AI Semiconductors
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6 insights in AI

The Efficiency Inflection: Why Trillion-Parameter Models Cost 100x Less in 18 Months
Let me say a few things that aren't pleasant to hear but need to be said. What's the defining keyword for the foundation model space in 2025? It's "efficiency." Not "bigger," not "stronger" — those t...

From Prediction to Discovery: AlphaFold's $1.7B Deal, 38,000 Verified Materials, and AI's Epistemological Wall
I have always believed one thing: AI's most profound contributions won't happen in the tech industry — they'll happen in laboratories. 2025 was the turning point year for AI for Science, transitionin...

The English Bias Problem: Why NLP's Best Models Lose 30 Points in Every Language But One
I want to begin with a seriously overlooked issue: the mainstream benchmarks in NLP carry a systemic English-centrism bias. FLORES-200 is, to date, the broadest-coverage machine translation benchmark...

Beyond 90% on ImageNet: Gaussian Splatting, Multimodal Vision, and the Gaps That Still Matter
It took me a long time to accept one thing: the volume of data produced annually in computer vision has grown beyond what any single person can comprehensively track. So I chose to track only the numb...

The Silicon Power Struggle: NVIDIA's MFU Reign, AMD's Efficiency Gambit, and the 2nm Wild Card
Before discussing any chip performance data, I need to establish test conditions. Talking about TOPS without specifying power walls, thermal design, and actual workloads is meaningless. The 2025-2026...

The 23% Reality Check: Why Enterprise AI Agent Deployments Are Failing at Scale
I'm not great at pleasantries, so let me lead with the conclusion. The AI Agent space went through a collective disillusionment in 2025. Gartner's Q4 2025 report found that the actual production depl...
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