Strong opinions, (bi-)weekly held - with great guests from the C++ community

auto this_episode = episode<48> {
.title = "I Don't Think I Could Code My Way out of a Paper Bag", /*

This week we chat with Frances Buontempo and Andy Balaam about Machine Learning, Artificial Intelligence and Genetic Algorithms.

We learn how ML is mostly just "multiplying and adding up" with a bit of "randomly trying stuff out" but that you might need a kill switch - except when you don't.

We also revive the "C++ Lamentations" debate and try to make an iota of difference.

.links = { "Frances' book, "Genetic Algorithms and Machine Learning for Programmers"", /* Build artificial life and grasp the essence of machine learning. Fire cannon balls, swarm bees, diffuse particles, and lead ants out of a paper bag. */ "Amazon link for Frances' book", "Andy's postcast", /* Movie and tech podcast with "Clueless" Andy Balaam and "Expert" Andy Cockerill */ "Frances' ACCU 2017 keynote", /* It has been said, to err is human, to really foul things up requires a computer [citation needed]. Given the long tradition of AI, which sometimes attempts to make a sentient being from hardware, or body parts (think Frankenstein's monster), are humans unique, or is this dream possible? Or desirable? */ ""Modern" C++ Lamentations", /* The post that kicked off the "modern C++ is un-debuggable" debate */ "Ben Deane's response to "Modern C++ Lamentations"", /* The C++ committee isn't following some sort of agenda to ignore the needs of game programmers, and 'modern' C++ isn't going to become undebuggable. */ "Sean Parent's response to "Modern C++ Lamentations"", /* This post is a response for a number of people who have asked me to give my 2¢ to a large Twitter thread, and post by Aras Pranckevičius, that is rooted in a post by Eric Niebler regarding C++20 standard ranges. */ "Genetic Algorithms (wikipedia)", /* In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on bio-inspired operators such as mutation, crossover and selection. */ "Your Code as a Crime Scene", /* Use Forensic Techniques to Arrest Defects, Bottlenecks, and Bad Design in Your Programs */ "NorDevCon", /* Tech conference in Norwich, UK */ "ACCU Conference", /* Tech (with strong C++ focus) conference in Bristol, UK */ "C++ on Sea" /* Standard ticket pricing ending soon! */ },
.tags = { "genetic algorithms", "ai", "ml", "c++" } };

Released: 22 January 2019
1 hr 3 mins 38 secs

A YouTube stream archive of this recording is also available:

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