Google has been releasing a ton of new GenAI functionality under the name “Gemini”, and they’ve officially rebranded Bard as Gemini. We take some time to talk through Gemini compared with offerings from OpenAI, Anthropic, Cohere, etc.

We also discuss the recent FCC decision to ban the use of AI voices in robocalls and what the decision might mean for government involvement in AI in 2024.

This week we’re talking to Daniel J. Barrett, author of Efficient Linux at the Command Line as well as many other books. Daniel has a PhD and has been teaching and writing about Linux for more than 30 years (almost 40!). So we invited Dan to join us on the show to talk about efficient ways to use Linux. He teaches us about combining commands, re-running commands, $CDPATH hacks, and more.

WestArtFactory’s premium PCB cheat sheets, Maxime Topolov tells of a disappearing AWS dev, Juspay Technologies releases HyperSwitch for payment processing, Servo gets new funding for 2023 & Cloudflare’s open source Wildebeest.

The new open source AI book from PremAI starts with “As a data scientist/ML engineer/developer with a 9 to 5 job, it’s difficult to keep track of all the innovations.” We couldn’t agree more, and we are so happy that this week’s guest Casper (among other contributors) have created this resource for practitioners.

During the episode, we cover the key categories to think about as you try to navigate the open source AI ecosystem, and Casper gives his thoughts on fine-tuning, vector DBs & more.

You might have heard that “AI is only as good as the data.” What does that mean and what data are we talking about? Chris and Daniel dig into that topic in the episode exploring the categories of data that you might encounter working in AI (for training, testing, fine-tuning, benchmarks, etc.). They also discuss the latest developments in AI regulation with the EU’s AI Act coming into force.

Dennis E. Taylor joins the show to take us “Into the Bobiverse” and other books he’s written. Dennis shares the backstory on how he went from programmer to author/writer and creator of Audible’s Best Science Fiction Book of 2016, his process for iterating and developing the story as he writes, plans for a Bobiverse movie, and what’s next in book 5 coming out in September 2024.

Reorx lists awesome apps & tools using the new ChatGPT API, Ernie Smith ranks self-hosted app alternatives, Very Good Ventures brings Dart to the server, Daniel Stenberg tells curl’s NuGet story & Hacker Stations showcases tech workspace setups from all over the world.

Jerod and Adam talked with Rich Harris –a JavaScript Journalist on The New York Times Investigations team– about his magical disappearing UI framework called Svelte. We compare and contrast Svelte to React, how the framework is embedded in a component, build time vs. run time, scoping CSS to components, and CSS in JavaScript. Rich also shares where Svelte v3 is heading and the details on Sapper, a framework for building extremely high-performance progressive web apps, powered by Svelte.

This week Daniel & Chris hang with repeat guest and good friend Demetrios Brinkmann of the MLOps Community. Together they review, debate, and poke fun at the 2024 Gartner Hype Cycle chart for Artificial Intelligence. You are invited to join them in this light-hearted fun conversation about the state of hype in artificial intelligence.

In this Fully Connected episode, Daniel and Chris explore recent highlights from the current model proliferation wave sweeping the world - including Stable Diffusion XL, OpenChat, Zeroscope XL, and Salesforce XGen. They note the rapid rise of open models, and speculate that just as in open source software, open models will dominate the future. Such rapid advancement creates its own problems though, so they finish by itemizing concerns such as cybersecurity, workflow productivity, and impact on human culture.

Chris & Daniel are out this week, so we’re bringing you a panel discussion from All Things Open 2023 moderated by Jerod Santo (Practical AI producer and co-host of The Changelog) and featuring keynoters Emily Freeman and James Q Quick.

Jerod is joined by Chris and Desmond (co-hosts of the ElixirTalk podcast) to catch up on what’s moving and shaking in the Elixir and Phoenix communities. We discuss what’s attractive about Elixir, what it means to have the language finalized, why folks are so excited by Phoenix LiveView, the ambitious new Lumen project that’s bringing Elixir to WebAssembly, and more.

Ellie Huxtable’s Atuin makes your shell history magical, Dmitry Kudryavtsev writes why he thinks engineers should focus on writing, LazyVim promises to transform your Neovim setup into a full-fleged IDE, Geoff Graham shares with Smashing Magazine how he writes CSS in 2023 & Brad Fitzpatrick collects a public list of bad issue track behaviors.

There are a ton of problems around building LLM apps in production and the last mile of that problem. Travis Fischer, builder of open AI projects like @ChatGPTBot, joins us to talk through these problems (and how to overcome them). He helps us understand the hierarchy of complexity from simple prompting to augmentation, agents, and fine-tuning. Along the way we discuss the frontend developer community that is rapidly adopting AI technology via Typescript (not Python).

This week Adam talks with Marcin Kurc about chasing the 9s. Marcin is the Co-founder and CEO of Nobl9 where they build tools for managing service level objectives, aka SLOs. We also talk about service level agreements (SLAs), service level indicators (SLIs), error budgets, and monitoring, and how it all comes together to help teams align on goals, improve customer satisfaction, manage risks, increase transparency, and of course, a favorite around here…continuous improvement. Kaizen! This is an awesome deep dive into the world of chasing those 9s, and how teams are levering SLOs to earn the trust of their customers as well showcase transparency.

How do you systematically measure, optimize, and improve the performance of LLM applications (like those powered by RAG or tool use)? Ragas is an open source effort that has been trying to answer this question comprehensively, and they are promoting a “Metrics Driven Development” approach. Shahul from Ragas joins us to discuss Ragas in this episode, and we dig into specific metrics, the difference between benchmarking models and evaluating LLM apps, generating synthetic test data and more.

Ken Thompson’s 75-year-project is a jukebox for the ages, Tabby is a self-hosted AI coding assistant, Codeberg is a collaboration platform and Git hosting for open source software, content and projects, TheSequence explains The LLama Effect & Paul Orlando writes about Ghosts, Guilds and Generative AI.

Sahn Lam details Stack Overflow’s monolith/on-prem architecture, Hillel Wayne asks the Lobsters community for killer libraries, Linux 6.2 is ready to run on M1 Macs thanks to Asahi Linux, Johan Halse writes up what to expect from your web framework & Eli Bendersky on using GoatCounter for blog analytics.

Seems like we are hearing a lot about GraphRAG these days, but there are lots of questions: what is it, is it hype, what is practical? One of our all time favorite podcast friends, Prashanth Rao, joins us to dig into this topic beyond the hype. Prashanth gives us a bit of background and practical use cases for GraphRAG and graph data.

This week we’re talking about open source industrial machines. We’re joined by Marcin Jakubowski from Open Source Ecology where they’re developing open source industrial machines that can be made for a fraction of commercial costs, and they’re sharing their designs online for free. The goal is to create an efficient open source economy that increases innovation through open collaboration. We talk about what it takes to build a civilization from scratch, the Open Building Institute and their Eco-Building Toolkit, the right to repair movement, DIY maker culture, and how Marcin plans to build 10,000 micro factories worldwide where anyone can come and make.

We’re excited to have Tuhin join us on the show once again to talk about self-hosting open access models. Tuhin’s company Baseten specializes in model deployment and monitoring at any scale, and it was a privilege to talk with him about the trends he is seeing in both tooling and usage of open access models. We were able to touch on the common use cases for integrating self-hosted models and how the boom in generative AI has influenced that ecosystem.

Large Language Models (LLMs) continue to amaze us with their capabilities. However, the utilization of LLMs in production AI applications requires the integration of private data. Join us as we have a captivating conversation with Jerry Liu from LlamaIndex, where he provides valuable insights into the process of data ingestion, indexing, and query specifically tailored for LLM applications. Delving into the topic, we uncover different query patterns and venture beyond the realm of vector databases.

This week we’re talking about the future of freeCodeCamp with Quincy Larson and what it’s taken to build it into the non-profit unicorn that it is. They’re expanding their Python section into a full-blown data science curriculum and they’ve launched a $150,000 fundraiser to make it happen with 100% dollar-for-dollar matching up to the first $150,000 thanks to Darrell Silver.

As you may know, we’re big fans of Quincy and the work being done at freeCodeCamp, so if you want to back their efforts as well, learn more and donate.

It seems like everyone is interested in Rust these days. Even the most popular Python linter, Ruff, isn’t written in Python! It’s written in Rust. But what is the state of training or inferencing deep learning models in Rust? In this episode, we are joined by Nathaniel Simard, the creator burn. We discuss Rust in general, the need to have support for AI in multiple languages, and the current state of doing “AI things” in Rust.

Jerod & Adam share our Zulip first impressions, react to Elasticsearch going open source (again), discuss Christian Hollinger’s blog post on why he still self-hosts & answer a listener question: how do we produce podcasts?

Erez Zukerman shares the story of launching the ErgoDox EZ on Indiegogo (May 2015), what it takes to create customizable ergonomic keyboards, the benefits of split keyboards and custom key layouts, repairability and longevity, community engagement, and the attention to detail required in everything they create. We talk through their keyboard lineup, our personal experience with how we mouse and keyboard…we cover it all.

Perry Mitchell joined the show to talk about the importance of password management and his project Buttercup — an open source password manager built around strong encryption and security standards, a beautifully simple interface, and freely available on all major platforms. We talked through encryption, security concerns, building for multiple platforms, Electron and React Native pros and woes, and their future plans to release a hosted sync and team service to sustain and grow Buttercup into a business that’s built around its open source.

Adam was out when Bryan made his podcast debut here on The Changelog, so we had to get him back on the show along with his co-founder and CEO Steve Tuck to discuss Silicon Valley (the TV show), all things Oxide, homelab possibilities, bringing the power of the cloud on prem, and more.

Emily Freeman joins the show alongside our Ship It co-host, Justin Garrison! We hear Emily’s burnout story & learn how she and Forrest Brazeal are putting tech-focused influencers on tap. But first: area code turf wars, bad movie reboots & buying used DVDs… at Starbucks?!

This week we’re talking with Gregory Kurtzer about Rocky Linux. Greg is the founder of the CentOS project, which recently shifted its strategy and has the Linux community scrambling. Rocky Linux aims to continue where the CentOS project left off — to provide a free and open source community-driven enterprise grade Linux operating system. We discuss the history of the CentOS project, how it fell under Red Hat’s control, the recent shift in Red Hat’s strategy with CentOS, and how Rocky Linux is designed to be 100% bug-for-bug compatible with Red Hat Enterprise Linux.