Chipstrat
We’re going to very gently discuss networking and GPUs. It’s an important topic, but it can feel boring or esoteric. Hang with me! Motivation Training an LLM requires a lot of floating point operations (FLOPs): Source How long to train these models? If a single GPU can produce about 2 PetaFLOP/s (2
Industry Insights
This week at HP’s annual Amplify Conference in Nashville, industry leaders are gathering under the theme ‘Driving the Future Together’ to explore how AI is reshaping the future of work. HP unveiled more than 80 new products across its portfolio, making a bold statement about its direction in the AI
AI
Executive Summary Custom CPU development is essential for maximizing the efficiency and performance of accelerated computing architectures. NVIDIA’s strategic approach to CPU design, specifically its purpose-built Arm-based CPUs, delivers significant competitive advantages by addressing the limitati
Chipstrat
Remember Jan 27th when Nvidia lost half a trillion dollars in market cap? An inconspicuous table buried in a paper played a key role: What did this paper actually say? Welcome to the third and final post in a series looking at DeepSeek. Let’s think things through from first principles. We can talk a
Industry Insights
Keeping up my theme of constantly analyzing the battery life of each new Apple M series silicon, I was excited to dive into the new M4 Macbook Air. Every year, gen on gen, Apple continues what their silicon design teams like to call the relentless pursuit of performance per watt. While the M4 is n
Industry Insights
Executive Summary: The Apple Mac Studio featuring the M3 Ultra represents the most powerful AI workstation currently available, tailored specifically toward AI developers’ demanding workflows. With its unprecedented unified memory (up to 512GB) and robust GPU performance, the M3 Ultra Mac Studio exc
Chipstrat
Nvidia’s 2025 earnings call was more revealing than it seemed. Is cost-per-token now the key battleground for AI infrastructure? Why is Nvidia pushing Ethernet, and what does that mean for Infiniband? What happens to aging GPUs? We’ll also explore Nvidia’s positioning against AI ASICs, revenue conce
AI
The GPU vs. Custom ASIC debate is easily one of the most talked about dynamics regarding AI compute infrastructure. I have dug deeply into the debate in this article here (Understanding the Hyper Scaler Custom ASIC Strategy). There is no doubt this is a central question NVIDIA executives get from i
AI
A closer look at NVIDIA’s Q4 earnings call highlights key investor concerns that management tackled head-on throughout the discussion. The conversation sheds light on the company’s strategic direction and how the market perceives its leadership in the rapidly evolving AI infrastructure space. 1. Bla
Industry Insights
The recent unveiling of Amazon’s enhanced Alexa with generative AI capabilities marks a significant milestone in the evolution of home-based AI assistants. As tech companies increasingly focus on generative AI capabilities, Amazon has carefully reimagined its digital assistant while preserving what
Chipstrat
We previously looked at DeepSeek’s reasoning model R1 and distilled variants. I started with the reasoning model because it could upend OpenAI’s business model, which seems to be playing out: Source Why keep reasoning proprietary after DeepSeek’s open weights R1? Yet a lot of investors freaked out b
AI
A few days ago, xAI announced Grok 3 and it’s easily the best LLM I’ve used. Good vibes, great quality, fast token generation, and happened to be trained on the most compute for any model (200,000 H100s). During the stream, Elon Musk said xAI is already working on Grok 4’s data center, which will be