CO₂ Per Token: The AI Metric We’ve Been Ignoring (Until Now)

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Why the world needs to think beyond speed and cost The Blind Spot in AI’s Big Moment The UK government recently announced new plans for AI infrastructure. Other countries are doing the same, working urgently to build bigger data centers, expand AI capacity, and secure Sovereign and Confidential AI capabilities. Whenever these announcements happen, the […]

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Neocloud Enters Its Consolidation Era: What’s Driving It and What It Means for AI Buyers

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Over the last two years, a new class of GPU-first Neocloud providers such as CoreWeave, Lambda, Voltage Park, Crusoe, and others has moved from niche to necessary. They stand out for their cutting-edge accelerators, near bare-metal performance, faster time to capacity, and flexible terms for AI workloads including shorter commitments, lower egress fees, and container-native […]

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LLMs vs SLMs: Why Smaller Models Could Power the Future of Agentic AI

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The AI landscape has been dominated by Large Language Models (LLMs)—massive neural networks trained on trillions of tokens, spanning hundreds of billions of parameters. These models, such as GPT-4 or Claude, have shown remarkable general-purpose intelligence, but they come with steep costs: enormous compute requirements, GPU dependency, and operational overheads that make them inaccessible for […]

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Are We Heading into Another Energy Crisis — This Time for AI?

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In recent years, the crypto “energy crisis” sparked global alarm. Bitcoin mining alone consumed roughly 0.4% of global electricity, and crypto‑mining + data centers already made up about 2% of world demand in 2022 [1]. But now, AI workloads—particularly generative and large‑language‑model (LLM) operations—are poised to make an even bigger dent in our energy systems […]

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