IT Strategy & Transformation Insights

Expert perspectives on technology leadership, project architecture, and cross-departmental collaboration

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Strategic perspectives from Nick Hume's 20+ years of experience in technology leadership

From Silicon to Token

The world of large‑language‑model inference moves fast. Meta’s Llama 4 and DeepSeek's range of models turns yesterday’s “good enough” hardware into today’s bottleneck, so picking the right platform is more strategic than ever. I compared eight options that keep popping up in various engineering and sales conversations, including consumer RTX GPUs, Apple Silicon, NVIDIA’s H‑series, Groq’s purpose‑built LPU, Cerebras’ wafer‑scale engine, and turnkey DGX workstations. Each proves valuable in th

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Here come the Inferencing ASIC's

The tidal wave of Generative AI (GenAI) has mostly consisted of training large language models (LLM's), like GPT-4, and the huge amount of compute needed to process these enormous datasets, e.g. GPT-4 has 1.76 trillion parameters. This compute has mainly looked like NVIDIA's GPUs, but you also need... 1. power 2. networking 3. capital, AND 4. a nice cool place to host them (data center) The looooooong tail of AI Inferencing will dictate that compute is installed closer to where it's neede

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Blog

GTC 2024 post-conference

Upon returning from GTC24, I've been able to reflect on all the new updates across NVIDIA's platforms and below is a summary of the various announcements. Blackwell was the star of the show, with the B100, B200 and GB200 chips announced. Note that there were no consumer facing graphics cards (RTX) were named, nor was there a successor to the L40S or BlueField3 DPU (though there was a new ConnectX8 NIC). As always though, a little bit of devil is in the details - as well as marketing waxing lyr

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