optimization

In Ars Technica's War Stories, Naughty Dog co-founder Andy Gavin explains how the team squeezed Crash Bandicoot onto the original PlayStation. They overwrote Sony library code in RAM, built custom animation compression, and streamed assets around slow seek times.

A long Machine Learning Street Talk interview with Kenneth Stanley, creator of NEAT and novelty search, about his book on why greatness cannot be planned. They discuss open-endedness, the tyranny of objectives, serendipity and the evolution of ideas.

Part two of a Computer History Museum oral history with Gary Davidian, covering his work on the 68000 emulator for PowerPC at Apple, Power Computing, clean-room contracting and later performance optimization work. It is nearly three hours long.

Lex Fridman interviews Jeff Hawkins, founder of Numenta and author of On Intelligence, about the Thousand Brains Theory and reverse-engineering the neocortex. They also cover Hierarchical Temporal Memory and brain-inspired AI architectures.

A 2023 University of Toronto conversation between Geoffrey Hinton and Fei-Fei Li on responsible AI development. They look back at the history of deep learning and ImageNet and discuss the ethics and risks of AI.

A 42-minute CBS interview with Geoffrey Hinton at the Vector Institute in 2023, covering the history of neural networks and the present and future of AI. He discusses AGI timelines and whether language models truly understand.

Lex Fridman interviews Chris Lattner, creator of LLVM, Clang and Swift, about compilers, Swift for TensorFlow, TPUs and ML accelerators. The talk covers how hardware and software meet to produce efficient code.

Grady Booch interviews John Backus, who led the IBM team that created FORTRAN in 1957, for the Computer History Museum in 2006. Backus describes the development of the first successful high-level language and its compiler. The interview runs 88 minutes.

An interview with Anders Hejlsberg, lead architect of TypeScript, about porting the TypeScript compiler to Go. He covers the 10x type-checking speedup, lower memory use, and why Go was chosen.

Developer Voices interviews Chris Lattner about Mojo, a Python-compatible language aimed at CPU/GPU performance built on LLVM and MLIR. It covers performance features, the type system and why Mojo uses Python syntax.

Lex Fridman's long interview with Chris Lattner, creator of LLVM and Swift, covering the future of computing and programming languages. It touches on compilers, hardware, and his work at Apple, Tesla, Google and SiFive.

Dwarkesh Patel interviews Richard Sutton, reinforcement learning pioneer, Turing Award winner and author of The Bitter Lesson. Sutton argues LLMs are a dead end because they cannot learn on the job, and that continual learning from experience will require a new architecture.

A Ray Summit 2022 keynote fireside chat between OpenAI's Greg Brockman and Anyscale's Robert Nishihara. They discuss how OpenAI's training infrastructure evolved and its use of Ray.

Dwarkesh Patel interviews Andrej Karpathy on why reinforcement learning is flawed, why AGI may blend into steady GDP growth, why self-driving took so long, and the future of education. The conversation runs about two and a half hours.

ThePrimeagen interviews Chris Lattner, creator of LLVM, Clang, Swift and Mojo, with TJ DeVries, in a long live-streamed conversation. They discuss language design and Lattner's experience building Swift.