Show Notes
In this episode we invite back our friend Bob Farzin to discuss our personal experiences with using teams of agents to write software, and we try to parse out the experiences we're seeing on the interwebs, including Steve Yegge's GasTown and Wes McKinney's discussion of agentic development in the context of Brooks's _Mythical Man Month_. "Introducing Beads: A coding agent memory system"Welcome to Gas Town — Steve Yegge's original essayThe Future of Coding Agents — Yegge's follow-upGas Town on...
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This week we conclude our discussion of dynamic memory allocation with a discussion of the history and implementation of garbage collectors. There are no mentions of raccoons. Recursive Functions of Symbolic Expressions and Their Computation by Machine, Part I Uniprocessor Garbage Collection Techniques? cpython/InternalDocs/garbage_collector.md at main Generation Scavenging: A Non-disruptlve High Perfornm.nce Storage Reclamation Algorithm 1. Introduction 2. The Relationship Betw Sen...
This week we present the first of two episodes on dynamic memory allocation. We were going to talk about garbage collection, but realized we should probably discuss allocators first. Turns out they are complicated, and there are many different strategies. Dynamic Storage Allocation: A Survey and Critical Review (Wilson) Hoard: a scalable memory allocator for multithreaded applications mimalloc: A new, high-performance, scalable memory allocator for the modern era - Microso...
In this episode we interview Alan Dyke, a colleague of Erik's who got his Ph.D from the University of Wales, Aberystwyth, where he did research on Computer-Aided Software Engineering. We talk about Alan's unique journey in software development, going from the academic environment to the defense industry, embedded software, and biotech. We also learn about the crucial importance of calibrating your software for hurricanes. Send us Fan Mail
This week we're talking about Mike's visit to DataCon LA 26. We talk about the conference, various talks he was able to see, and his own experience giving a talk. Compression Represents Intelligence Linearly [2602.17127] The Emergence of Lab-Driven Alignment Signatures: A Psychometric Framework for Auditing Latent Bias and Compounding Risk in Generative AI Instructor spaCy John Snow Labs Hierarchical Navigable Small Worlds (HNSW) | Pinecone Lance Video is a demonstration platform ...
In this episode we discuss the Monte Carlo method, both the technique and its place in the history of computing. The Monte Carlo method is a set of tools that use probability to solve problems that are otherwise intractable. Programs using Monte Carlo were among the first programs created on digital computers. The Monte Carlo Method Nicholas Metropolis; S. Ulam Journal of the American Statistical Association, Vol. 44, No. 247. (Sep. Equation of State Calculations by Fast Computi...