Research Archive
AI Factories: Reframing Infrastructure from Cost Center to Profit Center
All AI factories are data centers, but not all data centers are AI factories. For much of the last two decades, enterprise infrastructure strategy has been grounded in cost control. Data centers were built to support core IT functions—storage, compute, and networking—with an emphasis on efficiency, uptime, and total cost of ownership (TCO). These environments…
Google Cloud Next 2025: Ironwood TPU, Agent Toolkits, and Google’s vertical advantage
Key Takeaways: Google Cloud unveiled Ironwood (TPUv7), its first inference-optimized TPU, offering massive leaps in compute (5x), HBM capacity (6x), and power efficiency (2x) over the previous generation. Performance is estimated to be within 5% of an Nvidia B200, despite TPUv7’s single primary compute die design. New Agent Development Kit (ADK) and Agent2Agent (A2A) protocol…
We Do Not Have Enough Compute
We are in a huge AI compute shortage right now. At this very moment! When you hear most people talk about this, it’s generally in regards to model scaling and compute scaling for training. Not enough compute so labs can’t scale up the scaling laws. Right now is different, it’s the Ghibilification of AI, there’s…
What’s the difference between Nvidia’s Blackwell family and when do you use them?
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…
Understanding Hyperscaler Custom ASIC Strategy
The GPU vs. Custom ASIC debate is one of the most talked about in our circles of tech executives and investors. It is also a debate that requires more in-depth analysis to fully understand. I want to look at the custom ASIC strategy in two ways relative to this debate. The first is how custom…
The GPU vs. Custom ASIC Competitive Landscape: A Deeper Cost-Performance Analysis
Recent first-party benchmarking data provides crucial insight into the cost-performance dynamics between custom ASICs and GPUs across both training and inference workloads. The data reveals a nuanced competitive landscape where ASICs demonstrate meaningful cost-performance advantages, particularly in inference scenarios, though the implications for market share are more complex than raw performance metrics might suggest. Cost-Performance…