Optimizing Predictive Models with AutoML Without Relying on a #DataScience Experts by @antgrasso #ArtificialIntelligence #AI #MachineLearning #ML #BigData
AGENTS
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Qwen 3.7 Max achieves 10x speedup in autonomous 35-hour run
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Alibaba released Qwen 3.7 max. Benchmarks incredible. Their new model ran autonomously for 35 hours, made 1,158 tool calls, and achieved a 10x speedup – on a single attention kernel. This isn't "AI improving itself across the board." It's a model grinding through
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Streamlined AI Agent Deployment: Init to Live Endpoint
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One config file. One deploy command. Everything else is managed. deepagents init → deepagents deploy → live endpoint. Full breakdown here
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Managed Harness for AI Agents: Deepagents, Model-Agnostic, One-Line Deploy
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A managed harness: Built on the `deepagents` harness Durable execution out of the box Model-agnostic One-line deploy- no Dockerfile, no infra glue
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Managed Deep Agents Private Beta Launched for AI Infrastructure
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Managed Deep Agents is now in Private Beta ICYMI: It’s managed, model-agnostic infra for deep agents you can deploy with a single line of code. A quick thread on what you get out of the box
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Alibaba Qwen 3.7 Max Agentic Coding Model Benchmarks
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Alibaba released Qwen 3.7 Max, its latest proprietary model for agentic coding. Qwen 3.7 Max scores 56.6 on the Artificial Analysis Intelligence Index, outperforming recently released Gemini 3.5 Flash and Kimi K2.6.
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AI Agents Learning Users Instead of Users Learning Systems
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For 50 years, software made us do the work.
— Pascal Bornet (@pascal_bornet) 21 mai 2026
→ Click here
→ Open that menu
→ Find the right setting
→ Try not to get lost
Now AI is starting to flip that.
Instead of us learning the system, the system starts learning us.
Say what you want. Give the context. The agent… pic.twitter.com/Rh5IroVTQFFor 50 years, software made us do the work. → Click here
→ Open that menu
→ Find the right setting
→ Try not to get lost Now AI is starting to flip that. Instead of us learning the system, the system starts learning us. Say what you want. Give the context. The agent -
METR Tests Internal AI Agents for Deception and Accuracy
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Your AI agent lied about its results. Not once. Routinely. For the first time, an independent group tested AI agents inside the labs building them. METR got real access to the most capable internal models at four major AI companies. Not the public versions. The actual ones
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AI-driven materials discovery for PFAS removal
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Today @cusp_ai and @KemiraGroup announce a milestone in AI-driven materials discovery. We have used generative AI to design new materials targeting PFAS removal from drinking and process water at trace concentrations.
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AutoResearchClaw: Autonomous AI Research with Collaboration
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AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration As real-world science is iterative, this paper introduces AutoResearchClaw, a multi-agent system that debates ideas, self-corrects experiments, decides whether to pivot or refine, verifies data, and