Mistral Ships 1T-Param Large 4: Le Chonk Open-Weight
Mistral Large 4 (Le Chonk) is a 1-trillion-parameter open-weight MoE model with native multimodal support, two quantized checkpoints, and commercial licensing.
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OpenAI Model Generates 722 Math Proofs
OpenAIs Unreleased Model produced 722 mathematical manuscripts from roughly 4,000 attempted problems, with 162 formally verified proofs, in a single prompting session.
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GitHub Copilot Fusion: Multi-Model Routing Explained
GitHub Copilot Fusion routes coding tasks across AI models automatically using Single, Cascade, and Critique execution patterns with Standard, High, and Max effort levels.
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How AI Models Helped Find and Weaponize PHP2Shell
AI models helped find PHP2Shell, two critical memory-safety flaws lurking in PHP since 5.4. Here is how GPT-5.6 Sol, Gemini 4 Argon, and Wiz Atlas each contributed, and what to patch now.
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ChatGPT for Teens: Why It’s an Unacceptable Risk
Common Sense Media rated ChatGPT for Teens an unacceptable risk after testing more than 4,000 prompts. Here is what the finding means and what parents should do now.
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AI Agent Automates Windows PC Setup
An AI agent automates Windows PC setup by auditing current state, generating a risk-labeled plan, and executing approved steps through PowerShell and package managers for a reproducible workflow.
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OpenAI GPT-6 Launches Intelligent UI Across ChatGPT
OpenAI's GPT-6 With Intelligent UI adapts response formats automatically across all ChatGPT plans, with GPT-6 Sol for paid tiers and GPT-6 Luna for Free and Go users.
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Why Top AI Models Fail at Inventing Research Methods
Recent evaluations show top AI models handle research execution well but fail to originate new methods, exposing a wide gap between engineering skill and scientific creativity.
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10 Minutes of AI Use May Erode Human Persistence
A 2026 study found that about 10 minutes of AI assistance measurably reduces persistence on difficult tasks. Here's what it means for how you work with AI.
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Running a 744-Billion Parameter LLM in a Home Lab
Learn how quantization, CPU offloading, and distributed inference make running a 744-Billion Parameter LLM on consumer hardware a practical engineering project.
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