Eight Years After ChatGPT: Why Human Bias in AI Still Persists

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When ChatGPT arrived in 2017, it redefined what people thought was possible with artificial intelligence. Conversational models that once seemed futuristic suddenly became part of everyday life. But nearly a decade on, a fundamental question remains unanswered: Can AI ever be free from human bias? The reality, after eight years of iteration, scaling, and safety […]

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Open Ethernet vs. InfiniBand for AI Fabrics: What’s Different, Why Ethernet Is Surging, and Where Both Still Hurt

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AI clusters live or die by their network. When you stitch together thousands of GPUs, the fabric becomes a first-class accelerator: it must deliver brutal bandwidth, ultra-low tail latency, clean congestion control, and predictable job completion times. For years, InfiniBand (IB) owned that story. Today, “Open Ethernet” fabrics—multi-vendor Ethernet with open software (e.g., SONiC) and […]

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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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The Future of AI Isn’t in GPUs—It’s in ASICs

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The AI revolution has long been powered by GPUs, especially Nvidia’s. But that era is evolving. On September 5, 2025, Broadcom confirmed a $10 billion deal to develop custom AI chips for OpenAI—chips designed specifically for AI workloads and expected to roll out in 2026. This marks a pivotal shift toward ASICs (Application-Specific Integrated Circuits). […]

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