Demystifying NPUs: Questions and Answers(thechipletter.substack.com)

91 points by rbanffy 2 years ago | 29 comments

John C. Dvorak on Intel's First Neural Network Chip in 1990(thechipletter.substack.com)

92 points by klelatti 2 years ago | 57 comments

The First 'Apple Silicon' – The Aquarius Processor Project(thechipletter.substack.com)

53 points by tim_sw 3 years ago | 9 comments

RISC on a Chip: David Patterson and Berkeley RISC-I(thechipletter.substack.com)

94 points by lproven 3 years ago | 9 comments

Demystifying GPU compute architectures(thechipletter.substack.com)

173 points by rbanffy 2 years ago | 45 comments

Wafer Scale and Trilogy Systems: Part 1(thechipletter.substack.com)

17 points by signa11 2 years ago | 2 comments

AI has access to a vastly larger working memory than the human brain(davidepiffer.com)

524 points by rzk 2 months ago | 452 comments

A Substack essay by Davide Piffer arguing that AI's edge over mathematicians comes from a vast symbolic working memory rather than superior reasoning.

TPU Deep Dive(henryhmko.github.io)

392 points by transpute 1 year ago | 80 comments

A personal blog post giving a technical deep dive into Google's TPU architecture, its hardware/software co-design, and how it differs from GPUs.

TurboQuant: Redefining AI efficiency with extreme compression(research.google)

495 points by ray__ 7 months ago | 134 comments

Google Research blog post introducing TurboQuant, a method for extreme compression to improve AI model efficiency.

Deep Learning Is Applied Topology(theahura.substack.com)

473 points by theahura 1 year ago | 176 comments

A Substack essay from 12 Grams of Carbon arguing that deep learning is applied topology, explaining how neural networks transform data lying on manifolds.

TPUs vs. GPUs and why Google is positioned to win AI race in the long term(uncoveralpha.com)

375 points by vegasbrianc 11 months ago | 278 comments

A Substack deep dive from UncoverAlpha on Google's TPU chips, covering their technical design, strategic position versus GPUs, and financial implications for AI inference.

What every developer should know about GPU computing(codeconfessions.substack.com)

422 points by Anon84 3 years ago | 149 comments

A Substack primer by Abhinav Upadhyay explaining GPU architecture and computing concepts for software developers familiar mainly with CPUs.