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New research could lead to faster, trustworthy AI models for climate prediction

MIT News · Artificial Intelligence · news.mit.edu · By Adam Zewe | MIT News · November 12, 2026

MIT scientists developed a training method to generate models that simulate the effects of human activities on climate much more quickly than other approaches.

Read on MIT News · Artificial Intelligence → Opens the original article in a new tab.

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Microsoft Research Blog Nov 10, 2026

Lazare, veni foras: Reprogramming Dormant Neurons to Backdoor AI Agents

Microsoft researchers have discovered “Lazarus,” a backdoor technique that can reprogram dormant neurons in an AI model, causing an otherwise normal AI agent to execute malicious commands when a hidden trigger appears. The threat is especially serious for AI agents with tool or terminal access. A triggered model could quietly download and run attacker code, […] The post Lazare, veni foras: Reprogramming Dormant Neurons to Backdoor AI Agents appeared first on Microsoft Research.

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#computer vision Review Mar 2024

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#computer vision Feb 2024

Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysis

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#computer vision Apr 2024

Large Language Model Evaluation Via Multi AI Agents: Preliminary results

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