Richard Ho on Custom AI Chips, Inference Economics, CUDA, and AI-Assisted Engineering.
Tag: hardware
The Bloomberg Terminal for AI Compute
Steve Hou GPU Rental Rates, Token Price Trends, AMD’s Inference Push, and the AI Bubble.
Breaking the Memory Wall in the Age of Inference
Sid Sheth on Memory Bottlenecks, SRAM vs HBM, Digital In-Memory Compute, and the Future of Inference Hardware.
Beyond GPUs: Cerebras’ Wafer-Scale Engine for Lightning-Fast AI Inference
Hagay Lupesko on Wafer-Scale Architecture, High-Speed Inference, Enterprise AI, and Advanced Reasoning.
Bridging the Hardware-Software Divide in AI
Jay Dawani on A New Software Stack for AI Development.
TinyML, Sensor-Driven AI, and Advances in Large Language Models
Pete Warden on Revolutionizing Human-Device Interaction.
LLMs on CPUs, Period
Nir Shavit on tools for sparsifying and quantizing LLMs for efficient CPU inference.
Redefining AI Infrastructure: Deploying and Developing with a Next-Generation Developer Platform
Tim Davis on a programming language for AI, an efficient, user-friendly inference engine for seamless model execution.
The Rise of Custom Foundation Models
Andrew Feldman on How Enterprises Are Building and Deploying Their Own Foundation Models.
Bringing AI and computing closer to data sources
The Data Exchange Podcast: Bruno Fernandez-Ruiz on the current state of edge computing.