Tag: hardware

Vector search has hit a physical wall. Explore why CPU-bound indexing fails at scale and how FPGAs and custom ASICs are redefining the database layer.

The economic case for deploying local LLMs to eliminate API costs and latency. Why relying entirely on cloud inference is a massive tax on your margins.

We have hit the physical limits of what a single chip can do. The new unit of compute for AI infrastructure isn't the GPU; it's the fully integrated rack.

Why Patch Size fundamentally dictates your cloud throughput entirely independently of actual parameter count when deploying Vision Transformers in production.

This post contrasts the switching technologies of NVIDIA and Google's TPUs. Understanding their different approaches is key to matching modern AI workloads, which demand heavy data movement, to the optimal hardware.

It's not just about specs. This post breaks down the core trade-off between the GPU's versatile power and the TPU's hyper-efficient, specialized design for AI workloads.