AI Briefings

Field notes on agents, infrastructure, policy, and production wins—curated without sensationalism.

Oct 6, 20255 min read

The Infrastructure Race Heats Up: AMD's 6-Gigawatt Bet and the Hidden Costs of AI's Growing Pains

As OpenAI commits to deploying 6 gigawatts of AMD GPUs and developers grapple with AI-generated code vulnerabilities, the AI industry faces a critical infrastructure and security reckoning.

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Oct 5, 20255 min read

The Reinforcement Learning Divide: Why AI Progress Is Becoming Uneven

As reinforcement learning accelerates progress in specific AI domains, a technical gap is emerging that could reshape which AI capabilities advance—and which get left behind.

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Oct 5, 20255 min read

The Great AI Capital Shift: How Machine Learning Crossed the 50% Threshold in Venture Funding

For the first time in startup history, AI companies are capturing more than half of all venture capital dollars, fundamentally reshaping what gets funded and built.

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Oct 4, 20252 min read

AI Reshapes Drug Discovery as MIT and McMaster Map Antibiotic Mechanism with Machine Learning

A breakthrough in AI-assisted drug discovery demonstrates how machine learning can dramatically accelerate understanding of drug mechanisms, while major tech players position for AI's next phase.

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Oct 3, 20253 min read

AI Industry Shifts: OpenAI's Consumer Focus and Novel Hardware Challenges Nvidia

Major players are repositioning with OpenAI acquiring consumer AI talent while a new hardware startup threatens Nvidia's AI chip dominance.

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Oct 3, 20252 min read

AI Research Shifts from Models to Agents: Multi-Agent Systems Show Promise in Drug Discovery and Scientific Research

Recent developments show a clear pivot toward multi-agent AI systems that can collaborate, reason, and conduct autonomous research, with particular breakthroughs in drug discovery and scientific automation

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Oct 3, 20252 min read

AI Infrastructure Race Intensifies: MIT, Google, and Anthropic Make Strategic Moves

Major tech players are making billion-dollar bets on AI infrastructure while new research suggests ways to make AI systems more efficient and practical.

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