Linux Inlaws

Ever wondered what Google really knows about you (this applies to other big tech companies as well) and how to prevent this unsolicited gathering of information (to avoid the nasty term "spying"), this is the episode you want to listen to. And of course the rest of the back catalog of shows you carefully managed to avoid so far as you were of the opinion that other drugs are better suited to put you to sleep in no time. But weren't aware of the side effects. Now for the good news: As Linux Inlaws doesn't have any side effects (apart from furthering your knowledge of course), there's no package insert (hooray! :-).
Links

Edward Snowden: https://en.wikipedia.org/wiki/Edward_Snowden

Julian Assange: https://en.wikipedia.org/wiki/Julian_Assange

1984: https://openlibrary.org/works/OL1168083W/Nineteen_Eighty-Four

Tesla's EULA: https://www.tesla.com/legal/privacy

GoC's episode on electric cars (S2Ep2): https://grumpy-old-coders.org/#episodes

LineageOS: https://lineageos.org

AOSP @ Linux Inlaws (S02E38): https://archive.org/details/LI_S02E38_Android_and_more__7F48

Tor Browser Bundle: https://www.torproject.org/download/tor

The Tor episode (S01E75): https://archive.org/details/LI_S01E75_The_Onion_Router_Network__EE74

Google's Chrome shenanigans: https://www.forrester.com/blogs/google-chrome-settlement-shows-the-power-of-privacy-minded-consumers

Tails: https://tails.net

/e/OS/: https://e.foundation

GrapheneOS: https://grapheneos.org

The focus of this episode is a little unknown project by the name of Kodi, formerly known as XBMC. Powering approximately 75% of the world's hotel set-top boxes alone (wild guess :-), this codebase has come a long way since its inception more than 20 years ago. Chris and Martin have a panel of coredevs at the ready, ready to spill the beans and much more. Subjects range from esoteric programming languages such as C++, world domination (no surprises there! :-) and how to get there (as the brochure looks nice) and more. Much more. And FLOSS licenses. Curious what this blatant teaser is all about? Then don't miss this show!
Links

Kodi: https://kodi.tv

Xbox: https://en.wikipedia.org/wiki/Xbox

OSMC: https://osmc.tv

LibreELEC: https://libreelec.tv

Kodi Foundation: https://kodi.tv/about/foundation

DMCA: https://en.wikipedia.org/wiki/Digital_Millennium_Copyright_Act

Open Web OS: https://www.webosose.org

Kodi @ Github: https://github.com/xbmc/xbmc

Pennyworth: https://www.imdb.com/title/tt8425532

Rowan's LinkedIn post: https://www.linkedin.com/posts/rowant_no-hallucinations-activity-7403957717943394304-rW1S?utm_source=share&utm_medium=member_desktop&rcm=ACoAAACoKugBJZ6YDktj_4vqLoah1AT9rQk2eqM

History is the subject of this episode. So if you ever wondered what happened roughly 13 billion years ago (give or take a few), this episode is for you. Almost. As post-production advised us (to avoid the nasty term "try on your new shoes made from concrete in the middle of the ocean), we had to narrow this down to the history of a particular subject. So sparing no expenses never mind wisdom we chose artificial intelligence. As we are still struggling with the natural type of this anyway. So without further ado, let's get right into it. Word of caution: As usual, please be advised that listening to this show while driving, operating heavy machinery or other activities requiring your concentration and attention may not be a good idea. You have been warned! Plus bonus content about Skynet and winters of the AI persuasion (we desperately hope that at least this got your attention :-). And dolphins of course.
Links

Alan Turing's paper on AI: https://academic.oup.com/mind/article/LIX/236/433/986238?login=false

Pavlov and classical conditioning: http://www.scholarpedia.org/article/Classical_conditioning

Overview of machine learning: https://en.wikipedia.org/wiki/Machine_learning#Approaches

History of artificial intelligence: https://www.ibm.com/think/topics/history-of-artificial-intelligence

PageRank I: https://www.google.com/search/howsearchworks/how-search-works/ranking-results/

PageRank II (including lots of math): https://www.ams.org/publicoutreach/feature-column/fcarc-pagerank

DeepMind: https://deepmind.google

Elon Musk & World Domination: https://www.youtube.com/watch?v=-1bnCHWou9A

LLMs: https://pmc.ncbi.nlm.nih.gov/articles/PMC11645129

Expert systems: https://en.wikipedia.org/wiki/Expert_system

Skynet: https://en.wikipedia.org/wiki/Skynet_(Terminator)

Person of interest: https://www.imdb.com/title/tt1839578/?ref_=fn_t_1

Meta's Llama: https://www.llama.com

This episode features an update on MongoDB. For those listeners old enough to remember: We had the project on the show a few years back. Much has changed since then - or has it? Stay tuned to find out. But even if you don't know what MongoDB is about but always wanted to dip your toes in the NoSQL waters of document databases and such, this episode is for you! Plus the usual nonsense about vector databases, language models (large, small or medium if size does matter indeed) and all the rest of it. Enjoy!
Links

MongoDB: https://github.com/mongodb/mongo

Previous MongoDB episode (S01E90): https://archive.org/details/LI_S01E90_MongoDB_with_a_slight_marketing_angle___999A

Vectors and artificial intelligence: https://medium.com/@myscale/understanding-vector-indexing-a-comprehensive-guide-d1abe36ccd3c

TIOBE index: https://www.tiobe.com/tiobe-index

SEAL Team: https://www.imdb.com/title/tt6473344

Red Cliff: https://www.imdb.com/title/tt0425637/?ref_=fn_all_ttl_1

Red Cliff II: https://www.imdb.com/title/tt1326972/?ref_=fn_all_ttl_2

This episode is witness to our two ageing heroes taking a closer look at the mysterious and wonderful world of esoteric programming languages. So if you ever wanted to know what Brainfuck is really all about (but were too afraid to ask selected members of your family never mind your computer science lecturer), wanted to find out where Forth and Prolog are really used never mind what Zig is all about - you don't want to miss this episode. Plus a trip down memory lane (if our two heroes can remember where to find this memory lane thing).
Links

Prolog: https://en.wikibooks.org/wiki/Prolog

Zig: https://ziglang.org

Forth: https://forth-standard.org

Open Firmware: https://en.wikipedia.org/wiki/Open_Firmware

Sinclair ZX81: https://en.wikipedia.org/wiki/Zx-81

MUMPS: https://www.cs.uni.edu/~okane

Brainfuck: https://brainfuck.org

Ook!: https://esolangs.org/wiki/Ook!

Whitespace: https://web.archive.org/web/20150618184706/http://compsoc.dur.ac.uk/whitespace/tutorial.php

Bull$hit: https://github.com/jkstpierre/Bullshit-Programming-Language

Alan Turing: https://www.newscientist.com/people/alan-turing

ArnoldC: https://github.com/lhartikk/ArnoldC

Esolang: https://esolangs.org/wiki/Main_Page

Omgrofl: https://github.com/OlegSmelov/omgrofl-interpreter

Chef: https://esolangs.org/wiki/Chef

Oxyde: https://oxyde.cloud