The Stack Overflow Podcast

As explained in this piece, "A headless CMS is a back-end only content management system (CMS) built from the ground up as a content repository that makes content accessible via a RESTful API or GraphQL API for display on any device." Shopify has leaned hard into GraphQL and APIs in general. The goal, as Coates describes it, is to allow developers to bring their own stack to the front-end, but provide them with the benefits of Shopify's back-end, like edge data processing for improved speed  at global scale. Shopify also offers a wealth of DevOps tooling and logistical support when it comes to international commerce. We also discuss Liquid, the flexible template language Shopify uses for  building web apps.Our lifeboat badge of the week goes to chunhunghan for answering the question: How to customize the switch button in a flutter?See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

If you're full up on technical content and just want funny retweets, follow Adam on Twitter hereIf you're interested in learning more about tag pages, check out what the community created for Rust.Thanks to Peter Cordes, our lifeboat badge winner of the week, for answering the question: How can I accurately benchmark unaligned access speed on x86_64?See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

You can check out all the details about Collectives in our launch post here.We detailed the user research that allowed our community to help shape this product in a Meta post here.Teresa is on Twitter here and Jascha is on LinkedIn here. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

We chatted with three guests:Miguel Jetté: Head of AI R&DJosh Dong: AI Engineering ManagerJenny Drexler: Senior Speech ScientistWhen Jette was studying mathematics in the early 2000s, his focus was on computational biology, and more specifically, phylogenetic trees, and DNA sequences. He wanted to understand the evolution of certain traits and the forces that explain why our bones are a certain length or our brains a certain size. As it turned out, the algorithms and techniques he learned in this field mapped very well to the emerging discipline of automatic speech recognition, or ASR. During this period, Montreal was emerging as a hotbed for artificial intelligence, and Jette found himself working for Nuance, the company behind the original implementation of Siri. That experience led him to several positions in the world of speech recognition, and he eventually landed at Rev, where he founded the company’s AI department. Jette describes Rev as an “Uber for Transcription.” Anyone can sign up for the platform and earn money by listening to audio submitted by clients and transcribing the speech into text. This means the company has a tremendous dataset of raw audio that has been annotated by human beings and, in many cases, assessed a second time by the client. For someone looking to build an AI system that mastered the domain of speech to text, this was a goldmine. Jette built the earliest version of Rev’s AI, but it was up to our second guest, Josh Dong, to productize and scale that system. He helped the department transition from older technologies like Perl to more popular languages like Python. He also focused on practical concerns like modularity and reusable components. To combine machine learning and DevOps, Dong added Docker containers and a testing pipeline. If you’re interested in the nuts and bolts of keeping a system like Rev’s running at tremendous scale, you’ll want to check out this part of the show. We also explore some of the fascinating future and promise this technology holds in our time with Jenny Drexler. She explains how Rev is moving from a hybrid model—one that combines Jette’s older statistical techniques with Dong’s newer machine learning approach—to a new system that will be ML from end-to-end. This will open up the door for powerful applications, like a single system that can convert speech text across multiple languages in a single piece of audio. “One of the things that's really cool about these end to end models is that basically, whatever data you have, it can learn to handle it. So a very similar architecture can do sequence to sequence learning with different kinds of sequences. The model architecture that you might use for speech recognition can actually look very similar to what you might use for translation. And you can use that same architecture, to say, feed in audio in lots of different languages and be able to do transcription for any of them within one model. It's much harder with the hybrid models to sort of put all the right pieces together to make that happen,” explains Drexler.If you’re interested in learning more about the past, present, and future of artificial intelligence that can understand our spoken language and learn how to respond, check out the full episode. If you want to learn more about Rev or check out some of the positions they have open, you can find their careers page here.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Bligh explains her love for front end and the simple pleasure of bringing a designer’s vision to lifeWe also talk about making the transition from journalism and digital media to the world of software development. You can find her on Twitter here.You can check out Contact here.Learn more about Makers here.Our lifeboat badge winner of the week is Rami Amro Ahmed, who answered the question: What is the difference between Model Factory and a DB seeder in Laravel?See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

You can check out some more of Henley's work on his blog here. Recent pieces include:  A theory of how developers seek information All my career rejections Navigate your code like it's 2021  Why is it so hard to see code from 5 minutes ago? An inquisitive code editor: Overcome bugs before you know you have them How much time does the average developer spend typing in their editor versus researching, exploring, and pondering? Henley believes half an hour of inputting actual code a day is realistic, despite what you've heard about the 10X developer in your area. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

You can find Jenn on Twitter here. She is the creator of the wonderful website, make8bitart.com. You can check out Glitch here and dig into some of its WebXR projects.Our lifeboat badge of the week goes to Ruberandinda Patience, who explained why you got a 404 Not Found, even though the route exist in Laravel.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Karl is interested in the use of low code tools to extend development work beyond the engineering department. He also believes this approach, when done properly, allows teams to release new iterations more rapidly.Check out his company, draft.dev.Follow him on Twitter or LinkedIn.This week's lifefboat badge goes to Günter Zöchbauer, who explained: How to use 2 mixins in State in Flutter? See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Innocent is  a research associate at the MIT Gov /Lab. You can find him on Twitter here.Luke is the Founder and Executive Director of the civic technology organization Grassroot, as a practitioner-in-residence in 2021. You can follow him on Twitter here.Our lifeboat of the week goes to John Rotenstein, who explained: Why some services are called “AWS XXX” and the others “Amazon XXX”. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

You can read more about Spiros on his LinkedIn or Twitter.There is some good backstory on his first company, Log Insight, here. A rundown of the acquisition that led to Spiros joining Splunk is here. There are also some interesting details in Splunk's blog on the deal, which calls out Omnition as a "a stealth-mode SaaS company that is innovating in distributed tracing, improving monitoring across microservices applications."If you enjoy the conversation and want to hear more, Spiros has done some interesting talks that are up on Youtube here.Our lifeboat of the week goes to Willie Mentzel, who explains how to: Round Double to 1 decimal place in kotlin: from 0.044999 to 0.1. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.