Programming Throwdown

ChatGPT has made a mark on the world as we know it, but that’s only the tip of the AI iceberg. Join us as we discuss how the field of artificial intelligence is growing – including some developments that might not be on your radar!00:00:23 Introductions00:02:01 Jason’s attic adventure00:06:09 Comparing saws00:10:57 Patrick’s surprisingly useful thing00:12:21 SpaceX00:17:31 Human motion diffusion model00:20:47 37Signals00:29:30 Polars00:35:37 Books of the Show00:46:11 Neon00:50:33 Patrick’s player search00:53:47 ChatGPT01:17:12 The threat to Google01:28:06 Jason and Patrick’s future prognostications01:32:13 FarewellsResources mentioned in this episode:Join the Programming Throwdown Patreon community today:  https://www.patreon.com/programmingthrowdown?ty=hNews/Links:SpaceX Starship Static Test Fire Plannedhttps://www.cnet.com/science/space/spacex-prepping-for-first-full-test-fire-of-its-mega-starship-rocket/Human Motion Diffusion Modelhttps://guytevet.github.io/mdm-page/37Signals Leaving the Cloud and Details Cloud Costshttps://twitter.com/dhh/status/1613508201953038337Polars: DataFrames in Rusthttps://docs.rs/polars/latest/polars/index.htmlBook of the Show:Jason: Build by Tony Fadellhttps://amzn.to/3wpLnLWPatrick: Age of Myth by Michael Sullivan (Riyria)https://amzn.to/3HlEsJ5Tool of the Show:Jason: Neon: Serverless Postgres: https://neon.tech/Patrick: 7 Billion Humans (Steam): https://store.steampowered.com/app/792100/7_Billion_Humans/If you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/Reach out to us via email: programmingthrowdown@gmail.comYou can also follow Programming Throwdown on Facebook | Apple Podcasts | Spotify | Player.FM Join the discussion on our DiscordHelp support Programming Throwdown through our Patreon ★ Support this podcast on Patreon ★

Databases are key to almost any project, large or small.  Most database systems in the cloud are designed for heavy use and the costs can get expensive quickly, but database-as-a-service is a rapidly growing area, where many databases can share the same hardware for a much reduced rate, or even for free!  Sam Lambert, CEO of PlanetScale, joins Jason and Patrick to discuss database-as-a-service.00:01:41 Introductions00:02:34 Sam’s Github learning lesson00:07:08 The day after00:10:57 Getting started with databases00:14:21 Schema change difficulties00:19:47 Database transactions00:31:15 Why data recovery matters00:38:35 Planetscale00:49:24 Greetings from the past01:02:01 How Jason discovered Planetscale01:06:53 Branching01:14:00 The vision for Planetscale01:18:12 The rationale behind Planetscale’s work setup01:24:29 Careers at Planetscale01:28:06 Amp It Up01:33:10 FarewellsResources mentioned in this episode:Links:Sam Lambert:Linkedin: https://www.linkedin.com/in/isamlambert/PlanetScale:Website: https://planetscale.com/Twitter: https://twitter.com/planetscaledataLinkedin: https://www.linkedin.com/company/planetscale/Github: https://github.com/planetscaleCareers: https://planetscale.com/careersAmp It Up (Amazon):Paperback: https://www.amazon.com/Amp-Unlocking-Hypergrowth-Expectations-Intensity/dp/1119836115Audiobook: https://www.amazon.com/Amp-Hypergrowth-Expectations-Increasing-Elevating/dp/B09QBRBKFB/If you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/Reach out to us via email: programmingthrowdown@gmail.com You can also follow Programming Throwdown on Facebook | Apple Podcasts | Spotify | Player.FM  Join the discussion on our DiscordHelp support Programming Throwdown through our Patreon ★ Support this podcast on Patreon ★

Machine Learning Engineer is one of the fastest growing professions on the planet.  Liran Hason, co-founder and CEO of Aporia, joins us to discuss this new field and how folks can learn the skills and gain the experience needed to become an ML Engineer!00:00:59 Introductions00:01:44 How Liran got started making websites00:07:03 College advice for getting involved in real-world experience00:12:51 Jumping into the unknown00:15:22 ML engineering00:20:50 The missing part in data science development00:29:16 How to build skills in the ML space00:37:01 A horror story00:41:34 Model loading questions00:47:36 Must-have skills in an ML resume00:50:41 Deciding about data science00:59:08 Rust01:06:27 How Aporia contributes to the data science space01:14:26 Working at Aporia01:16:53 FarewellsResources mentioned in this episode:Links:Liran Hason:Linkedin: https://www.linkedin.com/in/hasuni/Aporia:Website: https://www.aporia.com/Twitter: https://twitter.com/aporiaaiLinkedin: https://www.linkedin.com/company/aporiaai/Github: https://github.com/aporia-aiThe Mom Test (Amazon):Paperback: https://www.amazon.com/Mom-Test-customers-business-everyone/dp/1492180742Audiobook: https://www.amazon.com/The-Mom-Test-Rob-Fitzpatrick-audiobook/dp/B07RJZKZ7FReferences:Shadow Mode: https://christophergs.com/machine%20learning/2019/03/30/deploying-machine-learning-applications-in-shadow-mode/Blue-green deployment: https://en.wikipedia.org/wiki/Blue-green_deploymentCoursera ML Specialization (Stanford): https://www.coursera.org/specializations/machine-learning-introductionAuto-retraining: https://neptune.ai/blog/retraining-model-during-deployment-continuous-training-continuous-testingIf you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/Reach out to us via email: programmingthrowdown@gmail.comYou can also follow Programming Throwdown on Facebook | Apple Podcasts | Spotify | Player.FM Join the discussion on our DiscordHelp support Programming Throwdown through our Patreon ★ Support this podcast on Patreon ★

Patrick and I are always stressing the importance of code reviews and collaboration when developing.  On Freund, co-founder & CEO at Wilco, is super familiar with how code review processes can go well, or become a hinderance. In today’s episode with us, he shares his unique perspective on code reviews and maintaining high code quality!00:00:56 Introductions00:01:38 On’s first exposure to tech00:06:04 Game development adventures00:11:12 The difference between university and real-world experiences00:17:43 A context switch question00:24:41 Points of frustration00:30:53 Build versus Buy complications00:32:06 Code reviews00:39:58 Quality of code00:45:12 Using callouts for the right reasons00:49:57 Code reviews can be too late sometimes00:52:11 Using social interaction as pre-review orientation00:57:03 How not to use code reviews01:01:35 Where Wilco helps programmers learn01:09:11 Working in Wilco01:11:49 FarewellsResources mentioned in this episode:Links:On Freund:Linkedin: https://www.linkedin.com/in/onfreundWilco:Website: https://www.trywilco.com/Twitter: https://twitter.com/trywilcoLinkedin: https://www.linkedin.com/company/trywilco References:Micro-Adventure:https://en.wikipedia.org/wiki/Micro_Adventure If you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/ Reach out to us via email: programmingthrowdown@gmail.com You can also follow Programming Throwdown on Facebook | Apple Podcasts | Spotify | Player.FM Join the discussion on our DiscordHelp support Programming Throwdown through our Patreon ★ Support this podcast on Patreon ★

At scale, anything we build is going to involve people.  Many of us have personal schedules and to-do lists, but how can we scale that to hundreds or even thousands of people?  When you file a help ticket at a massive company like Google or Facebook, ever wonder how that ticket is processed? Sanjay Siddhanti, Akasa’s Director of Engineering, is no slouch when it comes to navigating massive workflow engines – and in today’s episode, he shares his experiences in bioinformatics, workflows, and more with us.00:00:39 Workflow engine definitions00:01:40 Introductions00:02:24 Sanjay’s 8th grade programming experience00:05:28 Bioinformatics00:10:29 The academics-vs-industry dilemma00:16:52 Small company challenges00:18:18 Correctly identifying when to scale00:24:04 The solution Akasa provides00:31:38 Workflow engines in detail00:36:02 ETL frameworks00:45:06 The intent of integration construction00:47:13 Delivering a platform vs delivering a solution00:50:04 Working within US medico-legal frameworks00:53:28 Inadvertent uses of API calls00:55:47 Working in Akasa00:57:09 Interning in Akasa00:58:35 FarewellsResources mentioned in this episode:Sanjay:Twitter: https://twitter.com/siddhantisLinkedin: https://www.linkedin.com/in/sanjaysiddhanti/Akasa:Website: https://www.akasa.comSanjay’s Q&A https://akasa.com/blog/10-questions-for-sanjay-siddhanti-director-of-engineering-at-akasa/Careers: https://akasa.com/careers/Interning: https://www.linkedin.com/jobs/view/research-intern-ai-spring-summer-2023-at-akasa-3206403183/References:Episode 33: Design Patterns:https://www.programmingthrowdown.com/2014/05/episode-33-design-patterns.htmlThe Mythical Man-Month:https://en.wikipedia.org/wiki/The_Mythical_Man-MonthIf you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/Reach out to us via email: programmingthrowdown@gmail.comYou can also follow Programming Throwdown on Facebook | Apple Podcasts | Spotify | Player.FM Join the discussion on our DiscordHelp support Programming Throwdown through our Patreon ★ Support this podcast on Patreon ★

S1: Holiday 2022 SpecialToday we field questions from Programming Throwdown’s listeners about AI, machine learning, and more practical matters as developers in our annual holiday special!00:00:24 Introductions00:00:43 Programming Showdown merch00:02:13 Paul S00:03:28 Dealing with ergonomics00:10:39 On AI coding assistant tools00:16:43 Warren Y00:20:24 Ben inquires about performance testing00:27:39 Wild coding story00:29:37 AI coding’s disruption potential00:34:20 Jason’s Turing riddle00:35:50 ChatGPT00:43:59 Christian B00:45:13 Collection-of-Letters asks on documentation00:49:07 Zeh F00:50:51 Coding books that weren’t that great00:54:40 James K00:57:32 Jeremy S wonders about ML01:00:45 Virtual and live hangouts01:02:09 A retrospective01:07:49 Xu L01:09:22 Showing off the shirts01:11:31 FarewellsIf you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/Reach out to us via email: programmingthrowdown@gmail.comYou can also follow Programming Throwdown on Facebook | Apple Podcasts | Spotify | Player.FM  Join the discussion on our DiscordHelp support Programming Throwdown through our Patreon. Happy holidays from Programming Throwdown to everyone! ★ Support this podcast on Patreon ★

Package managers are an often-overlooked aspect of any operating system, but their importance is not to be underestimated – especially in today’s development environment. As both creator of Homebrew and CEO of tea.xyz, Max Howell is intimately familiar with the ins and outs of open-source development, software engineering, and balancing passion with practicality. He shares these experiences and more with us in today’s deep dive into the subject!00:01:00 Introductions00:01:29 When Max started Tea.XYZ00:03:51 British plugs00:08:10 Literally rolling out of bed to work00:11:49 The value of meetups00:13:14 Getting into open-source00:23:00 Mandrake00:25:02 Turning frustration into action00:30:47 Deno00:40:28 OSX’s relationship with Unix00:55:33 Trying out Ruby01:01:13 April Fools prank ideas01:04:13 The cause of sleepless nights with Homebrew01:14:41 What got Max inspired to do Tea01:19:53 From startup to company01:41:55 FarewellsResources mentioned in this episode:Links:Tea.XYZ:Website: https://tea.xyz/Twitter: https://twitter.com/teaxyz_Instagram: https://www.instagram.com/tea.xyz/Github: https://github.com/teaxyzReddit: https://reddit.com/r/teaxyzDiscord: https://discord.com/invite/KCZsXfJphnReferences:101 on Package Management:https://en.wikipedia.org/wiki/Package_managerDeno:https://deno.land/If you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/Reach out to us via email: programmingthrowdown@gmail.comYou can also follow Programming Throwdown on Facebook | Apple Podcasts | Spotify | Player.FM Join the discussion on our DiscordHelp support Programming Throwdown through our Patreon ★ Support this podcast on Patreon ★

Yonatan Cohen – Co-Founder & CTO of Quantum Machines – joins us in this episode to tackle quantum computing!  Did you know anyone can run quantum programs on Amazon Web Services for mere dollars? Learn about this field early to take pole superposition in the race to understand and use quantum computers!00:00:45 Introductions00:01:20 Yonatan’s beginnings00:03:49 The simulation question00:05:51 How physics led to quantum computing00:14:56 Richard Feynman00:16:44 On the irreversibility of normal computers00:21:25 Logic gates00:25:04 Qubits00:30:11 An example of qubits00:38:19 Why simulating a quantum computer matters00:42:23 NP-complete problems00:48:57 More people at a higher development level are needed00:54:16 Quantum machines in the middle layer01:02:56 Working at Quantum Machines01:05:05 FarewellsResources mentioned in this episode:Links:Quantum Machines:Website: https://www.quantum-machines.co/Careers: https://www.quantum-machines.co/careers/Yonatan Cohen:Linkedin: https://www.linkedin.com/in/yonatan-cohen-10076b113/References:Getting Started with Quantum Computinghttps://builtin.com/software-engineering-perspectives/how-to-learn-quantum-computingIf you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/Reach out to us via email: programmingthrowdown@gmail.comYou can also follow Programming Throwdown on Facebook | Apple Podcasts | Spotify | Player.FM Join the discussion on our DiscordHelp support Programming Throwdown through our Patreon ★ Support this podcast on Patreon ★

In this tour-de-force, Mike Dalessio – Engineering Director at Shopify – and Evan Phoenix – self-described “long-time Rubyist” – join us for a practical discussion of all things Ruby! Ruby is a beautiful language, and we're really excited to cover the history and present of this language with two experts. 00:01:03 Introductions00:01:49 Mike’s Ruby journey00:12:28 Evan’s own Ruby experience00:18:20 The pickaxe book00:20:34 Weird programming interests00:25:11 MINASWAN00:30:33 Language conferences00:36:38 Wrong answers on StackOverflow00:41:53 RubyCentral00:44:50 In-depth examination of Ruby00:47:57 How Shopify sticks to vanilla Rails00:50:28 A tale of two developers00:59:59 Bringing Ruby up to Python’s level01:04:48 Shopify’s largest app monolith01:11:12 Tuning the knobs01:18:01 How not to learn the hard way01:18:57 Opportunities at Shopify01:29:14 Working with the RubyShield program01:32:07 Rails for API servers01:33:21 Mike and Evan’s advice for listeners01:36:00 FarewellsResources mentioned in this episode:Links:RubyCentral:Website: https://rubycentral.org/RubyShield: https://rubycentral.org/ruby-shieldTwitter: https://twitter.com/rubycentralorgShopify:Website: https://www.shopify.com/Careers: https://www.shopify.com/careersDev Degree Program: https://devdegree.ca/pages/programHashiCorpWebsite: https://www.hashicorp.com/Careers: https://www.hashicorp.com/jobsMike Dalessio:Website: http://mike.daless.io/Twitter: https://twitter.com/flavorjonesEvan Phoenix:Website: https://github.com/evanphxTwitter: https://twitter.com/evanphxRubyConf 2022 (Nov. 29 – Dec. 1, 2022):Website: https://rubyconf.org/Other Episodes:Episode 47: RubyShow Link: https://www.programmingthrowdown.com/2015/10/episode-47-ruby.html References:“The Pickaxe Book” aka Programming Ruby: The Pragmatic Programmer’s Guide 2nd Edition:Amazon: https://www.amazon.com/Programming-Ruby-Pragmatic-Programmers-Second/dp/0974514055 If you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/ Reach out to us via email: programmingthrowdown@gmail.com You can also follow Programming Throwdown on Facebook | Apple Podcasts | Spotify | Player.FM  Join the discussion on our DiscordHelp support Programming Throwdown through our Patreon ★ Support this podcast on Patreon ★

Today we discuss adventures, books, tools, and art discoveries before diving into unsupervised machine learning in this duo episode!00:00:22 Introductions00:01:28 Email & inbox organization is very important00:07:28 The Douglas-Peucker algorithm00:11:48 Starter project selection00:17:01 Tic-Tac-Toe 00:21:41 Artemis 100:26:25 Space slingshots00:29:47 Flex Seal tape00:32:38 The Meditations00:37:58 Flour, Water, Salt, Yeast00:40:55 Pythagorea00:46:13 Google Keep00:48:05 Visual-IF00:50:49 Data insights01:03:07 Self-supervised learning01:10:26 A practical example of clustering01:15:10 Word embedding01:24:02 FarewellsWant to learn more? Check out these previous episodes:Episode 27: Artificial Intelligence Theoryhttps://www.programmingthrowdown.com/2013/05/episode-27-artificial-intelligence.htmlEpisode 28: Applied Artificial Intelligencehttps://www.programmingthrowdown.com/2013/06/episode-28-applied-artificial.htmlEpisode 109: Digital Marketing with Kevin Urrutiahttps://www.programmingthrowdown.com/2021/03/episode-109-digital-marketing-with.htmlResources mentioned in this episode:News/Links:Simplify lines with the Douglas-Peucker Algorithmhttps://ilya.puchka.me/douglas-peucker-algorithm/ How to pick a starter projecthttps://amir.rachum.com/blog/2022/08/07/starter-project/Tic-Tac-Toe in a single call to printf()https://github.com/carlini/printf-tac-toe Artemis 1https://www.nasa.gov/artemis-1/Visual-IFhttps://www.visual-if.com/Book of the Show:Jason’s Choice: “The Meditations” by Marcus Aureliushttps://amzn.to/3C3Kg7bPatrick’s Choice: “Flour, Water, Salt, Yeast” by Ken Forkishhttps://amzn.to/3CqFwKaTool of the Show:Jason’s Choice: PythagoreaAndroid: https://play.google.com/store/apps/details?id=com.hil_hk.pythagorea&hl=en&gl=USiOS: https://apps.apple.com/us/app/pythagorea/id994864779Patrick’s Choice: Google Keephttps://keep.google.com/References:Clustering: https://en.wikipedia.org/wiki/Cluster_analysisAutoencoding: https://en.wikipedia.org/wiki/AutoencoderContrastive Learning: https://towardsdatascience.com/understanding-contrastive-learning-d5b19fd96607Matrix Factorization: https://en.wikipedia.org/wiki/Matrix_factorization_(recommender_systems)Stochastic factorization: https://link.medium.com/ytuaUAYBjtbDeep Learning: https://en.wikipedia.org/wiki/Deep_learningIf you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/Reach out to us via email: programmingthrowdown@gmail.comYou can also follow Programming Throwdown on Facebook | Apple Podcasts | Spotify | Player.FM Join the discussion on our DiscordHelp support Programming Throwdown through our Patreon ★ Support this podcast on Patreon ★