on realistic LLM inference optimization tasks under single-GPU, goal, and time constraints, and what it reveals about current agents’ struggles with open-ended exploration, prompting reliance, and reward hacking. 🕐 12 June 2026 | 13:00 BST / 8:00 AM EDT 🔗Register: forms.gle/JkfeMUEhmLn9RwwD9

🚀 Join us for a CAMEL-AI Live Talk with Bowen @BowenWangNLP on CUA-Gym! CUA-Gym scales verifiable RLVR training data for computer-use agents, with 32,122 tasks across 110 environments. Homepage: cua-gym.xlang.ai 📅 June 5, 2026 | 13:00 London time Register: forms.gle/x3M1L4tfeSSoX5oH7

🚀 Join us for a CAMEL-AI Live Talk with Bowen @BowenWangNLP on CUA-Gym! CUA-Gym scales verifiable RLVR training data for computer-use agents, with 32,122 tasks across 110 environments. Homepage: cua-gym.xlang.ai 📅 June 5, 2026 | 13:00 London time Register: forms.gle/x3M1L4tfeSSoX5oH7

CAMEL-AI Live Talk this Friday 🚨 "Articraft: An Agentic System for Scalable Articulated 3D Asset Generation" by Matt Zhou @Mattzh1314 (Visiting Researcher at the University of Cambridge) Articraft is a system for generating 3D articulated assets at scale. It leverages a custom agentic harness with geometric validation built in, and a LLM-friendly 3D design library to achieve this. Tuning for a blend of both realism and cost-effectiveness, Matt and his team use Articraft to create a large 10k scale dataset of articulated objects, and study using this data to improve existing models and unlock downstream applications in robotic simulation and VR. Paper link: arxiv.org/html/2605.15187v1 🗓 May 29 · 8:00 PT / 16:00 BST 🔗 Register for Live Talk: forms.gle/K1drb9ao5QQmhB6z8

Check out Ariticraft 🦾 - a highly efficient agentic system that generates articulated 3D assets fully automatically at scale! 🚀 articraft3d.github.io/

Gemini 3.5 flash Gemini managed agents api just audited a real megatron-lm ci failure inside Eigent. root cause in minutes! watch the handoff: coordinator agent plans the audit, developer agent loads the ml-failure-audit skill and gathers the evidence, then gemini agent steps in as a remote sub-agent for the heavy reasoning. gemini managed agents api and gemini 3.5 flash now live on our open-source cowork Eigent! @googleaidevs @GoogleAIStudio

🚨CAMEL-AI Live Talk by Xingyue Huang @hxyscott on RelAgent, an LLM-agent framework that acts as a data scientist for relational learning. RelAgent autonomously searches via tool-calling over SQL feature programs and downstream models, guided by validation feedback and an evaluation workspace for task-specific diagnostics. At inference time, there are no LLM calls, only executable SQL features a classical model. RelAgent achieves competitive results against relational foundation models while staying fast, deterministic, and interpretable. Paper: arxiv.org/abs/2605.07840 ⏲️ 15 May 2026 13:00 BST | 8:00 EDT 🔗 Register: forms.gle/Myjx7A4URqp9Q7mD6

OrcaRouter now supports @CamelAIOrg 🐫🐋 We added ModelPlatformType.ORCAROUTER as a dedicated model platform integration. OrcaRouter is an OpenAI-compatible LLM gateway with adaptive routing that automatically picks the best upstream model per request. ⚡ Lower latency 💸 Better cost efficiency 🧠 Access to top models through one endpoint Works seamlessly with CAMEL and existing OpenAI-compatible agent workflows. github.com/camel-ai/camel