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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 - Microsoft Research
A Scalable Concurrent malloc(3) Implementation for FreeBSD

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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.

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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 for analyzing and searching video content with LanceDB. · GitHub

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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 Computing Machines
Hitting the Jackpot: The Birth of the Monte Carlo Method | LANL
Monte Carlo Sampling Methods Using Markov Chains and Their Applications W. K. Hastings Biometrika, Vol. 57, No. 1. (Apr., 1970),
2014HaighPriestleyRope-LosAlamosBetsonENIAC.pdf
The Unheralded Contributions of Klara Dan von Neumann

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In this episode we discuss the 5 most-cited papers from the flagship journal of the Association for Computing Machinery, the JACM.   The papers include everything from distributed computing to real-time scheduling. 
Direct Search'' Solution of Numerical and Statistical Problems | Journal of the ACM 
Impossibility of distributed consensus with one faulty process | Journal of the ACM 
Robust principal component analysis? | Journal of the ACM 
Authoritative sources in a hyperlinked environment | Journal of the ACM 
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment | Journal of the ACM

What is HITS Algorithm (Hyperlink-Induced Topic Search)?

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