cpp.chat
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++" }
};
