6 entries
Keyword: arc-agiArticle:ARC Prize Foundation
The ARC Prize Foundation has introduced ARC-AGI-3, an interactive benchmark designed to evaluate agentic intelligence within novel, turn-based environments. While human testers achieve a 100 percent completion rate, frontier AI systems score below one percent as of March 2026.
From Video: AI Weekly Updates: Open-Source Model Surge, Agent Harnesses, and Meta's AI Reality Check
Link:arcprize.org
The organisers of the ARC Prize have introduced the ARC-AGI-3 track for 2026. Moving beyond static reasoning tasks, the benchmark challenges autonomous AI agents to explore, adapt, and operate inside dynamic environments without instructions. A total prize fund of $850,000 is available.
From Video: AI Weekly Updates: Open-Source Model Surge, Agent Harnesses, and Meta's AI Reality Check
Link:arcprize.org
ARC-AGI-3 is an interactive reasoning benchmark designed to evaluate human-like intelligence in AI agents. Moving beyond static puzzles, agents must explore novel environments, derive goals on the fly, and adapt through multi-step interaction.
From Video: AI Weekly Updates: Open-Source Model Surge, Agent Harnesses, and Meta's AI Reality Check
Link:openlm.ai
OpenLM.ai has published Chatbot Arena +, a consolidated LLM leaderboard. The rankings combine an agent-driven battle platform using LLM-as-a-judge Elo ratings with the Artificial Analysis Intelligence Index (AAII) and the ARC-AGI v2 benchmark.
From Video: Weekly AI Updates: Vulkan, Mojo, Kimi K3, and Emerging Agent Frameworks
Article:Equipe do Google Gemini
Google has launched Gemini 3.1 Pro in preview, introducing significant gains in core reasoning designed to tackle complex problem-solving, coding, and agentic workflows.
From Video: Weekly AI Updates: Model Releases, Prompt Tricks, and Agent Architectures
VideoVideo:Lev Selector
Lev Selector reviews key artificial intelligence developments, highlighting the rapid adoption of open-source models on Vercel, Nvidia's AVO Agent solving ARC-AGI 3, and the proliferation of open-source coding harnesses. The presentation also analyses Meta's internal data, where unsupervised coding agents led to a notable rise in technical and security incidents following staff cuts.
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