Excited for this release — can't wait to see how agents handle the Snorkel-contributed tasks! We'll be at the event too — see you there!
AGENTS
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Stress-Testing AI Model Specifications Reveals Underlying Preferences
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Stress-testing model specifications, led by Jifan Zhang. Generating thousands of scenarios that cause models to make difficult trade-offs helps to reveal their underlying preferences, and can help researchers iterate on model specifications.
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AI Agents for Personalized Learning in Education
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AI Agents for Personalized Learning revolutionize my teaching.
They provide tailored experiences and solve education challenges.
• Use adaptive platforms
• Customize lesson plans
• Address individual needs Click below to read more: https://
godofprompt.ai/blog/ai-agents
-for-personalized-learning-use-cases
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Perplexity will allow its Assistant to record meetings
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Perplexity will enable its Assistant to join and record meetings so it can send out meeting summaries to participants. All capabilities will be adjustable. * Not available yet
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AGI Definition: Feature-Complete Remote Worker with High Reliability
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When I say AGI I mean a "feature complete" build of a remote worker with a lot of 9s (think: a bit like current Autopilot FSD, maybe plus a few more iterations). This is the original definition I've stuck to forever. Separate from the diffusion /implementation of it across
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Verdent AI Achieves High Performance on SWE-bench Verified
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Verdent AI achieved a score of 76.1% at pass@1 and 81.2% at pass@3 without parallel test-time compute on SWE-bench Verified!
— 🚨 AI News | TestingCatalog (@testingcatalog) 3 novembre 2025
Claude, GPT, and MiniMax models power Verdent agents, coordinating verification steps that review and validate code before it’s finalized. https://t.co/6XZCvxhL5H pic.twitter.com/GT1yRI5O2iVerdent AI achieved a score of 76.1% at pass@1 and 81.2% at pass@3 without parallel test-time compute on SWE-bench Verified! Claude, GPT, and MiniMax models power Verdent agents, coordinating verification steps that review and validate code before it’s finalized.
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The Evolution of AI from Tools to Thinking Collaborators
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Denario shows what happens when reasoning, experimentation, and authorship merge into one system. It doesn’t just help humans do science faster it expands what science can be. We’re not building tools anymore.
We’re building thinking collaborators. Are you excited or scared? -
Denario: AI-Powered Research Assistant for Automated Scientific Workflows
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Denario even comes with a full research GUI. You can load a dataset, describe a problem, and watch it generate a hypothesis, review the literature, build a method, run analysis, make plots, and produce a draft paper live. Science with a “Run” button.
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Automating Academic Research Workflows with Autonomous AI Agents
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Every output is organized like a research notebook. Each module writes its own files, and together they form the paper’s entire backbone from concept to publication. The structure feels eerily human: idea → literature → method → analysis → paper → review. Except this lab
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Using multi-agent systems for structured idea generation
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Denario’s creativity isn’t random. It’s structured conflict. An “idea maker” proposes a new project. An “idea hater” attacks it testing for novelty, feasibility, and clarity.
They argue, refine, iterate, and only the strongest idea survives. Machine brainstorming with