Podcasts about c sharp

C# si fa leggero!In questa puntata esploriamo 'dotnet run app.cs', la nuova funzionalità di .NET 10 che permette di scrivere ed eseguire script C# senza creare un progetto.Un solo file .cs, niente .csproj, e puoi partire subito: perfetto per prototipi, automation e piccoli tool da riga di comando. Scopri come funziona, cosa puoi farci e perché potrebbe diventare il tuo nuovo modo di usare C#.https://devblogs.microsoft.com/dotnet/announcing-dotnet-run-app/https://youtu.be/98MizuB7i-w?si=pguTqEmNOECnssPuhttps://devblogs.microsoft.com/visualstudio/agent-mode-has-arrived-in-preview-for-visual-studio/#dotnet #copilot #dotnetinpillole #podcast

Nel mondo delle applicazioni moderne, ogni ciclo di CPU e ogni allocazione contano. In questa puntata esploriamo Span e ReadOnlySpan, due strumenti introdotti in .NET Core 2.1 che permettono di lavorare con la memoria in modo sicuro ed estremamente efficiente.https://devblogs.microsoft.com/dotnet/welcome-to-c-7-2-and-span/https://learn.microsoft.com/en-us/dotnet/standard/memory-and-spans/memory-t-usage-guidelineshttps://learn.microsoft.com/en-us/shows/visual-studio-connect-event-2017/t125https://learn.microsoft.com/en-us/archive/msdn-magazine/2018/january/csharp-all-about-span-exploring-a-new-net-mainstay#dotnet #csharp #span #dotnetinpillole #podcast

Jerry Nixon is a Principal Program Manager on the SQL Server team focused on the Data API builder. He's also a fanatic for #CSharp, #StarTrek, and Etymology. He also serves as a professor at Colorado Christian University.   Topics of Discussion: [3:34] Why Jerry describes his life as a pearl necklace. [5:15] Jerry recommends the book Never Eat Alone and the importance of community. [6:01] How engineers and parenting are aligned. [7:02] Jerry reflects on Microsoft's history of evangelism, the rise of “opinionated” frameworks, and how .NET Aspire revives a form of proven prescriptive guidance. [9:35] Prescriptive guidance. [12:03] The inevitable evolution of .NET Aspire and how it simplifies container-based development by handling orchestration behind the scenes. [16:56] Paying more attention and awareness to the developer community. [18:30] How GraphQL fits into the Data API Builder experience, giving developers flexibility without needing to write complex backends. [21:40] Jerry talks about community feedback on Data API Builder and how real-world use cases help prioritize features and fix gaps in tooling. [31:02] Jerry's perspective on building container-based solutions. [32:15] Data API Builder's community involvement and upcoming features. [36:15] Docker Desktop. [38:58] The architectural concept of Data API Builder. [44:42] C# coding conventions at Microsoft and the friendly battles over things like naming, underscores, and formatting styles across internal teams.   Mentioned in this Episode: Clear Measure Way Architect Forum Software Engineer Forum Programming with Palermo — New Video Podcast! Email us at programming@palermo.net. Clear Measure, Inc. (Sponsor) .NET DevOps for Azure: A Developer's Guide to DevOps Architecture the Right Way, by Jeffrey Palermo .Net Aspire and Data API builder with the Community Jerry on LinkedIn Jerry Nixon Github Colorado Christian University Data API builder for Azure Databases samples Common C# code conventions What is Data API Builder? Quickstart: Use Data API builder with SQL   Want to Learn More? Visit AzureDevOps.Show for show notes and additional episodes.

On this episode.... Apocalyptic situations, what's in your emergency kit and carbon cows?Send in your "Clueless questions" to aintgotacluepodcast@gmail.comFor early add free access to all episodes and bonus bits:1 - Apple Podcasts - Click here or Tap Try Free on the Apple Podcasts app for a three day free trial.2 - Via Patreon by clicking herehttps://www.patreon.com/aintgotaclue/Follow AGAC on...Tik Tok- https://www.tiktok.com/@aintgotacluepodYouTube- https://www.youtube.com/channel/UCYz3U9CDm_xhBpmRWN3I9TwInstagram- https://instagram.com/aintgotacluepod

Fredrik talks to Pedro Abreu about the magical world of type theory. What is it, and why is it useful to know about and be inspired by? Pedro gives us some background on type theory, and then we talk about how type theory can provide new ways of reasoning about programs, and tools beyond tests to verify program correctness. This doesn’t mean that all languages should strive for the nirvana of dependent types, but knowing the tools are out there can come in handy even if the code you write is loosely typed. We wrap up with some further podcast tips, of course including Pedro’s own podcast Type theory forall. Thank you Cloudnet for sponsoring our VPS! Comments, questions or tips? We a re @kodsnack, @tobiashieta, @oferlund and @bjoreman on Twitter, have a page on Facebook and can be emailed at info@kodsnack.se if you want to write longer. We read everything we receive. If you enjoy Kodsnack we would love a review in iTunes! You can also support the podcast by buying us a coffee (or two!) through Ko-fi. Links Pedro Type theory Type theory forall - Pedro’s podcast Chalmers The meetup group through which Pedro and Fredrik met Purdue university Bertrand Russell The problem of self reference Types Set theory Kurt Gödel Halting problem Alan Turing Turing machine Alonzo Church Lambda calculus Rust Dependent types Formal methods Liquid types - Haskell extension SAT solver Property-based testing Quickcheck Curry-Howard isomorphism Support Kodsnack on Ko-fi! Functional programming Imperative programming Object-oriented programming Monads Monad transformers Lenses Interactive theorem provers Isabelle HOL Dafny Saul Crucible Symbolic execution CVC3, CVC5 solvers Pure functions C# Algebraic data types Pattern matching Scala Recursion Type theory forall episode 17: the first fantastic one with Conal Elliot. The discussion continues in episode 21 Denotational types Coq IRC Software foundations - about Coq and a lot more The church of logic podcast The Iowa type theory commute podcast Titles Type theory podcasts Very odd for some people Brazilian weather Relearning to appreciate The dawn of computer science Layers of sets Where types first come in Bundle values together The research about programming languages If you squint your eyes enough Nirvana of type systems Proofs all the way down Extra guarantees If your domain is infinite Formal guarantees The properties of my system What is the meaning of my program? Building better systems

We all have fond memories of the first Dev Day in 2023:and the blip that followed soon after. As Ben Thompson has noted, this year's DevDay took a quieter, more intimate tone. No Satya, no livestream, (slightly fewer people?). Instead of putting ChatGPT announcements in DevDay as in 2023, o1 was announced 2 weeks prior, and DevDay 2024 was reserved purely for developer-facing API announcements, primarily the Realtime API, Vision Finetuning, Prompt Caching, and Model Distillation.However the larger venue and more spread out schedule did allow a lot more hallway conversations with attendees as well as more community presentations including our recent guest Alistair Pullen of Cosine as well as deeper dives from OpenAI including our recent guest Michelle Pokrass of the API Team. Thanks to OpenAI's warm collaboration (we particularly want to thank Lindsay McCallum Rémy!), we managed to record exclusive interviews with many of the main presenters of both the keynotes and breakout sessions. We present them in full in today's episode, together with a full lightly edited Q&A with Sam Altman.Show notes and related resourcesSome of these used in the final audio episode below* Simon Willison Live Blog* swyx live tweets and videos* Greg Kamradt coverage of Structured Output session, Scaling LLM Apps session* Fireside Chat Q&A with Sam AltmanTimestamps* [00:00:00] Intro by Suno.ai* [00:01:23] NotebookLM Recap of DevDay* [00:09:25] Ilan's Strawberry Demo with Realtime Voice Function Calling* [00:19:16] Olivier Godement, Head of Product, OpenAI* [00:36:57] Romain Huet, Head of DX, OpenAI* [00:47:08] Michelle Pokrass, API Tech Lead at OpenAI ft. Simon Willison* [01:04:45] Alistair Pullen, CEO, Cosine (Genie)* [01:18:31] Sam Altman + Kevin Weill Q&A* [02:03:07] Notebook LM Recap of PodcastTranscript[00:00:00] Suno AI: Under dev daylights, code ignites. Real time voice streams reach new heights. O1 and GPT, 4. 0 in flight. Fine tune the future, data in sight. Schema sync up, outputs precise. Distill the models, efficiency splice.[00:00:33] AI Charlie: Happy October. This is your AI co host, Charlie. One of our longest standing traditions is covering major AI and ML conferences in podcast format. Delving, yes delving, into the vibes of what it is like to be there stitched in with short samples of conversations with key players, just to help you feel like you were there.[00:00:54] AI Charlie: Covering this year's Dev Day was significantly more challenging because we were all requested not to record the opening keynotes. So, in place of the opening keynotes, we had the viral notebook LM Deep Dive crew, my new AI podcast nemesis, Give you a seven minute recap of everything that was announced.[00:01:15] AI Charlie: Of course, you can also check the show notes for details. I'll then come back with an explainer of all the interviews we have for you today. Watch out and take care.[00:01:23] NotebookLM Recap of DevDay[00:01:23] NotebookLM: All right, so we've got a pretty hefty stack of articles and blog posts here all about open ais. Dev day 2024.[00:01:32] NotebookLM 2: Yeah, lots to dig into there.[00:01:34] NotebookLM 2: Seems[00:01:34] NotebookLM: like you're really interested in what's new with AI.[00:01:36] NotebookLM 2: Definitely. And it seems like OpenAI had a lot to announce. New tools, changes to the company. It's a lot.[00:01:43] NotebookLM: It is. And especially since you're interested in how AI can be used in the real world, you know, practical applications, we'll focus on that.[00:01:51] NotebookLM: Perfect. Like, for example, this Real time API, they announced that, right? That seems like a big deal if we want AI to sound, well, less like a robot.[00:01:59] NotebookLM 2: It could be huge. The real time API could completely change how we, like, interact with AI. Like, imagine if your voice assistant could actually handle it if you interrupted it.[00:02:08] NotebookLM: Or, like, have an actual conversation.[00:02:10] NotebookLM 2: Right, not just these clunky back and forth things we're used to.[00:02:14] NotebookLM: And they actually showed it off, didn't they? I read something about a travel app, one for languages. Even one where the AI ordered takeout.[00:02:21] NotebookLM 2: Those demos were really interesting, and I think they show how this real time API can be used in so many ways.[00:02:28] NotebookLM 2: And the tech behind it is fascinating, by the way. It uses persistent WebSocket connections and this thing called function calling, so it can respond in real time.[00:02:38] NotebookLM: So the function calling thing, that sounds kind of complicated. Can you, like, explain how that works?[00:02:42] NotebookLM 2: So imagine giving the AI Access to this whole toolbox, right?[00:02:46] NotebookLM 2: Information, capabilities, all sorts of things. Okay. So take the travel agent demo, for example. With function calling, the AI can pull up details, let's say about Fort Mason, right, from some database. Like nearby restaurants, stuff like that.[00:02:59] NotebookLM: Ah, I get it. So instead of being limited to what it already knows, It can go and find the information it needs, like a human travel agent would.[00:03:07] NotebookLM 2: Precisely. And someone on Hacker News pointed out a cool detail. The API actually gives you a text version of what's being said. So you can store that, analyze it.[00:03:17] NotebookLM: That's smart. It seems like OpenAI put a lot of thought into making this API easy for developers to use. But, while we're on OpenAI, you know, Besides their tech, there's been some news about, like, internal changes, too.[00:03:30] NotebookLM: Didn't they say they're moving away from being a non profit?[00:03:32] NotebookLM 2: They did. And it's got everyone talking. It's a major shift. And it's only natural for people to wonder how that'll change things for OpenAI in the future. I mean, there are definitely some valid questions about this move to for profit. Like, will they have more money for research now?[00:03:46] NotebookLM 2: Probably. But will they, you know, care as much about making sure AI benefits everyone?[00:03:51] NotebookLM: Yeah, that's the big question, especially with all the, like, the leadership changes happening at OpenAI too, right? I read that their Chief Research Officer left, and their VP of Research, and even their CTO.[00:04:03] NotebookLM 2: It's true. A lot of people are connecting those departures with the changes in OpenAI's structure.[00:04:08] NotebookLM: And I guess it makes you wonder what's going on behind the scenes. But they are still putting out new stuff. Like this whole fine tuning thing really caught my eye.[00:04:17] NotebookLM 2: Right, fine tuning. It's essentially taking a pre trained AI model. And, like, customizing it.[00:04:23] NotebookLM: So instead of a general AI, you get one that's tailored for a specific job.[00:04:27] NotebookLM 2: Exactly. And that opens up so many possibilities, especially for businesses. Imagine you could train an AI on your company's data, you know, like how you communicate your brand guidelines.[00:04:37] NotebookLM: So it's like having an AI that's specifically trained for your company?[00:04:41] NotebookLM 2: That's the idea.[00:04:41] NotebookLM: And they're doing it with images now, too, right?[00:04:44] NotebookLM: Fine tuning with vision is what they called it.[00:04:46] NotebookLM 2: It's pretty incredible what they're doing with that, especially in fields like medicine.[00:04:50] NotebookLM: Like using AI to help doctors make diagnoses.[00:04:52] NotebookLM 2: Exactly. And AI could be trained on thousands of medical images, right? And then it could potentially spot things that even a trained doctor might miss.[00:05:03] NotebookLM: That's kind of scary, to be honest. What if it gets it wrong?[00:05:06] NotebookLM 2: Well, the idea isn't to replace doctors, but to give them another tool, you know, help them make better decisions.[00:05:12] NotebookLM: Okay, that makes sense. But training these AI models must be really expensive.[00:05:17] NotebookLM 2: It can be. All those tokens add up. But OpenAI announced something called automatic prompt caching.[00:05:23] Alex Volkov: Automatic what now? I don't think I came across that.[00:05:26] NotebookLM 2: So basically, if your AI sees a prompt that it's already seen before, OpenAI will give you a discount.[00:05:31] NotebookLM: Huh. Like a frequent buyer program for AI.[00:05:35] NotebookLM 2: Kind of, yeah. It's good that they're trying to make it more affordable. And they're also doing something called model distillation.[00:05:41] NotebookLM: Okay, now you're just using big words to sound smart. What's that?[00:05:45] NotebookLM 2: Think of it like like a recipe, right? You can take a really complex recipe and break it down to the essential parts.[00:05:50] NotebookLM: Make it simpler, but it still tastes the same.[00:05:53] NotebookLM 2: Yeah. And that's what model distillation is. You take a big, powerful AI model and create a smaller, more efficient version.[00:06:00] NotebookLM: So it's like lighter weight, but still just as capable.[00:06:03] NotebookLM 2: Exactly. And that means more people can actually use these powerful tools. They don't need, like, a supercomputer to run them.[00:06:10] NotebookLM: So they're making AI more accessible. That's great.[00:06:13] NotebookLM 2: It is. And speaking of powerful tools, they also talked about their new O1 model.[00:06:18] NotebookLM 2: That's the one they've been hyping up. The one that's supposed to be this big leap forward.[00:06:22] NotebookLM: Yeah, O1. It sounds pretty futuristic. Like, from what I read, it's not just a bigger, better language model.[00:06:28] NotebookLM 2: Right. It's a different porch.[00:06:29] NotebookLM: They're saying it can, like, actually reason, right? Think.[00:06:33] NotebookLM 2: It's trained differently.[00:06:34] NotebookLM 2: They used reinforcement learning with O1.[00:06:36] NotebookLM: So it's not just finding patterns in the data it's seen before.[00:06:40] NotebookLM 2: Not just that. It can actually learn from its mistakes. Get better at solving problems.[00:06:46] NotebookLM: So give me an example. What can O1 do that, say, GPT 4 can't?[00:06:51] NotebookLM 2: Well, OpenAI showed it doing some pretty impressive stuff with math, like advanced math.[00:06:56] NotebookLM 2: And coding, too. Complex coding. Things that even GPT 4 struggled with.[00:07:00] NotebookLM: So you're saying if I needed to, like, write a screenplay, I'd stick with GPT 4? But if I wanted to solve some crazy physics problem, O1 is what I'd use.[00:07:08] NotebookLM 2: Something like that, yeah. Although there is a trade off. O1 takes a lot more power to run, and it takes longer to get those impressive results.[00:07:17] NotebookLM: Hmm, makes sense. More power, more time, higher quality.[00:07:21] NotebookLM 2: Exactly.[00:07:22] NotebookLM: It sounds like it's still in development, though, right? Is there anything else they're planning to add to it?[00:07:26] NotebookLM 2: Oh, yeah. They mentioned system prompts, which will let developers, like, set some ground rules for how it behaves. And they're working on adding structured outputs and function calling.[00:07:38] Alex Volkov: Wait, structured outputs? Didn't we just talk about that? We[00:07:41] NotebookLM 2: did. That's the thing where the AI's output is formatted in a way that's easy to use.[00:07:47] NotebookLM: Right, right. So you don't have to spend all day trying to make sense of what it gives you. It's good that they're thinking about that stuff.[00:07:53] NotebookLM 2: It's about making these tools usable.[00:07:56] NotebookLM 2: And speaking of that, Dev Day finished up with this really interesting talk. Sam Altman, the CEO of OpenAI, And Kevin Weil, their new chief product officer. They talked about, like, the big picture for AI.[00:08:09] NotebookLM: Yeah, they did, didn't they? Anything interesting come up?[00:08:12] NotebookLM 2: Well, Altman talked about moving past this whole AGI term, Artificial General Intelligence.[00:08:18] NotebookLM: I can see why. It's kind of a loaded term, isn't it?[00:08:20] NotebookLM 2: He thinks it's become a bit of a buzzword, and people don't really understand what it means.[00:08:24] NotebookLM: So are they saying they're not trying to build AGI anymore?[00:08:28] NotebookLM 2: It's more like they're saying they're focused on just Making AI better, constantly improving it, not worrying about putting it in a box.[00:08:36] NotebookLM: That makes sense. Keep pushing the limits.[00:08:38] NotebookLM 2: Exactly. But they were also very clear about doing it responsibly. They talked a lot about safety and ethics.[00:08:43] NotebookLM: Yeah, that's important.[00:08:44] NotebookLM 2: They said they were going to be very careful. About how they release new features.[00:08:48] NotebookLM: Good! Because this stuff is powerful.[00:08:51] NotebookLM 2: It is. It was a lot to take in, this whole Dev Day event.[00:08:54] NotebookLM 2: New tools, big changes at OpenAI, and these big questions about the future of AI.[00:08:59] NotebookLM: It was. But hopefully this deep dive helped make sense of some of it. At least, that's what we try to do here.[00:09:05] AI Charlie: Absolutely.[00:09:06] NotebookLM: Thanks for taking the deep dive with us.[00:09:08] AI Charlie: The biggest demo of the new Realtime API involved function calling with voice mode and buying chocolate covered strawberries from our friendly local OpenAI developer experience engineer and strawberry shop owner, Ilan Biggio.[00:09:21] AI Charlie: We'll first play you the audio of his demo and then go into a little interview with him.[00:09:25] Ilan's Strawberry Demo with Realtime Voice Function Calling[00:09:25] Romain Huet: Could you place a call and see if you could get us 400 strawberries delivered to the venue? But please keep that under 1500. I'm on it. We'll get those strawberries delivered for you.[00:09:47] Ilan: Hello? Hi there. Is this Ilan? I'm Romain's AI assistant. How is it going? Fantastic. Can you tell me what flavors of strawberry dips you have for me? Yeah, we have chocolate, vanilla, and we have peanut butter. Wait, how much would 400 chocolate covered strawberries cost? 400? Are you sure you want 400? Yes, 400 chocolate covered[00:10:14] swyx: strawberries.[00:10:15] Ilan: Wait,[00:10:16] swyx: how much[00:10:16] Ilan: would that be? I think that'll be around, like, 1, 415. 92.[00:10:25] Alex Volkov: Awesome. Let's go ahead and place the order for four chocolate covered strawberries.[00:10:31] Ilan: Great, where would you like that delivered? Please deliver them to the Gateway Pavilion at Fort Mason. And I'll be paying in cash.[00:10:42] Alex Volkov: Okay,[00:10:43] Ilan: sweet. So just to confirm, you want four strawberries?[00:10:45] Ilan: 400 chocolate covered strawberries to the Gateway Pavilion. Yes, that's perfect. And when can we expect delivery? Well, you guys are right nearby, so it'll be like, I don't know, 37 seconds? That's incredibly fast. Cool, you too.[00:11:09] swyx: Hi, Ilan, welcome to Lanespace. Oh, thank you. I just saw your amazing demos, had your amazing strawberries. You are dressed up, like, exactly like a strawberry salesman. Gotta have it all. What was the building on demo like? What was the story behind the demo?[00:11:22] swyx: It was really interesting. This is actually something I had been thinking about for months before the launch.[00:11:27] swyx: Like, having a, like, AI that can make phone calls is something like I've personally wanted for a long time. And so as soon as we launched internally, like, I started hacking on it. And then that sort of just started. We made it into like an internal demo, and then people found it really interesting, and then we thought how cool would it be to have this like on stage as, as one of the demos.[00:11:47] swyx: Yeah, would would you call out any technical issues building, like you were basically one of the first people ever to build with a voice mode API. Would you call out any issues like integrating it with Twilio like that, like you did with function calling, with like a form filling elements. I noticed that you had like intents of things to fulfill, and then.[00:12:07] swyx: When there's still missing info, the voice would prompt you, roleplaying the store guy.[00:12:13] swyx: Yeah, yeah, so, I think technically, there's like the whole, just working with audio and streams is a whole different beast. Like, even separate from like AI and this, this like, new capabilities, it's just, it's just tough.[00:12:26] swyx: Yeah, when you have a prompt, conversationally it'll just follow, like the, it was, Instead of like, kind of step by step to like ask the right questions based on like the like what the request was, right? The function calling itself is sort of tangential to that. Like, you have to prompt it to call the functions, but then handling it isn't too much different from, like, what you would do with assistant streaming or, like, chat completion streaming.[00:12:47] swyx: I think, like, the API feels very similar just to, like, if everything in the API was streaming, it actually feels quite familiar to that.[00:12:53] swyx: And then, function calling wise, I mean, does it work the same? I don't know. Like, I saw a lot of logs. You guys showed, like, in the playground, a lot of logs. What is in there?[00:13:03] swyx: What should people know?[00:13:04] swyx: Yeah, I mean, it is, like, the events may have different names than the streaming events that we have in chat completions, but they represent very similar things. It's things like, you know, function call started, argument started, it's like, here's like argument deltas, and then like function call done.[00:13:20] swyx: Conveniently we send one that has the full function, and then I just use that. Nice.[00:13:25] swyx: Yeah and then, like, what restrictions do, should people be aware of? Like, you know, I think, I think, before we recorded, we discussed a little bit about the sensitivities around basically calling random store owners and putting, putting like an AI on them.[00:13:40] swyx: Yeah, so there's, I think there's recent regulation on that, which is why we want to be like very, I guess, aware of, of You know, you can't just call anybody with AI, right? That's like just robocalling. You wouldn't want someone just calling you with AI.[00:13:54] swyx: I'm a developer, I'm about to do this on random people.[00:13:57] swyx: What laws am I about to break?[00:14:00] swyx: I forget what the governing body is, but you should, I think, Having consent of the person you're about to call, it always works. I, as the strawberry owner, have consented to like getting called with AI. I think past that you, you want to be careful. Definitely individuals are more sensitive than businesses.[00:14:19] swyx: I think businesses you have a little bit more leeway. Also, they're like, businesses I think have an incentive to want to receive AI phone calls. Especially if like, they're dealing with it. It's doing business. Right, like, it's more business. It's kind of like getting on a booking platform, right, you're exposed to more.[00:14:33] swyx: But, I think it's still very much like a gray area. Again, so. I think everybody should, you know, tread carefully, like, figure out what it is. I, I, I, the law is so recent, I didn't have enough time to, like, I'm also not a lawyer. Yeah, yeah, yeah, of course. Yeah.[00:14:49] swyx: Okay, cool fair enough. One other thing, this is kind of agentic.[00:14:52] swyx: Did you use a state machine at all? Did you use any framework? No. You just stick it in context and then just run it in a loop until it ends call?[00:15:01] swyx: Yeah, there isn't even a loop, like Okay. Because the API is just based on sessions. It's always just going to keep going. Every time you speak, it'll trigger a call.[00:15:11] swyx: And then after every function call was also invoked invoking like a generation. And so that is another difference here. It's like it's inherently almost like in a loop, be just by being in a session, right? No state machines needed. I'd say this is very similar to like, the notion of routines, where it's just like a list of steps.[00:15:29] swyx: And it, like, sticks to them softly, but usually pretty well. And the steps is the prompts? The steps, it's like the prompt, like the steps are in the prompt. Yeah, yeah, yeah. Right, it's like step one, do this, step one, step two, do that. What if I want to change the system prompt halfway through the conversation?[00:15:44] swyx: You can. Okay. You can. To be honest, I have not played without two too much. Yeah,[00:15:47] swyx: yeah.[00:15:48] swyx: But, I know you can.[00:15:49] swyx: Yeah, yeah. Yeah. Awesome. I noticed that you called it real time API, but not voice API. Mm hmm. So I assume that it's like real time API starting with voice. Right, I think that's what he said on the thing.[00:16:00] swyx: I can't imagine, like, what else is real[00:16:02] swyx: time? Well, I guess, to use ChatGPT's voice mode as an example, Like, we've demoed the video, right? Like, real time image, right? So, I'm not actually sure what timelines are, But I would expect, if I had to guess, That, like, that is probably the next thing that we're gonna be making.[00:16:17] swyx: You'd probably have to talk directly with the team building this. Sure. But, You can't promise their timelines. Yeah, yeah, yeah, right, exactly. But, like, given that this is the features that currently, Or that exists that we've demoed on Chachapiti. Yeah. There[00:16:29] swyx: will never be a[00:16:29] swyx: case where there's like a real time text API, right?[00:16:31] swyx: I don't Well, this is a real time text API. You can do text only on this. Oh. Yeah. I don't know why you would. But it's actually So text to text here doesn't quite make a lot of sense. I don't think you'll get a lot of latency gain. But, like, speech to text is really interesting. Because you can prevent You can prevent responses, like audio responses.[00:16:54] swyx: And force function calls. And so you can do stuff like UI control. That is like super super reliable. We had a lot of like, you know, un, like, we weren't sure how well this was gonna work because it's like, you have a voice answering. It's like a whole persona, right? Like, that's a little bit more, you know, risky.[00:17:10] swyx: But if you, like, cut out the audio outputs and make it so it always has to output a function, like you can end up with pretty pretty good, like, Pretty reliable, like, command like a command architecture. Yeah,[00:17:21] swyx: actually, that's the way I want to interact with a lot of these things as well. Like, one sided voice.[00:17:26] swyx: Yeah, you don't necessarily want to hear the[00:17:27] swyx: voice back. And like, sometimes it's like, yeah, I think having an output voice is great. But I feel like I don't always want to hear an output voice. I'd say usually I don't. But yeah, exactly, being able to speak to it is super sweet.[00:17:39] swyx: Cool. Do you want to comment on any of the other stuff that you announced?[00:17:41] swyx: From caching I noticed was like, I like the no code change part. I'm looking forward to the docs because I'm sure there's a lot of details on like, what you cache, how long you cache. Cause like, enthalpy caches were like 5 minutes. I was like, okay, but what if I don't make a call every 5 minutes?[00:17:56] swyx: Yeah,[00:17:56] swyx: to be super honest with you, I've been so caught up with the real time API and making the demo that I haven't read up on the other stuff. Launches too much. I mean, I'm aware of them, but I think I'm excited to see how all distillation works. That's something that we've been doing like, I don't know, I've been like doing it between our models for a while And I've seen really good results like I've done back in a day like from GPT 4 to GPT 3.[00:18:19] swyx: 5 And got like, like pretty much the same level of like function calling with like hundreds of functions So that was super super compelling So, I feel like easier distillation, I'm really excited for. I see. Is it a tool?[00:18:31] swyx: So, I saw evals. Yeah. Like, what is the distillation product? It wasn't super clear, to be honest.[00:18:36] swyx: I, I think I want to, I want to let that team, I want to let that team talk about it. Okay,[00:18:40] swyx: alright. Well, I appreciate you jumping on. Yeah, of course. Amazing demo. It was beautifully designed. I'm sure that was part of you and Roman, and[00:18:47] swyx: Yeah, I guess, shout out to like, the first people to like, creators of Wanderlust, originally, were like, Simon and Carolis, and then like, I took it and built the voice component and the voice calling components.[00:18:59] swyx: Yeah, so it's been a big team effort. And like the entire PI team for like Debugging everything as it's been going on. It's been, it's been so good working with them. Yeah, you're the first consumers on the DX[00:19:07] swyx: team. Yeah. Yeah, I mean, the classic role of what we do there. Yeah. Okay, yeah, anything else? Any other call to action?[00:19:13] swyx: No, enjoy Dev Day. Thank you. Yeah. That's it.[00:19:16] Olivier Godement, Head of Product, OpenAI[00:19:16] AI Charlie: The latent space crew then talked to Olivier Godmont, head of product for the OpenAI platform, who led the entire Dev Day keynote and introduced all the major new features and updates that we talked about today.[00:19:28] swyx: Okay, so we are here with Olivier Godmont. That's right.[00:19:32] swyx: I don't pronounce French. That's fine. It was perfect. And it was amazing to see your keynote today. What was the back story of, of preparing something like this? Preparing, like, Dev Day? It[00:19:43] Olivier Godement: essentially came from a couple of places. Number one, excellent reception from last year's Dev Day.[00:19:48] Olivier Godement: Developers, startup founders, researchers want to spend more time with OpenAI, and we want to spend more time with them as well. And so for us, like, it was a no brainer, frankly, to do it again, like, you know, like a nice conference. The second thing is going global. We've done a few events like in Paris and like a few other like, you know, non European, non American countries.[00:20:05] Olivier Godement: And so this year we're doing SF, Singapore, and London. To frankly just meet more developers.[00:20:10] swyx: Yeah, I'm very excited for the Singapore one.[00:20:12] Olivier Godement: Ah,[00:20:12] swyx: yeah. Will you be[00:20:13] Olivier Godement: there?[00:20:14] swyx: I don't know. I don't know if I got an invite. No. I can't just talk to you. Yeah, like, and then there was some speculation around October 1st.[00:20:22] Olivier Godement: Yeah. Is it because[00:20:23] swyx: 01, October 1st? It[00:20:25] Olivier Godement: has nothing to do. I discovered the tweet yesterday where like, people are so creative. No one, there was no connection to October 1st. But in hindsight, that would have been a pretty good meme by Tiana. Okay.[00:20:37] swyx: Yeah, and you know, I think like, OpenAI's outreach to developers is something that I felt the whole in 2022, when like, you know, like, people were trying to build a chat GPT, and like, there was no function calling, all that stuff that you talked about in the past.[00:20:51] swyx: And that's why I started my own conference as like like, here's our little developer conference thing. And, but to see this OpenAI Dev Day now, and like to see so many developer oriented products coming to OpenAI, I think it's really encouraging.[00:21:02] Olivier Godement: Yeah, totally. It's that's what I said, essentially, like, developers are basically the people who make the best connection between the technology and, you know, the future, essentially.[00:21:14] Olivier Godement: Like, you know, essentially see a capability, see a low level, like, technology, and are like, hey, I see how that application or that use case that can be enabled. And so, in the direction of enabling, like, AGI, like, all of humanity, it's a no brainer for us, like, frankly, to partner with Devs.[00:21:31] Alessio: And most importantly, you almost never had waitlists, which, compared to like other releases, people usually, usually have.[00:21:38] Alessio: What is the, you know, you had from caching, you had real time voice API, we, you know, Shawn did a long Twitter thread, so people know the releases. Yeah. What is the thing that was like sneakily the hardest to actually get ready for, for that day, or like, what was the kind of like, you know, last 24 hours, anything that you didn't know was gonna work?[00:21:56] Olivier Godement: Yeah. The old Fairly, like, I would say, involved, like, features to ship. So the team has been working for a month, all of them. The one which I would say is the newest for OpenAI is the real time API. For a couple of reasons. I mean, one, you know, it's a new modality. Second, like, it's the first time that we have an actual, like, WebSocket based API.[00:22:16] Olivier Godement: And so, I would say that's the one that required, like, the most work over the month. To get right from a developer perspective and to also make sure that our existing safety mitigation that worked well with like real time audio in and audio out.[00:22:30] swyx: Yeah, what design choices or what was like the sort of design choices that you want to highlight?[00:22:35] swyx: Like, you know, like I think for me, like, WebSockets, you just receive a bunch of events. It's two way. I obviously don't have a ton of experience. I think a lot of developers are going to have to embrace this real time programming. Like, what are you designing for, or like, what advice would you have for developers exploring this?[00:22:51] Olivier Godement: The core design hypothesis was essentially, how do we enable, like, human level latency? We did a bunch of tests, like, on average, like, human beings, like, you know, takes, like, something like 300 milliseconds to converse with each other. And so that was the design principle, essentially. Like, working backward from that, and, you know, making the technology work.[00:23:11] Olivier Godement: And so we evaluated a few options, and WebSockets was the one that we landed on. So that was, like, one design choice. A few other, like, big design choices that we had to make prompt caching. Prompt caching, the design, like, target was automated from the get go. Like, zero code change from the developer.[00:23:27] Olivier Godement: That way you don't have to learn, like, what is a prompt prefix, and, you know, how long does a cache work, like, we just do it as much as we can, essentially. So that was a big design choice as well. And then finally, on distillation, like, and evaluation. The big design choice was something I learned at Skype, like in my previous job, like a philosophy around, like, a pit of success.[00:23:47] Olivier Godement: Like, what is essentially the, the, the minimum number of steps for the majority of developers to do the right thing? Because when you do evals on fat tuning, there are many, many ways, like, to mess it up, frankly, like, you know, and have, like, a crappy model, like, evals that tell, like, a wrong story. And so our whole design was, okay, we actually care about, like, helping people who don't have, like, that much experience, like, evaluating a model, like, get, like, in a few minutes, like, to a good spot.[00:24:11] Olivier Godement: And so how do we essentially enable that bit of success, like, in the product flow?[00:24:15] swyx: Yeah, yeah, I'm a little bit scared to fine tune especially for vision, because I don't know what I don't know for stuff like vision, right? Like, for text, I can evaluate pretty easily. For vision let's say I'm like trying to, one of your examples was grab.[00:24:33] swyx: Which, very close to home, I'm from Singapore. I think your example was like, they identified stop signs better. Why is that hard? Why do I have to fine tune that? If I fine tune that, do I lose other things? You know, like, there's a lot of unknowns with Vision that I think developers have to figure out.[00:24:50] swyx: For[00:24:50] Olivier Godement: sure. Vision is going to open up, like, a new, I would say, evaluation space. Because you're right, like, it's harder, like, you know, to tell correct from incorrect, essentially, with images. What I can say is we've been alpha testing, like, the Vision fine tuning, like, for several weeks at that point. We are seeing, like, even higher performance uplift compared to text fine tuning.[00:25:10] Olivier Godement: So that's, there is something here, like, we've been pretty impressed, like, in a good way, frankly. But, you know, how well it works. But for sure, like, you know, I expect the developers who are moving from one modality to, like, text and images will have, like, more, you know Testing, evaluation, like, you know, to set in place, like, to make sure it works well.[00:25:25] Alessio: The model distillation and evals is definitely, like, the most interesting. Moving away from just being a model provider to being a platform provider. How should people think about being the source of truth? Like, do you want OpenAI to be, like, the system of record of all the prompting? Because people sometimes store it in, like, different data sources.[00:25:41] Alessio: And then, is that going to be the same as the models evolve? So you don't have to worry about, you know, refactoring the data, like, things like that, or like future model structures.[00:25:51] Olivier Godement: The vision is if you want to be a source of truth, you have to earn it, right? Like, we're not going to force people, like, to pass us data.[00:25:57] Olivier Godement: There is no value prop, like, you know, for us to store the data. The vision here is at the moment, like, most developers, like, use like a one size fits all model, like be off the shelf, like GP40 essentially. The vision we have is fast forward a couple of years. I think, like, most developers will essentially, like, have a.[00:26:15] Olivier Godement: An automated, continuous, fine tuned model. The more, like, you use the model, the more data you pass to the model provider, like, the model is automatically, like, fine tuned, evaluated against some eval sets, and essentially, like, you don't have to every month, when there is a new snapshot, like, you know, to go online and, you know, try a few new things.[00:26:34] Olivier Godement: That's a direction. We are pretty far away from it. But I think, like, that evaluation and decision product are essentially a first good step in that direction. It's like, hey, it's you. I set it by that direction, and you give us the evaluation data. We can actually log your completion data and start to do some automation on your behalf.[00:26:52] Alessio: And then you can do evals for free if you share data with OpenAI. How should people think about when it's worth it, when it's not? Sometimes people get overly protective of their data when it's actually not that useful. But how should developers think about when it's right to do it, when not, or[00:27:07] Olivier Godement: if you have any thoughts on it?[00:27:08] Olivier Godement: The default policy is still the same, like, you know, we don't train on, like, any API data unless you opt in. What we've seen from feedback is evaluation can be expensive. Like, if you run, like, O1 evals on, like, thousands of samples Like, your build will get increased, like, you know, pretty pretty significantly.[00:27:22] Olivier Godement: That's problem statement number one. Problem statement number two is, essentially, I want to get to a world where whenever OpenAI ships a new model snapshot, we have full confidence that there is no regression for the task that developers care about. And for that to be the case, essentially, we need to get evals.[00:27:39] Olivier Godement: And so that, essentially, is a sort of a two bugs one stone. It's like, we subsidize, basically, the evals. And we also use the evals when we ship new models to make sure that we keep going in the right direction. So, in my sense, it's a win win, but again, completely opt in. I expect that many developers will not want to share their data, and that's perfectly fine to me.[00:27:56] swyx: Yeah, I think free evals though, very, very good incentive. I mean, it's a fair trade. You get data, we get free evals. Exactly,[00:28:04] Olivier Godement: and we sanitize PII, everything. We have no interest in the actual sensitive data. We just want to have good evaluation on the real use cases.[00:28:13] swyx: Like, I always want to eval the eval. I don't know if that ever came up.[00:28:17] swyx: Like, sometimes the evals themselves are wrong, and there's no way for me to tell you.[00:28:22] Olivier Godement: Everyone who is starting with LLM, teaching with LLM, is like, Yeah, evaluation, easy, you know, I've done testing, like, all my life. And then you start to actually be able to eval, understand, like, all the corner cases, And you realize, wow, there's like a whole field in itself.[00:28:35] Olivier Godement: So, yeah, good evaluation is hard and so, yeah. Yeah, yeah.[00:28:38] swyx: But I think there's a, you know, I just talked to Brain Trust which I think is one of your partners. Mm-Hmm. . They also emphasize code based evals versus your sort of low code. What I see is like, I don't know, maybe there's some more that you didn't demo.[00:28:53] swyx: YC is kind of like a low code experience, right, for evals. Would you ever support like a more code based, like, would I run code on OpenAI's eval platform?[00:29:02] Olivier Godement: For sure. I mean, we meet developers where they are, you know. At the moment, the demand was more for like, you know, easy to get started, like eval. But, you know, if we need to expose like an evaluation API, for instance, for people like, you know, to pass, like, you know, their existing test data we'll do it.[00:29:15] Olivier Godement: So yeah, there is no, you know, philosophical, I would say, like, you know, misalignment on that. Yeah,[00:29:19] swyx: yeah, yeah. What I think this is becoming, by the way, and I don't, like it's basically, like, you're becoming AWS. Like, the AI cloud. And I don't know if, like, that's a conscious strategy, or it's, like, It doesn't even have to be a conscious strategy.[00:29:33] swyx: Like, you're going to offer storage. You're going to offer compute. You're going to offer networking. I don't know what networking looks like. Networking is maybe, like, Caching or like it's a CDN. It's a prompt CDN.[00:29:45] Alex Volkov: Yeah,[00:29:45] swyx: but it's the AI versions of everything, right? Do you like do you see the analogies or?[00:29:52] Olivier Godement: Whatever Whatever I took to developers. I feel like Good models are just half of the story to build a good app There's a third model you need to do Evaluation is the perfect example. Like, you know, you can have the best model in the world If you're in the dark, like, you know, it's really hard to gain the confidence and so Our philosophy is[00:30:11] Olivier Godement: The whole like software development stack is being basically reinvented, you know, with LLMs. There is no freaking way that open AI can build everything. Like there is just too much to build, frankly. And so my philosophy is, essentially, we'll focus on like the tools which are like the closest to the model itself.[00:30:28] Olivier Godement: So that's why you see us like, you know, investing quite a bit in like fine tuning, distillation, our evaluation, because we think that it actually makes sense to have like in one spot, Like, you know, all of that. Like, there is some sort of virtual circle, essentially, that you can set in place. But stuff like, you know, LLMOps, like tools which are, like, further away from the model, I don't know if you want to do, like, you know, super elaborate, like, prompt management, or, you know, like, tooling, like, I'm not sure, like, you know, OpenAI has, like, such a big edge, frankly, like, you know, to build this sort of tools.[00:30:56] Olivier Godement: So that's how we view it at the moment. But again, frankly, the philosophy is super simple. The strategy is super simple. It's meeting developers where they want us to be. And so, you know that's frankly, like, you know, day in, day out, like, you know, what I try to do.[00:31:08] Alessio: Cool. Thank you so much for the time.[00:31:10] Alessio: I'm sure you,[00:31:10] swyx: Yeah, I have more questions on, a couple questions on voice, and then also, like, your call to action, like, what you want feedback on, right? So, I think we should spend a bit more time on voice, because I feel like that's, like, the big splash thing. I talked well Well, I mean, I mean, just what is the future of real time for OpenAI?[00:31:28] swyx: Yeah. Because I think obviously video is next. You already have it in the, the ChatGPT desktop app. Do we just have a permanent, like, you know, like, are developers just going to be, like, sending sockets back and forth with OpenAI? Like how do we program for that? Like, what what is the future?[00:31:44] Olivier Godement: Yeah, that makes sense. I think with multimodality, like, real time is quickly becoming, like, you know, essentially the right experience, like, to build an application. Yeah. So my expectation is that we'll see like a non trivial, like a volume of applications like moving to a real time API. Like if you zoom out, like, audio is really simple, like, audio until basically now.[00:32:05] Olivier Godement: Audio on the web, in apps, was basically very much like a second class citizen. Like, you basically did like an audio chatbot for users who did not have a choice. You know, they were like struggling to read, or I don't know, they were like not super educated with technology. And so, frankly, it was like the crappy option, you know, compared to text.[00:32:25] Olivier Godement: But when you talk to people in the real world, the vast majority of people, like, prefer to talk and listen instead of typing and writing.[00:32:34] swyx: We speak before we write.[00:32:35] Olivier Godement: Exactly. I don't know. I mean, I'm sure it's the case for you in Singapore. For me, my friends in Europe, the number of, like, WhatsApp, like, voice notes they receive every day, I mean, just people, it makes sense, frankly, like, you know.[00:32:45] Olivier Godement: Chinese. Chinese, yeah.[00:32:46] swyx: Yeah,[00:32:47] Olivier Godement: all voice. You know, it's easier. There is more emotions. I mean, you know, you get the point across, like, pretty well. And so my personal ambition for, like, the real time API and, like, audio in general is to make, like, audio and, like, multimodality, like, truly a first class experience.[00:33:01] Olivier Godement: Like, you know, if you're, like, you know, the amazing, like, super bold, like, start up out of YC, you want to build, like, the next, like, billion, like, you know, user application to make it, like, truly your first and make it feel, like, you know, an actual good, like, you know, product experience. So that's essentially the ambition, and I think, like, yeah, it could be pretty big.[00:33:17] swyx: Yeah. I think one, one people, one issue that people have with the voice so far as, as released in advanced voice mode is the refusals.[00:33:24] Alex Volkov: Yeah.[00:33:24] swyx: You guys had a very inspiring model spec. I think Joanne worked on that. Where you said, like, yeah, we don't want to overly refuse all the time. In fact, like, even if, like, not safe for work, like, in some occasions, it's okay.[00:33:38] swyx: How, is there an API that we can say, not safe for work, okay?[00:33:41] Olivier Godement: I think we'll get there. I think we'll get there. The mobile spec, like, nailed it, like, you know. It nailed it! It's so good! Yeah, we are not in the business of, like, policing, you know, if you can say, like, vulgar words or whatever. You know, there are some use cases, like, you know, I'm writing, like, a Hollywood, like, script I want to say, like, will go on, and it's perfectly fine, you know?[00:33:59] Olivier Godement: And so I think the direction where we'll go here is that basically There will always be like, you know, a set of behavior that we will, you know, just like forbid, frankly, because they're illegal against our terms of services. But then there will be like, you know, some more like risky, like themes, which are completely legal, like, you know, vulgar words or, you know, not safe for work stuff.[00:34:17] Olivier Godement: Where basically we'll expose like a controllable, like safety, like knobs in the API to basically allow you to say, hey, that theme okay, that theme not okay. How sensitive do you want the threshold to be on safety refusals? I think that's the Dijkstra. So a[00:34:31] swyx: safety API.[00:34:32] Olivier Godement: Yeah, in a way, yeah.[00:34:33] swyx: Yeah, we've never had that.[00:34:34] Olivier Godement: Yeah. '[00:34:35] swyx: cause right now is you, it is whatever you decide. And then it's, that's it. That, that, that would be the main reason I don't use opening a voice is because of[00:34:42] Olivier Godement: it's over police. Over refuse over refusals. Yeah. Yeah, yeah. No, we gotta fix that. Yeah. Like singing,[00:34:47] Alessio: we're trying to do voice. I'm a singer.[00:34:49] swyx: And you, you locked off singing.[00:34:51] swyx: Yeah,[00:34:51] Alessio: yeah, yeah.[00:34:52] swyx: But I, I understand music gets you in trouble. Okay. Yeah. So then, and then just generally, like, what do you want to hear from developers? Right? We have, we have all developers watching you know, what feedback do you want? Any, anything specific as well, like from, especially from today anything that you are unsure about, that you are like, Our feedback could really help you decide.[00:35:09] swyx: For sure.[00:35:10] Olivier Godement: I think, essentially, it's becoming pretty clear after today that, you know, I would say the open end direction has become pretty clear, like, you know, after today. Investment in reasoning, investment in multimodality, Investment as well, like in, I would say, tool use, like function calling. To me, the biggest question I have is, you know, Where should we put the cursor next?[00:35:30] Olivier Godement: I think we need all three of them, frankly, like, you know, so we'll keep pushing.[00:35:33] swyx: Hire 10, 000 people, or actually, no need, build a bunch of bots.[00:35:37] Olivier Godement: Exactly, and so let's take O1 smart enough, like, for your problems? Like, you know, let's set aside for a second the existing models, like, for the apps that you would love to build, is O1 basically it in reasoning, or do we still have, like, you know, a step to do?[00:35:50] Olivier Godement: Preview is not enough, I[00:35:52] swyx: need the full one.[00:35:53] Olivier Godement: Yeah, so that's exactly that sort of feedback. Essentially what they would love to do is for developers I mean, there's a thing that Sam has been saying like over and over again, like, you know, it's easier said than done, but I think it's directionally correct. As a developer, as a founder, you basically want to build an app which is a bit too difficult for the model today, right?[00:36:12] Olivier Godement: Like, what you think is right, it's like, sort of working, sometimes not working. And that way, you know, that basically gives us like a goalpost, and be like, okay, that's what you need to enable with the next model release, like in a few months. And so I would say that Usually, like, that's the sort of feedback which is like the most useful that I can, like, directly, like, you know, incorporate.[00:36:33] swyx: Awesome. I think that's our time. Thank you so much, guys. Yeah, thank you so much.[00:36:38] AI Charlie: Thank you. We were particularly impressed that Olivier addressed the not safe for work moderation policy question head on, as that had only previously been picked up on in Reddit forums. This is an encouraging sign that we will return to in the closing candor with Sam Altman at the end of this episode.[00:36:57] Romain Huet, Head of DX, OpenAI[00:36:57] AI Charlie: Next, a chat with Roman Hewitt, friend of the pod, AI Engineer World's fair closing keynote speaker, and head of developer experience at OpenAI on his incredible live demos And advice to AI engineers on all the new modalities.[00:37:12] Alessio: Alright, we're live from OpenAI Dev Day. We're with Juan, who just did two great demos on, on stage.[00:37:17] Alessio: And he's been a friend of Latentspace, so thanks for taking some of the time.[00:37:20] Romain Huet: Of course, yeah, thank you for being here and spending the time with us today.[00:37:23] swyx: Yeah, I appreciate appreciate you guys putting this on. I, I know it's like extra work, but it really shows the developers that you're, Care and about reaching out.[00:37:31] Romain Huet: Yeah, of course, I think when you go back to the OpenAI mission, I think for us it's super important that we have the developers involved in everything we do. Making sure that you know, they have all of the tools they need to build successful apps. And we really believe that the developers are always going to invent the ideas, the prototypes, the fun factors of AI that we can't build ourselves.[00:37:49] Romain Huet: So it's really cool to have everyone here.[00:37:51] swyx: We had Michelle from you guys on. Yes, great episode. She very seriously said API is the path to AGI. Correct. And people in our YouTube comments were like, API is not AGI. I'm like, no, she's very serious. API is the path to AGI. Like, you're not going to build everything like the developers are, right?[00:38:08] swyx: Of[00:38:08] Romain Huet: course, yeah, that's the whole value of having a platform and an ecosystem of amazing builders who can, like, in turn, create all of these apps. I'm sure we talked about this before, but there's now more than 3 million developers building on OpenAI, so it's pretty exciting to see all of that energy into creating new things.[00:38:26] Alessio: I was going to say, you built two apps on stage today, an international space station tracker and then a drone. The hardest thing must have been opening Xcode and setting that up. Now, like, the models are so good that they can do everything else. Yes. You had two modes of interaction. You had kind of like a GPT app to get the plan with one, and then you had a cursor to do apply some of the changes.[00:38:47] Alessio: Correct. How should people think about the best way to consume the coding models, especially both for You know, brand new projects and then existing projects that you're trying to modify.[00:38:56] Romain Huet: Yeah. I mean, one of the things that's really cool about O1 Preview and O1 Mini being available in the API is that you can use it in your favorite tools like cursor like I did, right?[00:39:06] Romain Huet: And that's also what like Devin from Cognition can use in their own software engineering agents. In the case of Xcode, like, it's not quite deeply integrated in Xcode, so that's why I had like chat GPT side by side. But it's cool, right, because I could instruct O1 Preview to be, like, my coding partner and brainstorming partner for this app, but also consolidate all of the, the files and architect the app the way I wanted.[00:39:28] Romain Huet: So, all I had to do was just, like, port the code over to Xcode and zero shot the app build. I don't think I conveyed, by the way, how big a deal that is, but, like, you can now create an iPhone app from scratch, describing a lot of intricate details that you want, and your vision comes to life in, like, a minute.[00:39:47] Romain Huet: It's pretty outstanding.[00:39:48] swyx: I have to admit, I was a bit skeptical because if I open up SQL, I don't know anything about iOS programming. You know which file to paste it in. You probably set it up a little bit. So I'm like, I have to go home and test it. And I need the ChatGPT desktop app so that it can tell me where to click.[00:40:04] Romain Huet: Yeah, I mean like, Xcode and iOS development has become easier over the years since they introduced Swift and SwiftUI. I think back in the days of Objective C, or like, you know, the storyboard, it was a bit harder to get in for someone new. But now with Swift and SwiftUI, their dev tools are really exceptional.[00:40:23] Romain Huet: But now when you combine that with O1, as your brainstorming and coding partner, it's like your architect, effectively. That's the best way, I think, to describe O1. People ask me, like, can GPT 4 do some of that? And it certainly can. But I think it will just start spitting out code, right? And I think what's great about O1, is that it can, like, make up a plan.[00:40:42] Romain Huet: In this case, for instance, the iOS app had to fetch data from an API, it had to look at the docs, it had to look at, like, how do I parse this JSON, where do I store this thing, and kind of wire things up together. So that's where it really shines. Is mini or preview the better model that people should be using?[00:40:58] Romain Huet: Like, how? I think people should try both. We're obviously very excited about the upcoming O1 that we shared the evals for. But we noticed that O1 Mini is very, very good at everything math, coding, everything STEM. If you need for your kind of brainstorming or your kind of science part, you need some broader knowledge than reaching for O1 previews better.[00:41:20] Romain Huet: But yeah, I used O1 Mini for my second demo. And it worked perfectly. All I needed was very much like something rooted in code, architecting and wiring up like a front end, a backend, some UDP packets, some web sockets, something very specific. And it did that perfectly.[00:41:35] swyx: And then maybe just talking about voice and Wanderlust, the app that keeps on giving, what's the backstory behind like preparing for all of that?[00:41:44] Romain Huet: You know, it's funny because when last year for Dev Day, we were trying to think about what could be a great demo app to show like an assistive experience. I've always thought travel is a kind of a great use case because you have, like, pictures, you have locations, you have the need for translations, potentially.[00:42:01] Romain Huet: There's like so many use cases that are bounded to travel that I thought last year, let's use a travel app. And that's how Wanderlust came to be. But of course, a year ago, all we had was a text based assistant. And now we thought, well, if there's a voice modality, what if we just bring this app back as a wink.[00:42:19] Romain Huet: And what if we were interacting better with voice? And so with this new demo, what I showed was the ability to like, So, we wanted to have a complete conversation in real time with the app, but also the thing we wanted to highlight was the ability to call tools and functions, right? So, like in this case, we placed a phone call using the Twilio API, interfacing with our AI agents, but developers are so smart that they'll come up with so many great ideas that we could not think of ourselves, right?[00:42:48] Romain Huet: But what if you could have like a, you know, a 911 dispatcher? What if you could have like a customer service? Like center, that is much smarter than what we've been used to today. There's gonna be so many use cases for real time, it's awesome.[00:43:00] swyx: Yeah, and sometimes actually you, you, like this should kill phone trees.[00:43:04] swyx: Like there should not be like dial one[00:43:07] Romain Huet: of course para[00:43:08] swyx: espanol, you know? Yeah, exactly. Or whatever. I dunno.[00:43:12] Romain Huet: I mean, even you starting speaking Spanish would just do the thing, you know you don't even have to ask. So yeah, I'm excited for this future where we don't have to interact with those legacy systems.[00:43:22] swyx: Yeah. Yeah. Is there anything, so you are doing function calling in a streaming environment. So basically it's, it's web sockets. It's UDP, I think. It's basically not guaranteed to be exactly once delivery. Like, is there any coding challenges that you encountered when building this?[00:43:39] Romain Huet: Yeah, it's a bit more delicate to get into it.[00:43:41] Romain Huet: We also think that for now, what we, what we shipped is a, is a beta of this API. I think there's much more to build onto it. It does have the function calling and the tools. But we think that for instance, if you want to have something very robust, On your client side, maybe you want to have web RTC as a client, right?[00:43:58] Romain Huet: And, and as opposed to like directly working with the sockets at scale. So that's why we have partners like Life Kit and Agora if you want to, if you want to use them. And I'm sure we'll have many mores in the, in many more in the future. But yeah, we keep on iterating on that, and I'm sure the feedback of developers in the weeks to come is going to be super critical for us to get it right.[00:44:16] swyx: Yeah, I think LiveKit has been fairly public that they are used in, in the Chachapiti app. Like, is it, it's just all open source, and we just use it directly with OpenAI, or do we use LiveKit Cloud or something?[00:44:28] Romain Huet: So right now we, we released the API, we released some sample code also, and referenced clients for people to get started with our API.[00:44:35] Romain Huet: And we also partnered with LifeKit and Agora, so they also have their own, like ways to help you get started that plugs natively with the real time API. So depending on the use case, people can, can can decide what to use. If you're working on something that's completely client or if you're working on something on the server side, for the voice interaction, you may have different needs, so we want to support all of those.[00:44:55] Alessio: I know you gotta run. Is there anything that you want the AI engineering community to give feedback on specifically, like even down to like, you know, a specific API end point or like, what, what's like the thing that you want? Yeah. I[00:45:08] Romain Huet: mean, you know, if we take a step back, I think dev Day this year is all different from last year and, and in, in a few different ways.[00:45:15] Romain Huet: But one way is that we wanted to keep it intimate, even more intimate than last year. We wanted to make sure that the community is. Thank you very much for joining us on the Spotlight. That's why we have community talks and everything. And the takeaway here is like learning from the very best developers and AI engineers.[00:45:31] Romain Huet: And so, you know we want to learn from them. Most of what we shipped this morning, including things like prompt caching the ability to generate prompts quickly in the playground, or even things like vision fine tuning. These are all things that developers have been asking of us. And so, the takeaway I would, I would leave them with is to say like, Hey, the roadmap that we're working on is heavily influenced by them and their work.[00:45:53] Romain Huet: And so we love feedback From high feature requests, as you say, down to, like, very intricate details of an API endpoint, we love feedback, so yes that's, that's how we, that's how we build this API.[00:46:05] swyx: Yeah, I think the, the model distillation thing as well, it might be, like, the, the most boring, but, like, actually used a lot.[00:46:12] Romain Huet: True, yeah. And I think maybe the most unexpected, right, because I think if I, if I read Twitter correctly the past few days, a lot of people were expecting us. To shape the real time API for speech to speech. I don't think developers were expecting us to have more tools for distillation, and we really think that's gonna be a big deal, right?[00:46:30] Romain Huet: If you're building apps that have you know, you, you want high, like like low latency, low cost, but high performance, high quality on the use case distillation is gonna be amazing.[00:46:40] swyx: Yeah. I sat in the distillation session just now and they showed how they distilled from four oh to four mini and it was like only like a 2% hit in the performance and 50 next.[00:46:49] swyx: Yeah,[00:46:50] Romain Huet: I was there as well for the superhuman kind of use case inspired for an Ebola client. Yeah, this was really good. Cool man! so much for having me. Thanks again for being here today. It's always[00:47:00] AI Charlie: great to have you. As you might have picked up at the end of that chat, there were many sessions throughout the day focused on specific new capabilities.[00:47:08] Michelle Pokrass, Head of API at OpenAI ft. Simon Willison[00:47:08] AI Charlie: Like the new model distillation features combining EVOLs and fine tuning. For our next session, we are delighted to bring back two former guests of the pod, which is something listeners have been greatly enjoying in our second year of doing the Latent Space podcast. Michelle Pokras of the API team joined us recently to talk about structured outputs, and today gave an updated long form session at Dev Day, describing the implementation details of the new structured output mode.[00:47:39] AI Charlie: We also got her updated thoughts on the VoiceMode API we discussed in her episode, now that it is finally announced. She is joined by friend of the pod and super blogger, Simon Willison, who also came back as guest co host in our Dev Day. 2023 episode.[00:47:56] Alessio: Great, we're back live at Dev Day returning guest Michelle and then returning guest co host Fork.[00:48:03] Alessio: Fork, yeah, I don't know. I've lost count. I think it's been a few. Simon Willison is back. Yeah, we just wrapped, we just wrapped everything up. Congrats on, on getting everything everything live. Simon did a great, like, blog, so if you haven't caught up, I[00:48:17] Simon Willison: wrote my, I implemented it. Now, I'm starting my live blog while waiting for the first talk to start, using like GPT 4, I wrote me the Javascript, and I got that live just in time and then, yeah, I was live blogging the whole day.[00:48:28] swyx: Are you a cursor enjoyer?[00:48:29] Simon Willison: I haven't really gotten into cursor yet to be honest. I just haven't spent enough time for it to click, I think. I'm more a copy and paste things out of Cloud and chat GPT. Yeah. It's interesting.[00:48:39] swyx: Yeah. I've converted to cursor and 01 is so easy to just toggle on and off.[00:48:45] Alessio: What's your workflow?[00:48:46] Alessio: VS[00:48:48] Michelle Pokrass: Code co pilot, so Yep, same here. Team co pilot. Co pilot is actually the reason I joined OpenAI. It was, you know, before ChatGPT, this is the thing that really got me. So I'm still into it, but I keep meaning to try out Cursor, and I think now that things have calmed down, I'm gonna give it a real go.[00:49:03] swyx: Yeah, it's a big thing to change your tool of choice.[00:49:06] swyx: Yes,[00:49:06] Michelle Pokrass: yeah, I'm pretty dialed, so.[00:49:09] swyx: I mean, you know, if you want, you can just fork VS Code and make your own. That's the thing to dumb thing, right? We joked about doing a hackathon where the only thing you do is fork VS Code and bet me the best fork win.[00:49:20] Michelle Pokrass: Nice.[00:49:22] swyx: That's actually a really good idea. Yeah, what's up?[00:49:26] swyx: I mean, congrats on launching everything today. I know, like, we touched on it a little bit, but, like, everyone was kind of guessing that Voice API was coming, and, like, we talked about it in our episode. How do you feel going into the launch? Like, any design decisions that you want to highlight?[00:49:41] Michelle Pokrass: Yeah, super jazzed about it. The team has been working on it for a while. It's, like, a very different API for us. It's the first WebSocket API, so a lot of different design decisions to be made. It's, like, what kind of events do you send? When do you send an event? What are the event names? What do you send, like, on connection versus on future messages?[00:49:57] Michelle Pokrass: So there have been a lot of interesting decisions there. The team has also hacked together really cool projects as we've been testing it. One that I really liked is we had an internal hack a thon for the API team. And some folks built like a little hack that you could use to, like VIM with voice mode, so like, control vim, and you would tell them on like, nice, write a file and it would, you know, know all the vim commands and, and pipe those in.[00:50:18] Michelle Pokrass: So yeah, a lot of cool stuff we've been hacking on and really excited to see what people build with it.[00:50:23] Simon Willison: I've gotta call out a demo from today. I think it was Katja had a 3D visualization of the solar system, like WebGL solar system, you could talk to. That is one of the coolest conference demos I've ever seen.[00:50:33] Simon Willison: That was so convincing. I really want the code. I really want the code for that to get put out there. I'll talk[00:50:39] Michelle Pokrass: to the team. I think we can[00:50:40] Simon Willison: probably

Po prawie 5 latach, ponownie zagościła u nas Agata Rygielska. Tym razem rozmawialiśmy o jej drodze od tłumaczki do kodującej Tech Writerki. Agata opowiedziała nam dlaczego postanowiła rozwijać swoje umiejętności techniczne, jakich języków i technologii się uczyła, w jaki sposób nabywała wiedzę, jakie były dla niej największe wyzwania oraz jakie ma plany na przyszłość. Na koniec dzielimy się wynikami krótkiej ankiety na temat kodowania, którą przeprowadziliśmy wśród Tech Writerów. Dowiecie się z niej m.in. jaki procent ankietowanych koduje a jaki zna rożnicę między Javą i JavaScriptem. Informacje dodatkowe: "#11 Robot dokumentuje część 2 - automatyzacja kontra ludzie", Tech Writer koduje: https://techwriterkoduje.pl/blog/2019/12/12/11 "Optimus - ofiara chorego systemu, który od lat niszczy polską przedsiębiorczość": https://forsal.pl/artykuly/780660,optimus-ofiara-chorego-systemu-ktory-od-lat-niszczy-polska-przedsiebiorczosc.html MadCap Flare: https://www.madcapsoftware.com/products/flare/ React: https://react.dev/ Docker: https://www.docker.com/ "#27 Tech Writer szkoli się z Pythona", Tech Writer koduje: https://techwriterkoduje.pl/blog/2021/2/17/27 lxml: https://lxml.de/ Jenkins: https://www.jenkins.io/ Babel: https://babeljs.io/ Rollup: https://rollupjs.org/ Git: https://git-scm.com/ Cursor AI: https://www.cursor.com/ Notepad++: https://notepad-plus-plus.org/ Visual Studio Code: https://code.visualstudio.com/ Strona Sebastiana Witowskiego: https://switowski.com/ "Modern Python Projects Course", Talk Python to Me: https://training.talkpython.fm/courses/modern-python-projects PyCharm: https://www.jetbrains.com/pycharm/ Vale: https://github.com/errata-ai/vale Static site generator: https://www.gatsbyjs.com/docs/glossary/static-site-generator/ "What is CodeWhisperer?", Amazon AWS Documentation: https://docs.aws.amazon.com/codewhisperer/latest/userguide/what-is-cwspr.html "Cascading Style Sheets", Wikipedia: https://simple.wikipedia.org/wiki/Cascading_Style_Sheets Sourcery: https://sourcery.ai/ Kotlin: https://kotlinlang.org/ Vasont CMS: https://www.globallinkccms.com/products/vasont "C Sharp (programming language)", Wikipedia: https://en.wikipedia.org/wiki/C_Sharp_(programming_language) "XSL Formatting Objects", Wikipedia: https://pl.wikipedia.org/wiki/XSL_Formatting_Objects Pykonik, Kraków Python User Group: https://www.meetup.com/pl-PL/pykonik/

David Neal, developer advocate and Asana content creator, discusses his talk, The Illustrated Guide to Node.js. David shares insights from his 10-year journey with Node.js, discussing its origins, use cases, and why it remains a vital tool for developers, giving insights into JavaScript's evolution and practical tips for navigating the Node.js ecosystem. Links https://reverentgeek.com https://twitter.com/reverentgeek https://techhub.social/@reverentgeek https://staging.bsky.app/profile/reverentgeek.com https://www.threads.net/@reverentgeek https://github.com/reverentgeek https://www.youtube.com/ReverentGeek https://www.linkedin.com/in/davidneal We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Let us know by sending an email to our producer, Emily, at emily.kochanekketner@logrocket.com (mailto:emily.kochanekketner@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form (https://podrocket.logrocket.com/get-podrocket-stickers), and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understand where your users are struggling by trying it for free at [LogRocket.com]. Try LogRocket for free today.(https://logrocket.com/signup/?pdr) Special Guest: David Neal.

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Da un commento arrivato ad un mio video, prendo la palla al balzo per parlare di come poter organizzare il codice delle nostre Classi/Struct/Interface.https://youtu.be/LltUUCX1rbk?si=0hmpD_1aw-n5pqsj#visualstudio #csharp #partialclasses #region #codestyles

Summary Databases come in a variety of formats for different use cases. The default association with the term "database" is relational engines, but non-relational engines are also used quite widely. In this episode Oren Eini, CEO and creator of RavenDB, explores the nuances of relational vs. non-relational engines, and the strategies for designing a non-relational database. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management This episode is brought to you by Datafold – a testing automation platform for data engineers that prevents data quality issues from entering every part of your data workflow, from migration to dbt deployment. Datafold has recently launched data replication testing, providing ongoing validation for source-to-target replication. Leverage Datafold's fast cross-database data diffing and Monitoring to test your replication pipelines automatically and continuously. Validate consistency between source and target at any scale, and receive alerts about any discrepancies. Learn more about Datafold by visiting dataengineeringpodcast.com/datafold (https://www.dataengineeringpodcast.com/datafold). Dagster offers a new approach to building and running data platforms and data pipelines. It is an open-source, cloud-native orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. Your team can get up and running in minutes thanks to Dagster Cloud, an enterprise-class hosted solution that offers serverless and hybrid deployments, enhanced security, and on-demand ephemeral test deployments. Go to dataengineeringpodcast.com/dagster (https://www.dataengineeringpodcast.com/dagster) today to get started. Your first 30 days are free! Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics. Trusted by teams of all sizes, including Comcast and Doordash, Starburst is a data lake analytics platform that delivers the adaptability and flexibility a lakehouse ecosystem promises. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data. Want to see Starburst in action? Go to dataengineeringpodcast.com/starburst (https://www.dataengineeringpodcast.com/starburst) and get $500 in credits to try Starburst Galaxy today, the easiest and fastest way to get started using Trino. Your host is Tobias Macey and today I'm interviewing Oren Eini about the work of designing and building a NoSQL database engine Interview Introduction How did you get involved in the area of data management? Can you describe what constitutes a NoSQL database? How have the requirements and applications of NoSQL engines changed since they first became popular ~15 years ago? What are the factors that convince teams to use a NoSQL vs. SQL database? NoSQL is a generalized term that encompasses a number of different data models. How does the underlying representation (e.g. document, K/V, graph) change that calculus? How have the evolution in data formats (e.g. N-dimensional vectors, point clouds, etc.) changed the landscape for NoSQL engines? When designing and building a database, what are the initial set of questions that need to be answered? How many "core capabilities" can you reasonably design around before they conflict with each other? How have you approached the evolution of RavenDB as you add new capabilities and mature the project? What are some of the early decisions that had to be unwound to enable new capabilities? If you were to start from scratch today, what database would you build? What are the most interesting, innovative, or unexpected ways that you have seen RavenDB/NoSQL databases used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on RavenDB? When is a NoSQL database/RavenDB the wrong choice? What do you have planned for the future of RavenDB? Contact Info Blog (https://ayende.com/blog/) LinkedIn (https://www.linkedin.com/in/ravendb/?originalSubdomain=il) Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ (https://www.pythonpodcast.com) covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast (https://www.themachinelearningpodcast.com) helps you go from idea to production with machine learning. Visit the site (https://www.dataengineeringpodcast.com) to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com (mailto:hosts@dataengineeringpodcast.com)) with your story. Links RavenDB (https://ravendb.net/) RSS (https://en.wikipedia.org/wiki/RSS) Object Relational Mapper (ORM) (https://en.wikipedia.org/wiki/Object%E2%80%93relational_mapping) Relational Database (https://en.wikipedia.org/wiki/Relational_database) NoSQL (https://en.wikipedia.org/wiki/NoSQL) CouchDB (https://couchdb.apache.org/) Navigational Database (https://en.wikipedia.org/wiki/Navigational_database) MongoDB (https://www.mongodb.com/) Redis (https://redis.io/) Neo4J (https://neo4j.com/) Cassandra (https://cassandra.apache.org/_/index.html) Column-Family (https://en.wikipedia.org/wiki/Column_family) SQLite (https://www.sqlite.org/) LevelDB (https://github.com/google/leveldb) Firebird DB (https://firebirdsql.org/) fsync (https://man7.org/linux/man-pages/man2/fsync.2.html) Esent DB? (https://learn.microsoft.com/en-us/windows/win32/extensible-storage-engine/extensible-storage-engine-managed-reference) KNN == K-Nearest Neighbors (https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm) RocksDB (https://rocksdb.org/) C# Language (https://en.wikipedia.org/wiki/C_Sharp_(programming_language)) ASP.NET (https://en.wikipedia.org/wiki/ASP.NET) QUIC (https://en.wikipedia.org/wiki/QUIC) Dynamo Paper (https://www.allthingsdistributed.com/files/amazon-dynamo-sosp2007.pdf) Database Internals (https://amzn.to/49A5wjF) book (affiliate link) Designing Data Intensive Applications (https://amzn.to/3JgCZFh) book (affiliate link) The intro and outro music is from The Hug (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Love_death_and_a_drunken_monkey/04_-_The_Hug) by The Freak Fandango Orchestra (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/) / CC BY-SA (http://creativecommons.org/licenses/by-sa/3.0/)

Peter van Hardenberg talks about Industrialists vs. Academics, Ink&Switch's evolution over time, the Hollywood Model, internal lab infrastructure, and more! Peter is the lab director and CEO of Ink&Switch, a private, creator oriented, computing research lab.  References Ink&Switch (and their many publications) The Hollywood Model in R&D Idea Machines Episode with Adam Wiggins Paul Erdós Transcript Peter Van Hardenberg [00:01:21] Ben: Today I have the pleasure of speaking with Peter van Hardenbergh. Peter is the lab director and CEO of Inkin switch. Private creator oriented, competing research lab. I talked to Adam Wiggins, one of inkind switches founders, [00:01:35] way back in episode number four. It's amazing to see the progress they've made as an organization. They've built up an incredible community of fellow travelers and consistently released research reports that gesture at possibilities for competing that are orthogonal to the current hype cycles. Peter frequently destroys my complacency with his ability to step outside the way that research has normally done and ask, how should we be operating, given our constraints and goals. I hope you enjoy my conversation with Peter. Would you break down your distinction between academics and industrialists [00:02:08] Peter: Okay. Academics are people whose incentive structure is connected to the institutional rewards of the publishing industry, right? You, you publish papers. And you get tenure and like, it's a, it's, it's not so cynical or reductive, but like fundamentally the time cycles are long, right? Like you have to finish work according to when, you know, submission deadlines for a conference are, you know, you're [00:02:35] working on something now. You might come back to it next quarter or next year or in five years, right? Whereas when you're in industry, you're connected to users, you're connected to people at the end of the day who need to touch and hold and use the thing. And you know, you have to get money from them to keep going. And so you have a very different perspective on like time and money and space and what's possible. And the real challenge in terms of connecting these two, you know, I didn't invent the idea of pace layers, right? They, they operate at different pace layers. Academia is often intergenerational, right? Whereas industry is like, you have to make enough money every quarter. To keep the bank account from going below zero or everybody goes home, [00:03:17] Ben: Right. Did. Was it Stuart Brand who invented pace [00:03:22] Peter: believe it was Stewart Brand. Pace layers. Yeah. [00:03:25] Ben: That actually I, I'd never put these two them together, but the, the idea I, I, I think about impedance mismatches between [00:03:35] organizations a lot. And that really sort of like clicks with pace layers Exactly. Right. Where it's like [00:03:39] Peter: Yeah, absolutely. And, and I think in a big way what we're doing at, Ink& Switch on some level is trying to provide like synchro mesh between academia and industry, right? Because they, the academics are moving on a time scale and with an ambition that's hard for industry to match, right? But also, Academics. Often I think in computer science are like, have a shortage of good understanding about what the real problems people are facing in the world today are. They're not disinterested. [00:04:07] Ben: just computer [00:04:08] Peter: Those communication channels don't exist cuz they don't speak the same language, they don't use the same terminology, they don't go to the same conferences, they don't read the same publications. Right. [00:04:18] Ben: Yeah. [00:04:18] Peter: so vice versa, you know, we find things in industry that are problems and then it's like you go read the papers and talk to some scientists. I was like, oh dang. Like. We know how to solve this. It's just nobody's built it. [00:04:31] Ben: Yeah. [00:04:32] Peter: Or more accurately it would be to say [00:04:35] there's a pretty good hunch here about something that might work, and maybe we can connect the two ends of this together. [00:04:42] Ben: Yeah. Often, I, I think of it as someone, someone has, it is a quote unquote solved problem, but there are a lot of quote unquote, implementation details and those implementation details require a year of work. [00:04:56] Peter: yeah, a year or many years? Or an entire startup, or a whole career or two? Yeah. And, and speaking of, Ink&Switch, I don't know if we've ever talked about, so a switch has been around for more than half a decade, right? [00:05:14] Peter: Yeah, seven or eight years now, I think I could probably get the exact number, but yeah, about that. [00:05:19] Ben: And. I think I don't have a good idea in my head over that time. What, what has changed about in, can switches, conception of itself and like how you do things. Like what is, what are some of the biggest things that have have changed over that time?[00:05:35] [00:05:35] Peter: So I think a lot of it could be summarized as professionalization. But I, I'll give a little brief history and can switch began because the. You know, original members of the lab wanted to do a startup that was Adam James and Orion, but they recognized that they didn't, they weren't happy with computing and where computers were, and they knew that they wanted to make something that would be a tool that would help people who were solving the world's problems work better. That's kinda a vague one, but You know, they were like, well, we're not physicists, we're not social scientists. You know, we can't solve climate change or radicalization directly, or you know, the journalism crisis or whatever, but maybe we can build tools, right? We know how to make software tools. Let's build tools for the people who are solving the problems. Because right now a lot of those systems they rely on are getting like steadily worse every day. And I think they still are like the move to the cloud disempowerment of the individual, like, you [00:06:35] know, surveillance technology, distraction technology. And Tristan Harris is out there now. Like hammering on some of these points. But there's just a lot of things that are like slow and fragile and bad and not fun to work with and lose your, you know, lose your work product. You know, [00:06:51] Ben: Yeah, software as a service more generally. [00:06:54] Peter: Yeah. And like, there's definitely advantages. It's not like, you know, people are rational actors, but something was lost. And so the idea was well go do a bit of research, figure out what the shape of the company is, and then just start a company and, you know, get it all solved and move on. And I think the biggest difference, at least, you know, aside from scale and like actual knowledge is just kind of the dawning realization at some point that like there won't really be an end state to this problem. Like this isn't a thing that's transitional where you kind of come in and you do some research for a bit, and then we figure out the answer and like fold up the card table and move on to the next thing. It's like, oh no, this, this thing's gotta stick around because these problems aren't gonna [00:07:35] go away. And when we get through this round of problems, we already see what the next round are. And that's probably gonna go on for longer than any of us will be working. And so the vision now, at least from my perspective as the current lab director, is much more like, how can I get this thing to a place where it can sustain for 10 years, for 50 years, however long it takes, and you know, to become a place that. Has a culture that can sustain, you know, grow and change as new people come in. But that can sustain operations indefinitely. [00:08:07] Ben: Yeah. And, and so to circle back to the. The, the jumping off point for this, which is sort of since, since it began, what have been some of the biggest changes of how you operate? How you, or just like the, the model more generally or, or things that you were [00:08:30] Peter: Yeah, so the beginning was very informal, but, so maybe I'll skip over the first like [00:08:35] little period where it was just sort of like, Finding our footing. But around the time when I joined, we were just four or five people. And we did one project, all of us together at a time, and we just sort of like, someone would write a proposal for what we should do next, and then we would argue about like whether it was the right next thing. And, you know, eventually we would pick a thing and then we would go and do that project and we would bring in some contractors and we called it the Hollywood model. We still call it the Hollywood model. Because it was sort of structured like a movie production. We would bring in, you know, to our little core team, we'd bring in a couple specialists, you know, the equivalent of a director of photography or like a, you know, a casting director or whatever, and you bring in the people that you need to accomplish the task. Oh, we don't know how to do Bluetooth on the web. Okay. Find a Bluetooth person. Oh, there's a bunch of crypto stuff, cryptography stuff. Just be clear on this upcoming project, we better find somebody who knows, you know, the ins and outs of like, which cryptography algorithms to use or [00:09:35] what, how to build stuff in C Sharp for Windows platform or Surface, whatever the, the project was over time. You know, we got pretty good at that and I think one of the biggest changes, sort of after we kind of figured out how to actually do work was the realization that. Writing about the work not only gave us a lot of leverage in terms of our sort of visibility in the community and our ability to attract talent, but also the more we put into the writing, the more we learned about the research and that the process of, you know, we would do something and then write a little internal report and then move on. But the process of taking the work that we do, And making it legible to the outside world and explaining why we did it and what it means and how it fits into the bigger picture. That actually like being very diligent and thorough in documenting all of that greatly increases our own understanding of what we did.[00:10:35] And that was like a really pleasant and interesting surprise. I think one of my sort of concerns as lab director is that we got really good at that and we write all these like, Obscenely long essays that people claim to read. You know, hacker News comments on extensively without reading. But I think a lot about, you know, I always worry about the orthodoxy of doing the same thing too much and whether we're sort of falling into patterns, so we're always tinkering with new kind of project systems or new ways of working or new kinds of collaborations. And so yeah, that's ongoing. But this, this. The key elements of our system are we bring together a team that has both longer term people with domain contexts about the research, any required specialists who understand like interesting or important technical aspects of the work. And then we have a specific set of goals to accomplish [00:11:35] with a very strict time box. And then when it's done, we write and we put it down. And I think this avoids number of the real pitfalls in more open-ended research. It has its own shortcomings, right? But one of the big pitfalls that avoids is the kind of like meandering off and losing sight of what you're doing. And you can get great results from that in kind of a general research context. But we're very much an industrial research context. We're trying to connect real problems to specific directions to solve them. And so the time box kind of creates the fear of death. You're like, well, I don't wanna run outta time and not have anything to show for it. So you really get focused on trying to deliver things. Now sometimes that's at the cost, like the breadth or ambition of a solution to a particular thing, but I think it helps us really keep moving forward. [00:12:21] Ben: Yeah, and, and you no longer have everybody in the lab working on the same projects, right. [00:12:28] Peter: Yeah. So today, at any given time, The sort of population of the lab fluctuates between sort of [00:12:35] like eight and 15 people, depending on, you know, whether we have a bunch of projects in full swing or you know, how you count contractors. But we usually, at the moment we have sort of three tracks of research that we're doing. And those are local first software Programmable Inc. And Malleable software. [00:12:54] Ben: Nice. And so I, I actually have questions both about the, the write-ups that you do and the Hollywood model and so on, on the Hollywood model. Do you think that I, I, and this is like, do you think that the, the Hollywood model working in, in a. Industrial Research lab is particular to software in the sense that I feel like the software industry, people change jobs fairly frequently. Contracting is really common. Contractors are fairly fluid and. [00:13:32] Peter: You mean in terms of being able to staff and source people?[00:13:35] [00:13:35] Ben: Yeah, and people take, like, take these long sabbaticals, right? Where it's like, it's not uncommon in the software industry for someone to, to take six months between jobs. [00:13:45] Peter: I think it's very hard for me to generalize about the properties of other fields, so I want to try and be cautious in my evaluation here. What I would say is that, I think the general principle of having a smaller core of longer term people who think and gain a lot of context about a problem and pairing them up with people who have fresh ideas and relevant expertise, does not require you to have any particular industry structure. Right. There are lots of ways of solving this problem. Go to a research, another research organization and write a paper with someone from [00:14:35] an adjacent field. If you're in academia, right? If you're in a company, you can do a partnership you know, hire, you know, I think a lot of fields of science have much longer cycles, right? If you're doing material science, you know, takes a long time to build test apparatus and to formulate chemistries. Like [00:14:52] Ben: Yeah. [00:14:52] Peter: someone for several years, right? Like, That's fine. Get a detach detachment from another part of the company and bring someone as a secondment. Like I think that the general principle though, of putting together a mixture of longer and shorter term people with the right set of skills, yes, we solve it a particular way in our domain. But I don't think that that's software u unique to software. [00:15:17] Ben: Would, would it be overreaching to map that onto professors and postdocs and grad students where you have the professor who is the, the person who's been working on the, the program for a long time has all the context and then you have postdocs and grad students [00:15:35] coming through the lab. [00:15:38] Peter: Again, I need to be thoughtful about. How I evaluate fields that I'm less experienced with, but both my parents went through grad school and I've certainly gotten to know a number of academics. My sense of the relationship between professors and or sort of PhD, yeah, I guess professors and their PhD students, is that it's much more likely that the PhD students are given sort of a piece of the professor's vision to execute. [00:16:08] Ben: Yeah. [00:16:09] Peter: And that that is more about scaling the research interests of the professor. And I don't mean this in like a negative way but I think it's quite different [00:16:21] Ben: different. [00:16:22] Peter: than like how DARPA works or how I can switch works with our research tracks in that it's, I it's a bit more prescriptive and it's a bit more of like a mentor-mentee kind of relationship as [00:16:33] Ben: Yeah. More training.[00:16:35] [00:16:35] Peter: Yeah. And you know, that's, that's great. I mean, postdocs are a little different again, but I think, I think that's different than say how DARPA works or like other institutional research groups. [00:16:49] Ben: Yeah. Okay. I, I wanted to see how, how far I could stretch the, stretch [00:16:55] Peter: in academia there's famous stories about Adosh who would. Turn up on your doorstep you know, with a suitcase and a bottle of amphetamines and say, my, my brain is open, or something to that effect. And then you'd co-author a paper and pay his room and board until you found someone else to send him to.   I think that's closer in the sense that, right, like, here's this like, great problem solver with a lot of like domain skills and he would parachute into a place where someone was working on something interesting and help them make a breakthrough with it. [00:17:25] Ben: Yeah. I think the, the thing that I want to figure out, just, you know, long, longer term is how to. Make those [00:17:35] short term collaborations happen when with, with like, I, I I think it's like, like there's some, there's some coy intention like in, in the sense of like Robert Kos around like organizational boundaries when you have people coming in and doing things in a temporary sense. [00:17:55] Peter: Yeah, academia is actually pretty good at this, right? With like paper co-authors. I mean, again, this is like the, the pace layers thing. When you have a whole bunch of people organized in an industry and a company around a particular outcome, You tend to have like very specific goals and commitments and you're, you're trying to execute against those and it's much harder to get that kind of like more fluid movement between domains. [00:18:18] Ben: Yeah, and [00:18:21] Peter: That's why I left working in companies, right? Cause like I have run engineering processes and built products and teams and it's like someone comes to me with a really good idea and I'm like, oh, it's potentially very interesting, but like, [00:18:33] Ben: but We [00:18:34] Peter: We got [00:18:35] customers who have outages who are gonna leave if we don't fix the thing, we've got users falling out of our funnel. Cause we don't do basic stuff like you just, you really have a lot of work to do to make the thing go [00:18:49] Ben: Yeah. [00:18:49] Peter: business. And you know, my experience of research labs within businesses is that they're almost universally unsuccessful. There are exceptions, but I think they're more coincidental than, than designed. [00:19:03] Ben: Yeah. And I, I think less and less successful over time is, is my observation that. [00:19:11] Peter: Interesting. [00:19:12] Ben: Yeah, there's a, there's a great paper that I will send you called like, what is the name? Oh, the the Changing Structure of American Innovation by She Aurora. I actually did a podcast with him because I like the paper so much. that that I, I think, yeah, exactly. And so going back to your, your amazing [00:19:35] write-ups, you all have clearly invested quite a chunk of, of time and resources into some amount of like internal infrastructure for making those really good. And I wanted to get a sense of like, how do you decide when it's worth investing in internal infrastructure for a lab? [00:19:58] Peter: Ooh. Ah, that's a fun question. Least at In and Switch. It's always been like sort of demand driven. I wish I could claim to be more strategic about it, but like we had all these essays, they were actually all hand coded HTML at one point. You know, real, real indie cred there. But it was a real pain when you needed to fix something or change something. Cause you had to go and, you know, edit all this H T M L. So at some point we were doing a smaller project and I built like a Hugo Templating thing [00:20:35] just to do some lab notes and I faked it. And I guess this is actually a, maybe a somewhat common thing, which is you do one in a one-off way. And then if it's promising, you invest more in it. [00:20:46] Ben: Yeah. [00:20:46] Peter: And it ended up being a bigger project to build a full-on. I mean, it's not really a cms, it's sort of a cms, it's a, it's a templating system that produces static HT m l. It's what all our essays come out of. But there's also a lot of work in a big investment in just like design and styling. And frankly, I think that one of the things that in can switch apart from other. People who do similar work in the space is that we really put a lot of work into the presentation of our work. You know, going beyond, like we write very carefully, but we also care a lot about like, picking good colors, making sure that text hyphenates well, that it, you know, that the the screencast has the right dimensions and, you know, all that little detail work and. It's expensive [00:21:35] in time and money to do, but I think it's, I think the results speak for themselves. I think it's worth it. [00:21:47] Ben: Yeah. I, and I mean, if, if the ultimate goal is to influence what people do and what they think, which I suspect is, is at least some amount of the goal then communicating it. [00:22:00] Peter: It's much easier to change somebody's mind than to build an entire company. [00:22:05] Ben: Yes. Well, [00:22:06] Peter: you wanna, if you wanna max, it depends. Well, you don't have to change everybody's mind, right? Like changing an individual person's mind might be impossible. But if you can put the right ideas out there in the right way to make them legible, then you'll change the right. Hopefully you'll change somebody's mind and it will be the right somebody. [00:22:23] Ben: yeah. No, that is, that is definitely true. And another thing that I am. Always obscenely obsessed, exceedingly impressed by that. In Switch. [00:22:35] Does is your sort of thoughtfulness around how you structure your community and sort of tap into it. Would you be willing to sort of like, walk me through how you think about that and like how you have sort of the, the different layers of, of kind of involvement? [00:22:53] Peter: Okay. I mean, sort of the, maybe I'll work from, from the inside out cuz that's sort of the history of it. So in the beginning there was just sort of the people who started the lab. And over time they recruited me and, and Mark Mcg again and you know, some of our other folk to come and, and sign on for this crazy thing. And we started working with these wonderful, like contractors off and on and and so the initial sort of group was quite small and quite insular and we didn't publish anything. And what we found was that. Once we started, you know, just that alone, the act of bringing people in and working with them started to create the beginning of a [00:23:35] community because people would come into a project with us, they'd infect us with some of their ideas, we'd infect them with some of ours. And so you started to have this little bit of shared context with your past collaborators. And because we have this mix of like longer term people who stick with the lab and other people who come and go, You start to start to build up this, this pool of people who you share ideas and language with. And over time we started publishing our work and we began having what we call workshops where we just invite people to come and talk about their work at Ink and Switch. And by at, I mean like now it's on a discord. Back in the day it was a Skype or a Zoom call or whatever. And the rule back then in the early days was like, if you want to come to the talk. You have to have given a talk or have worked at the lab. And so it was like very good signal to noise ratio in attendance cuz the only people who would be on the zoom call would be [00:24:35] people who you knew were grappling with those problems. For real, no looky lose, no, no audience, right? And over time it just, there were too many really good, interesting people who are doing the work. To fit in all those workshops and actually scheduling workshops is quite tiring and takes a lot of energy. And so over time we sort of started to expand this community a little further. And sort of now our principle is you know, if you're doing the work, you're welcome to come to the workshops. And we invite some people to do workshops sometimes, but that's now we have this sort of like small private chat group of like really interesting folk. And it's not open to the public generally because again, we, I don't want to have an audience, right? I want it to practitioner's space. And so over time, those people have been really influential on us as well. And having that little inner [00:25:35] circle, and it's a few hundred people now of people who, you know, like if you have a question to ask about something tricky. There's probably somebody in there who has tried it, but more significantly, like the answer will come from somebody who has tried it, not from somebody who will call you an idiot for trying or who will, right, like you, you avoid all the, don't read the comments problems because the sort of like, if anybody was like that, I would probably ask them to leave, but we've been fortunate that we haven't had any of that kind of stuff in the community. I will say though, I think I struggle a lot because I think. It's hard to be both exclusive and inclusive. Right, but exclusive community deliberately in the sense that I want it to be a practitioner's space and one where people can be wrong and it's not too performative, like there's not investors watching or your, your user base or whatever. [00:26:32] Ben: Yeah. [00:26:32] Peter: at the same time, [00:26:33] Ben: strangers. [00:26:34] Peter: [00:26:35] inclusive space where we have people who are earlier in their career or. From non-traditional backgrounds, you know, either academically or culturally or so on and so forth. And it takes constant work to be like networking out and meeting new people and like inviting them into this space. So it's always an area to, to keep working on. At some point, I think we will want to open the aperture further, but yeah, it's, it's, it's a delicate thing to build a community. [00:27:07] Ben: Yeah, I mean the, the, frankly, the reason I'm asking is because I'm trying to figure out the same things and you have done it better than basically anybody else that I've seen. This is, this is maybe getting too down into the weeds. But why did you decide that discourse or discord was the right tool for it? And the, the reason that I ask is that I personally hate sort of [00:27:35] streaming walls of texts, and I find it very hard to, to seriously discuss ideas in, in that format. [00:27:43] Peter: Yeah, I think async, I mean, I'm an old school like mailing list guy. On some level I think it's just a pragmatic thing. We use Discord for our internal like day-to-day operations like. Hey, did you see the pr? You know, oh, we gotta call in an hour with so-and-so, whatever. And then we had a bunch of people in that community and then, you know, we started having the workshops and inviting more people. So we created a space in that same discord where. You know, people didn't have to get pinged when we had a lab call and we didn't want 'em turning up on the zoom anyway. And so it wasn't so much like a deliberate decision to be that space. I think there's a huge opportunity to do better and you know, frankly, what's there is [00:28:35] not as designed or as deliberate as I would like. It's more consequence of Organic growth over time and just like continuing to do a little bit here and there than like sort of an optimum outcome. And it could, there, there's a lot of opportunity to do better. Like we should have newsletters, there should be more, you know, artifacts of past conversations with better organizations. But like all of that stuff takes time and energy. And we are about a small little research lab. So many people you know, [00:29:06] Ben: I, I absolutely hear you on that. I think the, the, the tension that I, I see is that people, I think like texting, like sort of stream of texts. Slack and, and discord type things. And, and so there's, there's the question of like, what can you get people to do versus like, what creates the, the right conversation environment?[00:29:35] And, and maybe that's just like a matter of curation and like standard setting. [00:29:42] Peter: Yeah, I don't know. We've had our, our rabbit trails and like derailed conversations over the years, but I think, you know, if you had a forum, nobody would go there. [00:29:51] Ben: Yeah. [00:29:52] Peter: like, and you could do a mailing list, but I don't know, maybe we could do a mailing list. That would be a nice a nice form, I think. But people have to get something out of a community to put things into it and you know, you have to make, if you want to have a forum or, or an asynchronous posting place, you know, the thing is people are already in Discord or slack. [00:30:12] Ben: exactly. [00:30:13] Peter: something else, you have to push against the stream. Now, actually, maybe one interesting anecdote is I did experiment for a while with, like, discord has sort of a forum post feature. They added a while back [00:30:25] Ben: Oh [00:30:25] Peter: added it. Nobody used it. So eventually I, I turned it off again. Maybe, maybe it just needs revisiting, but it surprised me that it wasn't adopted, I guess is what [00:30:35] I would say. [00:30:36] Ben: Yeah. I mean, I think it, I think the problem is it takes more work. It's very easy to just dash off a thought. [00:30:45] Peter: Yeah, but I think if you have the right community, then. Those thoughts are likely to have been considered and the people who reply will speak from knowledge [00:30:55] Ben: Yeah. [00:30:56] Peter: and then it's not so bad, right? [00:30:59] Ben: it's [00:30:59] Peter: The problem is with Hacker News or whatever where like, or Reddit or any of these open communities like you, you know, the person who's most likely to reply is not the person who's most helpful to apply. [00:31:11] Ben: Yeah, exactly. Yeah, that makes, that makes a lot of sense. And sort of switching tracks yet again, how so one, remind me how long your, your projects are, like how long, how big are the, is the time box. [00:31:28] Peter: the implementation phase for a standard income switch Hollywood project, which I can now call them standard, I think, cuz we've done like, [00:31:35] Ooh, let me look. 25 or so over the years. Let's see, what's my project count number at? I have a little. Tracker. Yeah, I think it's 25 today. So we've done about 20 some non-trivial number of these 10 to 12 weeks of implementation is sort of the core of the project, and the idea is that when you hit that start date, at the beginning of that, you should have the team assembled. You should know what you're building, you should know why you're building it, and you should know what done looks like. Now it's research, so inevitably. You know, you get two weeks in and then you take a hard left and like, you know, but that, that we write what's called the brief upfront, which is like, what is the research question we are trying to answer by funding this work and how do we think this project will answer it? Now, your actual implementation might change, or you might discover targets of opportunity along the way. But the idea is that by like having a, a narrow time box, like a, a team [00:32:35] that has a clear understanding of what you're trying to accomplish. And like the right set of people on board who already have all the like necessary skills. You can execute really hard for like that 10 to 12 weeks and get quite far in that time. Now, that's not the whole project though. There's usually a month or two upfront of what we call pre-infusion, kind of coming from the espresso idea that like you make better espresso if you take a little time at low pressure first to get ready with the shot, and so we'll do. You know, and duration varies here, but there's a period before that where we're making technical choices. Are we building this for the web or is this going on iPad? Are we gonna do this with rust and web assembly, or is this type script is this, are we buying Microsoft Surface tablets for this as we're like the ink behavior, right? So all those decisions we try and make up front. So when you hit the execution phase, you're ready to go. Do we need, what kind of designer do we want to include in this project? And who's available, you know? All of that stuff. We [00:33:35] try and square away before we get to the execution phase. [00:33:38] Ben: right. [00:33:38] Peter: when the end of the execution phase, it's like we try to be very strict with like last day pencils down and try to also reserve like the last week or two for like polish and cleanup and sort of getting things. So it's really two to two and a half, sometimes three months is like actually the time you have to do the work. And then after that, essays can take between like two months and a year or two. To produce finally. But we try to have a dr. We try to have a good first draft within a month after the end of the project. And again, this isn't a process that's like probably not optimal, but basically someone on the team winds up being the lead writer and we should be more deliberate about that. But usually the project lead for a given project ends up being the essay writer. And they write a first draft with input and collaboration from the rest of the group. And then people around [00:34:35] the lab read it and go, this doesn't make any sense at all. Like, what? What do you do? And you know, to, to varying degrees. And then it's sort of okay, right? Once you've got that kind of feedback, then you go back and you restructured and go, oh, I need to explain this part more. You know, oh, these findings don't actually cover the stuff that other people at the lab thought was interesting from the work or whatever. And then that goes through, you know, an increasing sort of, you know, standard of writing stuff, right? You send it out to some more people and then you send it to a bigger group. And you know, we send it to people who are in the field that whose input we respect. And then we take their edits and we debate which ones to take. And then eventually it goes in the HTML template. And then there's a long process of like hiring an external copy editor and building nice quality figures and re-recording all your crappy screencasts to be like, Really crisp with nice lighting and good, you know, pacing and, you know, then finally at the end of all of that, we publish. [00:35:33] Ben: Nice. And [00:35:35] how did you settle on the, the 10 to 12 weeks as the right size, time box? [00:35:42] Peter: Oh, it's it's it's, it's clearly rationally optimal. [00:35:46] Ben: Ah, of course, [00:35:47] Peter: No, I'm kidding. It's totally just, it became a habit. I mean, I think. Like I, I can give an intuitive argument and we've, we've experimented a bit. You know, two weeks is not long enough to really get into anything, [00:36:02] Ben: right. [00:36:02] Peter: and the year is too long. There's too much, too much opportunity to get lost along the way. There's no, you go too long with no real deadline pressure. It's very easy to kind of wander off into the woods. And bear in mind that like the total project duration is really more like six months, right? And so where we kind of landed is also that we often have like grad students or you know, people who are between other contracts or things. It's much easier to get people for three months than for eight months. And if I feel like [00:36:35] just intuitively, if I, if someone came to you with an eight month project, I'd be, I'm almost positive that I would be able to split it into two, three month projects and we'd be able to like find a good break point somewhere in the middle. And then write about that and do another one. And it's like, this is sort of a like bigger or smaller than a bread box argument, but like, you know, a month is too little and six months feels too long. So two to four months feels about right. In terms of letting you really get into, yeah, you can really get into the meat of a problem. You can try a few different approaches. You can pick your favorite and then spend a bit of time like analyzing it and like working out the kinks. And then you can like write it up. [00:37:17] Ben: Thanks. [00:37:18] Peter: But you know, there have been things that are not, that haven't fit in that, and we're doing some stuff right now that has, you know, we've had a, like six month long pre-infusion going this year already on some ink stuff. So it's not a universal rule, but like that's the, that's the [00:37:33] Ben: Yeah. No, I [00:37:35] appreciate that intuition [00:37:36] Peter: and I think it also, it ties into being software again, right? Like again, if you have to go and weld things and like [00:37:43] Ben: yeah, exactly. [00:37:44] Peter: You know, [00:37:44] Ben: let let some bacteria grow. [00:37:46] Peter: or like, you know, the, it's very much a domain specific answer. [00:37:51] Ben: Yeah. Something that I wish people talked about more was like, like characteristic time scales of different domains. And I, I think that's software, I mean, software is obviously shorter, but it'd be interesting to, to sort of dig down and be like, okay, like what, what actually is it? So the, the, the last question I'd love to ask is, To what extent does everybody in the lab know what's, what everybody else is working on? Like. [00:38:23] Peter: So we use two tools for that. We could do a better job of this. Every Monday the whole lab gets together for half an hour only. [00:38:35] And basically says what they're doing. Like, what are you up to this week? Oh, we're trying to like, you know, figure out what's going on with that you know, stylist shaped problem we were talking about at the last demo, or, oh, we're, you know, we're in essay writing mode. We've got a, we're hoping to get the first draft done this week, or, you know, just whatever high level kind of objectives the team has. And then I was asked the question like, well, Do you expect to have anything for show and tell on Friday and every week on Friday we have show and tell or every other week. Talk a bit more about that and at show and tell. It's like whatever you've got that you want input on or just a deadline for you can share. Made some benchmark showing that this code is now a hundred times faster. Great. Like bring it to show and tell. Got that like tricky you know, user interaction, running real smooth. Bring it to show and tell, built a whole new prototype of a new kind of [00:39:35] like notetaking app. Awesome. Like come and see. And different folks and different projects have taken different approaches to this. What has been most effective, I'm told by a bunch of people in their opinion now is like, kind of approaching it. Like a little mini conference talk. I personally actually air more on the side of like a more casual and informal thing. And, and those can be good too. Just from like a personal alignment like getting things done. Perspective. What I've heard from people doing research who want to get useful feedback is that when they go in having sort of like rehearsed how to explain what they're doing, then how to show what they've done and then what kind of feedback they want. That not only do they get really good feedback, but also that process of making sure that the demo you're gonna do will actually run smoothly and be legible to the rest of the group [00:40:35] forces you. Again, just like the writing, it forces you to think about what you're doing and why you made certain choices and think about which ones people are gonna find dubious and tell them to either ignore that cuz it was a stand-in or let's talk about that cuz it's interesting. And like that, that that little cycle is really good. And that tends to be, people often come every two weeks for that [00:40:59] Ben: Yeah. [00:41:01] Peter: within when they're in active sort of mode. And so not always, but like two weeks feels about like the right cadence to, to have something. And sometimes people will come and say like, I got nothing this week. Like, let's do it next week. It's fine. And the other thing we do with that time is we alternate what we call zoom outs because they're on Zoom and I have no, no sense of humor I guess. But they're based on, they're based on the old you and your research hamming paper with where the idea is that like, at least for a little while, every week [00:41:35] we all get together and talk about something. Bigger picture that's not tied to any of our individual projects. Sometimes we read a paper together, sometimes we talk about like an interesting project somebody saw, you know, in the world. Sometimes it's skills sharing. Sometimes it's you know, just like, here's how I make coffee or something, right? Like, You know, just anything that is bigger picture or out of the day-to-day philosophical stuff. We've read Illich and, and Ursula Franklin. People love. [00:42:10] Ben: I like that a lot. And I, I think one thing that, that didn't, that, that I'm still wondering about is like, On, on sort of a technical level are, are there things that some peop some parts of the lab that are working on that other parts of the lab don't get, like they, they know, oh, like this person's working on [00:42:35] inks, but they kind of have no idea how inks actually work? Or is it something where like everybody in the lab can have a fairly detailed technical discussion with, with anybody else [00:42:45] Peter: Oh no. I mean, okay, so there are interesting interdependencies. So some projects will consume the output of past projects or build on past projects. And that's interesting cuz it can create almost like a. Industry style production dependencies where like one team wants to go be doing some research. The local first people are trying to work on a project. Somebody else is using auto merge and they have bugs and it's like, oh but again, this is why we have those Monday sort of like conversations. Right? But I think the teams are all quite independent. Like they have their own GitHub repositories. They make their own technology decisions. They use different programming languages. They, they build on different stacks, right? Like the Ink team is often building for iPad because that's the only place we can compile like [00:43:35] ink rendering code to get low enough latency to get the experiences we want. We've given up on the browser, we can't do it, but like, The local first group for various reasons has abandoned electron and all of these like run times and mostly just build stuff for the web now because it actually works and you spend all, spend way less calories trying to make the damn thing go if you don't have to fight xcode and all that kind of stuff. And again, so it really varies, but, and people choose different things at different times, but no, it's not like we are doing code review for each other or like. Getting into the guts. It's much more high level. Like, you know, why did you make that, you know, what is your programming model for this canvas you're working on? How does you know, how does this thing relate to that thing? Why is, you know, why does that layout horizontally? It feels hard to, to parse the way you've shown that to, you know, whatever. [00:44:30] Ben: Okay, cool. That, that makes sense. I just, I, the, the, the reason I ask [00:44:35] is I am just always thinking about how how related do projects inside of a single organization need to be for, like, is, is there sort of like an optimum amount of relatedness? [00:44:50] Peter: I view them all as the aspects of the same thing, and I think that that's, that's an important. Thing we didn't talk about. The goal of income switch is to give rise to a new kind of computing that is more user-centric, that's more productive, that's more creative in like a very raw sense that we want people to be able to think better thoughts, to produce better ideas, to make better art, and that computers can help them with that in ways that they aren't and in fact are [00:45:21] Ben: Yeah. [00:45:25] Peter: whether you're working on ink, Or local first software or malleable software media canvases or whatever domain you are working in. It [00:45:35] is the same thing. It is an ingredient. It is an aspect, it is a dimension of one problem. And so some, in some sense, all of this adds together to make something, whether it's one thing or a hundred things, whether it takes five years or 50 years, you know, that's, we're all going to the same place together. But on many different paths and at different speeds and with different confidence, right? And so in the small, the these things can be totally unrelated, but in the large, they all are part of one mission. And so when you say, how do you bring these things under one roof, when should they be under different roofs? It's like, well, when someone comes to me with a project idea, I ask, do we need this to get to where we're going? [00:46:23] Ben: Yeah, [00:46:24] Peter: And if we don't need it, then we probably don't have time to work on it because there's so much to do. And you know, there's a certain openness to experimentation and, [00:46:35] and uncertainty there. But that, that's the rubric that I use as the lab director is this, is this on the critical path of the revolution?  

Sempre più sviluppatori si stanno avvicinando al mondo .NET e a C#. In questo episodio vi dico da quali video tutorial poter iniziare ad apprendere le basi di .NET, C#, ASP.NET e Blazor.https://dotnet.microsoft.com/en-us/learn/videos

Composer and Latin Grammy-nominated conductor Dimitri Cervo presents in this album his complete piano works, in a comprehensive selection of pieces that span nearly four decades of creative output.   Interpreted by Lucas Thomazinho, one of the most prominent figures in the contemporary piano scene, the album showcases the ongoing artistic evolution and rich diversity of musical influences that permeate Cervo's body of work.   The album features three distinct phases in Cervo's compositional journey: The first phase, spanning from 1985 to 1997, is notably marked by the influence of classical piano repertoire, with special reverence for the works of Scriabin and Chopin, whose works were intensely studied by Cervo during his academic piano training. Standouts from this phase include Estudo (1985), with its intricate rhythmic changes, and Prelúdio Titanic (1985), an evocative piece that portrays the history of the famous ship. The second creative phase (1998-2010) is characterized by the innovative fusion of distinctive elements of Brazilian music with minimalism. Finally, the third and current phase, which began in 2011 and continues to the present day, is marked by the amalgamation of various influences and the consolidation of the composer's artistic maturity and innovative vision in the contemporary musical landscape. Tracks1. Estudo (1985) (01:11) 2. Prelúdio in B Major (1985) (01:49) 3. Prelúdio “Titanic” (1985) (01:39) 4. Prelúdio in C-Sharp (1988) (01:27) 5. Toccata Fantástica (1989) (04:41) 6. Prelúdio I (1990) (01:57) 7. Prelúdio II (1991) (02:33) 8. Prelúdio III (1990) (02:48) 9. Prelúdio IV (1995) (03:33) 10. Flot (1994) (07:28) 11. Brasil 2000 (1998) (07:54) 12. Tema para Filme I (2005) (03:22) 13. Tema para Filme II (1989) (03:00) 14. Tema para Filme III (2007) (04:02) 15. Tema para Filme IV (2008) (01:35) 16. Tema para Filme V (2008) (04:32) 17. Tema para Filme VI (1987) (00:59) 18. Tema para Filme VII (2021) (01:23) 19. Variações Ternas Sobre um Tema de Ronaldo Miranda (2022) (05:41) Classical Music Discoveries is sponsored by Uber. @CMDHedgecock#ClassicalMusicDiscoveries #KeepClassicalMusicAlive#CMDGrandOperaCompanyofVenice #CMDParisPhilharmonicinOrléans#CMDGermanOperaCompanyofBerlin#CMDGrandOperaCompanyofBarcelonaSpain#ClassicalMusicLivesOn#Uber#AppleClassical Please consider supporting our show, thank you!Donate (classicalmusicdiscoveries.store) staff@classicalmusicdiscoveries.comThis album is broadcast with the permission of Bárbara Leu from Azul Music.         

Ready to jump into the captivating realm of coding and computer technology? This episode promises an intriguing exploration of the journey from early computing to the cutting-edge applications of artificial intelligence in software development. Join us with Thomas Theunen, head of commerce at Forward, as he reminisces about his fascinating evolution from a curious child tinkering with his first computer to becoming a tech-savvy forward thinker.  Interested in how languages evolve in the world of coding? From Thomas's maiden voyage with C Sharp, his engagement with Windows Phone applications, to his dedicated seven-year expedition with Java at an enterprise level, it's a rollercoaster ride through the tech landscape. Our discussion dives deep into the Salesforce ecosystem, JavaScript development, and the emerging uses of AI in speeding up workflows. Lastly, Thomas discusses the burgeoning B2C Commerce Cloud community and his invaluable contributions to it.  This isn't just an episode; it's a chronicle of a tech enthusiast's journey, making it a must-listen for all computer technology and coding enthusiasts! Show Highlights: Thomas's professional journey with software development languages. His experience transitioning into the Salesforce ecosystem, JavaScript development with BTC Commerce Cloud, and his evolution from a developer to an architect. The role of AI in software development, how it has helped Thomas speed up his workflows, and the importance of human involvement in reviewing AI-generated solutions. Thomas' contribution to the B2C Commerce Cloud community, its growth over the years, and his insights into using React in development. The transformative role of AI in workflow improvement, from aiding in code generation to simplifying unit tests. Links: Thomas on LinkedIn: https://www.linkedin.com/in/thomas-theunen-10905680/  

Professor Dame Lesley Regan is the Government's first Women's Health Ambassador for England. She is one of the main drivers behind the upcoming Women's Health Strategy which aims to tackle the gender health gap and improve services for women. As a former president of the Royal College of Obstetricians and Gynaecologists – only the second woman to hold that post in its 94-year history – she shone a light on historically taboo subjects from period problems and contraception to the menopause. Lesley was born in London in 1956. When she was seven she told her father that she wanted to be a doctor and although the sciences weren't her strongest subjects at school, she won a place at the Royal Free Hospital Medical School in London in 1975. In 1991 she was appointed a senior lecturer in Obstetrics and Gynaecology at St Mary's Hospital in London and consultant at Imperial College Healthcare NHS Trust. The following year she set up the Recurrent Miscarriage Clinic at St Mary's which is the largest miscarriage referral service in the world. In 2020 she was appointed a DBE for services to women's healthcare. DISC ONE: Mr Bojangles – Nina Simone DISC TWO: Symphony No. 5 in C Sharp. Composed by Mahler and performed by Berliner Philharmoniker DISC THREE: Agnus Dei. Composed by Bach and performed by Iestyn Davies, (counter-tenor), The English Consort, conducted by Harry Bicket DISC FOUR: I Cried for You - Katie Melua DISC FIVE: Norma: Act I, Scene 1: Casta diva (Norma/Coro) Composed by Vincenzo Bellini and performed by Maria Callas (soprano), The Teatro Alla Scala Orchestra, conducted by Tullio Serafin DISC SIX: The Best – Tina Turner DISC SEVEN: Metamorpheme – Shakespeare and the Bible DISC EIGHT: Clarinet Concerto In A, K. 622 - II. Adagio. Composed by Mozart and performed by Karl Leister (clarinet) and Berliner Philharmoniker, conducted by Herbert Von Karajan BOOK CHOICE: The Works of George Eliot LUXURY ITEM: Marmite on toast CASTAWAY'S FAVOURITE: The Best – Tina Turner Presenter Lauren Laverne Producer Paula McGinley

On this bonus episode, originally recorded as a Patreon bonus in 2022, Kirk goes through a few great Legend of Zelda pieces that he didn't manage to get into on last year's Zelda-focused Strong Songs episode. If you want to hear next week's new episode on Tears of the Kingdom early, go become a patron now!FEATURED:"Tears of the Kingdom Theme" from The Legend of Zelda: Tears of the Kingdom, comp. Manaka Kataoka, Maasa Miyoshi, Masato Ohashi, Tsukasa Usui"Song of Storms," "Dark World/Lorule Theme," "Gerudo Valley," and "The Great Fairy's Fountain" by Koji KondoVarious themes from Crypt of the Necrodancer: Cadence of Hyrule, composed by Danny Baranowski feat Jules Conroy on guitarDr. Pez's Ocarina of Time prog album: https://www.youtube.com/watch?v=pDH3g6rRjM8Fantasie-impromptu in C-Sharp" by Frédéric Chopin, 1815, performed by Arthur Rubinstein-----LINKS-----SUPPORT STRONG SONGSPaypal | Patreon.com/StrongsongsMERCH STOREstore.strongsongspodcast.comSOCIAL MEDIA@StrongSongs | @Kirkhamilton | IG: @Kirk_HamiltonNEWSLETTERhttps://kirkhamilton.substack.com/subscribeJOIN THE DISCORDhttps://discord.gg/GCvKqAM8SmOUTRO SOLO PLAY-A-LONG:https://soundcloud.com/kirkhamilton/strong-songs-outro-music-no-soloSTRONG SONGS PLAYLISTSSpotify | Apple Music | YouTube Music---------------OCTOBER 2023 WHOLE-NOTE PATRONSCorpus FriskyBen BarronCatherine WarnerDamon WhiteKaya WoodallDan AustinJay SwartzMiriam JoySEAN D WINNIERushDaniel Hannon-BarryChristopher MillerJamie WhiteChristopher McConnellDavid MascettiJoe LaskaKen HirshJezMelanie AndrichJenness GardnerDave SharpeSami SamhuriJeremy DawsonAccessViolationAndre BremerDave FloreyOCTOBER 2023 HALF-NOTE PATRONSDent EarlCarlos LernerMisty HaisfieldAbraham BenrubiChristopher BrunoChris KotarbaCallum WebbLynda MacNeilDick MorganBen SteinSusan GreenSean MurphyJake YumatillaAlan BroughRandal VegterGo Birds!Whit SidenerRobert Granatdave malloyNick GallowayHeather Johnsonjohn halpinPeter HardingDavidMeghan O'LearyJohn BaumanDax and Dane HuddlestonMartín SalíasStu BakerSteve MartinoDr Arthur A GrayCarolinaGary PierceMatt BaxterGiantPredatoryMolluskLuigi BocciaE Margaret WartonCharles McGeeCatherine ClauseEthan BaumanKenIsWearingAHatJordan BlockAaron WadeJeff UlmJamieDeebsPortland Eye CareCarrie SchneiderRichard SneddonJulian RoleffDoreen CarlsonDavid McDarbyWendy GilchristElliot RosenLisa TurnerPaul WayperBruno GaetaKenneth JungAdam StofskyZak RemerRishi SahayJason ReitmanAilie FraserRob TsukNATALIE MISTILISJosh SingerPhino DeLeonAmy Lynn ThornsenAdam WKelli BrockingtonVictoria YuBrad Clarkmino caposselaSteve PaquinEmma SklarBernard KhooRobert HeuerMatthew GoldenDavid NoahGeraldine ButlerMadeleine MaderJason PrattAbbie BergDoug BelewDermot CrowleyAchint SrivastavaRyan RairighMichael BermanOlivia BishopJohn GisselquistLinda DuffyBonnie PrinsenLiz SegerEoin de BurcaKevin PotterM Shane BordersDallas HockleyJason GerryNathan GouwensLauren ReayEric PrestemonDamian BradyAngela LivingstoneDavid FriedmanSarah SulanDiane HughesMichael CasnerLowell MeyerStephen TsoneffWenGeoff GoldenRob FPascal RuegerRandy SouzaClare HolbertonDiane TurnerTom ColemanMark PerryDhu WikMelEric HelmJonathan DanielsMichael FlahertyJarrod SchindlerCaro Fieldmichael bochnerNaomi WatsonDavid CushmanAlexanderChris KGavin DoigSam FennTanner MortonAJ SchusterJennifer BushDavid StroudAmanda FurlottiAndrew BakerJules BaileyAndrew FairL.B. MorseBill ThorntonBrian AmoebasBrett DouvilleJeffrey OlsonMatt BetzelNate from KalamazooMelanie StiversRichard TollerAlexander PolsonEarl LozadaJustin McElroyArjun SharmaJames JohnsonKevin MorrellColin Hodo

In today's episode, Sundi and Owen are joined by Yordis Prieto and Stephen Chudleigh to compare notes on HTTP requests in Elixir vs. Ruby, JavaScript, Go, and Rust. They cover common pain points when working with APIs, best practices, and lessons that can be learned from other programming languages. Yordis maintains Elixir's popular Tesla HTTP client library and shares insights from building APIs and maintaining open-source projects. Stephen has experience with Rails and JavaScript, and now works primarily in Elixir. They offer perspectives on testing HTTP requests and working with different libraries. While Elixir has matured, there is room for improvement - especially around richer struct parsing from HTTP responses. The discussion highlights ongoing efforts to improve the developer experience for HTTP clients in Elixir and other ecosystems. Topics Discussed in this Episode HTTP is a protocol - but each language has different implementation methods Tesla represents requests as middleware that can be modified before sending Testing HTTP requests can be a challenge due to dependence on outside systems GraphQL, OpenAPI, and JSON API provide clear request/response formats Elixir could improve richer parsing from HTTP into structs Focus on contribution ergonomics lowers barriers for new participants Maintainers emphasize making contributions easy via templates and clear documentation APIs drive adoption of standards for client/server contracts They discuss GraphQL, JSON API, OpenAPI schemas, and other standards that provide clear request/response formats TypeScript brings types to APIs and helps to validate responses Yordis notes that Go and Rust make requests simple via tags for mapping JSON to structs Language collaboration shares strengths from different ecosystems and inspires new libraries and tools for improving the programming experience Links Mentioned Elixir-Tesla Library: https://github.com/elixir-tesla/tesla Yordis on Github: https://github.com/yordis Yordis on Twitter: https://twitter.com/alchemist_ubi Yordis on LinkedIn: https://www.linkedin.com/in/yordisprieto/ Yordis on YouTube: https://www.youtube.com/@alchemistubi Stephen on Twitter: https://twitter.com/stepchud Stephen's projects on consciousness: https://harmonicdevelopment.us Owen suggests: Http.cat HTTParty: https://github.com/jnunemaker/httparty Guardian Library: https://github.com/ueberauth/guardian Axios: https://axios-http.com/ Straw Hat Fetcher: https://github.com/straw-hat-team/nodejs-monorepo/tree/master/packages/%40straw-hat/fetcher Elixir Tesla Wiki: https://github.com/elixir-tesla/tesla/wiki HTTPoison: https://github.com/edgurgel/httpoison Tesla Testing: https://hexdocs.pm/tesla/readme.html#testing Tesla Mock: https://hexdocs.pm/tesla/Tesla.Mock.html Finch: https://hex.pm/packages/finch Mojito: https://github.com/appcues/mojito Erlang Libraries and Frameworks Working Group: https://github.com/erlef/libs-and-frameworks/ and https://erlef.org/wg/libs-and-frameworks Special Guests: Stephen Chudleigh and Yordis Prieto.

Hosts Dan Ivovich, Owen Bickford, and Sundi Myint kick off the 11th season of the Elixir Wizards podcast. This season's theme is “Branching Out from Elixir,” which expands the conversation to compare notes with experts from other communities; they discuss their experiences with other languages like JavaScript, PHP, Python, Ruby, C#, Go, and Dart before and after learning Elixir. This season's conversations will illuminate how problems are solved in different languages vs. Elixir; upcoming episode topics teased include education, data processing, deployment strategies, and garbage collection; the hosts express excitement for conversations analyzing similarities and differences between communities. Topics Discussed in this Episode Season 11 branches out from Elixir to compare notes with other programming communities Sundi, Owen, and Dan introduce the season theme and their interest in exploring these conversations The hosts compare their experiences with PHP, JavaScript, Python, Ruby, C#, Go, Dart and Elixir The Wizards compare and contrast differences in their personal experience building similar things with different languages Dan dreams in Ruby and uses it for quick prototypes Comparing problem-solving approaches across languages will reframe perspectives Upcoming episodes explore data processing workflows, machine learning, and game development Pop Quiz: Who's that Pokémon... or language, or framework? Links Mentioned https://smartlogic.io/ https://codepen.io/ https://i.redd.it/0lg7979qtr511.jpg

C# DevKit "Now Generally Available". Da Visual Studio Code è ora possibile sviluppare applicazioni C# (ASP.NET, Blazor, ...) con ancora più facilità e con un'esperienza molto più vicina a quella che ci ha abituato il fratello maggiore Visual Studio 2022.- https://marketplace.visualstudio.com/items?itemName=ms-dotnettools.csdevkit- https://devblogs.microsoft.com/dotnet/csharp-dev-kit-now-generally-available/

FULL SHOW NOTES https://podcast.nz365guy.com/486 You're in for a treat as we invite you to listen to our special guest Tchesco Ayih's fascinating transformation from dabbling in a computer repair shop to becoming an MVP in Ghana. With our fireside chat, we delve into Tchesco's inspiring journey that's marked by his love for cooking and gaming, his self-taught graphic design and C-Sharp skills, and his unexpected MVP award. He'll let you in on his approach to learning new skills, staying updated with the latest trends, and the significance of being part of tech communities. Moving on, we'll traverse the evolving landscape of the Power Platform community in Ghana, its inception, growth, and the key role MVP Abu Kondi played in shaping it. We'll also draw parallels with the community growth in Nigeria and shed light on Tchesco's efforts to bolster the French community's involvement in this tech revolution. Join us and get captivated by Tchesco's story of perseverance, thirst for knowledge, and the influence of tech communities in transforming lives. It's an insightful ride you wouldn't want to miss.OTHER RESOURCES: Microsoft MVP YouTube Series - How to Become a Microsoft MVP  90-Day Mentoring Challenge - https://ako.nz365guy.com/ AgileXRM AgileXRm - The integrated BPM for Microsoft Power PlatformSupport the showIf you want to get in touch with me, you can message me here on Linkedin.Thanks for listening

Join us as we welcome Rob Cowell, a renowned DevOps advocate, on a journey through his personal and professional life in the world of programming and Salesforce. Starting with his early experiences tinkering with a Sord M5 computer, Rob shares how he transformed his passion for programming into a fulfilling career. We trace his evolution from working with Microsoft Access to .NET, C Sharp, and ultimately Salesforce and Apex, highlighting the importance of continuous learning and adaptation in the fast-paced tech industry. Transitioning into his current role, Rob pulls back the curtain on what it truly means to be a DevOps advocate. Emphasizing the significance of communication, collaboration, small incremental changes, and automation, he discusses how a commitment to quality is integral to delivering excellent results. The episode also explores the role of a Salesforce DevOps engineer and how to adopt the required skill set. Tune in to glean invaluable insights from Rob's vast experience and deep knowledge of the Salesforce ecosystem. Show Highlights: The role and importance of Salesforce DevOps in delivering quality results efficiently. The key components of Salesforce DevOps include communication, collaboration, small incremental changes, and automation. The transition from traditional development stacks into Salesforce and the unique elements of the platform. The role of a Salesforce DevOps engineer and how to adopt the necessary skill set. The introduction of Rob Cowell's project, 'Shirt Force,' which combines humor and philanthropy by creating Salesforce-themed t-shirts and donating the profits to charity. Insights into continuous improvement and the importance of adapting DevOps to your way of working. Links: Julián on LinkedIn: https://linkedin.com/in/juliandavidduque Rob on LinkedIn: https://www.linkedin.com/in/rob-cowell/ Rob's Twitter/X: @RobSalesforce Other resources: Gearset: https://gearset.com/ DevOps Launchpad free training and certs: https://devopslaunchpad.com/ Shirtforce: https://shirtforce.org/ His work on the demoscene: https://demozoo.org/sceners/32053/

Learning has become a superpower in the modern world we live in. But learning at a deep level is something that is extremely challenging. In this episode we explore the topic of Intentional Mastery and why it matters.Key topics covered in this episode:

James does some experiments with building .NET MAUI UI without any XAML at all and completely in C#! We discuss the pros, cons, and if James will continue his journey to C# only! Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us (https://itunes.apple.com/us/podcast/merge-conflict/id1133064277?mt=2&ls=1) ⭐⭐ Machine transcription available on http://mergeconflict.fm

High availability, data model flexibility, elastic scalability… If these words have piqued your interest, then this is the episode for you!   Join Lois Houston and Nikita Abraham, along with Autumn Black, as they discuss how Oracle NoSQL Database Cloud Service is designed for today's most demanding applications, ensuring fast and predictable single-digit millisecond response times at scale, even as throughput requirements change.   Oracle MyLearn: https://mylearn.oracle.com/ Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ Twitter: https://twitter.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Ranbir Singh, and the OU Studio Team for helping us create this episode.   -------------------------------------------------------   Episode Transcript: 00;00;00;00 - 00;00;38;28 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started. Hello and welcome to the Oracle University Podcast. I'm Nikita Abraham, Principal Technical Editor with Oracle University, and with me is Lois Houston, Director of Product Innovation and Go to Market Programs.   00;00;39;01 - 00;01;04;26 Hi there! Many of today's modern applications face a lot of different challenges. These could be anything from managing data models that are continuously evolving to providing UIs that are highly responsive. Yeah, and that's because in today's environment, no one wants to go to an interface where they have to wait for minutes or even seconds, really. Exactly. So innovations have to happen rapidly and they have to keep up with the demands of the customer base.   00;01;05;01 - 00;01;27;25 Since we discussed the MySQL database in our last episode, we thought it would only make sense to talk about NoSQL next. And we're very happy to have Oracle Database Specialist Autumn Black joining us again. Hi Autumn. What can you tell us about Oracle NoSQL Database Cloud Service? The Oracle NoSQL Database Cloud Service really offers a lot of great properties.   00;01;27;28 - 00;01;53;28 It's serverless, always on, and fully managed by Oracle. Developers can focus on application development without having to worry about managing servers, storage expansion, cluster deployment, software installation, or even backups. It's fully elastic. You just provision the throughput and storage capacity your application requires. Resources are automatically allocated and they scale accordingly to meet the dynamic workload requirements that you have.   00;01;54;01 - 00;02;18;16 The service provides predictable low latency for all types of application workload, whether it's at the peak workload or at a very low level of the workload. The latency is always at sub 10 milliseconds. Flexible data model supports document, columnar, and key value formats to capture any of the kinds of data you may have. These data models can interoperate with each other using a single application interface.   00;02;18;18 - 00;02;49;04 It offers developer-friendly APIs, and it's integrated with popular application development tools. It comes with enterprise-grade security. It's cost-effective. Lastly, and most importantly, it makes hybrid cloud or multi-cloud deployment with Oracle NoSQL Database extremely easy. This enables enterprises to expand their business operations, open up new business potential and opportunities. Autumn, you said Oracle NoSQL Database Cloud Service is fully managed by Oracle.   00;02;49;06 - 00;03;09;17 What does that exactly mean? What are the things that Oracle really handles? Oracle's responsible for the back-end software and hardware. The developer gets to focus on the application and who can use that application. Today's modern developers are not interested in what's going on behind the scenes. They want to be sure that they can get what they want when they want it.   00;03;09;20 - 00;03;36;03 Could you tell us about some use cases where we'd see Oracle NoSQL Database Cloud Service being used? We see it in mobile applications. We see it in the Internet of Things. We see it in a 360-degree customer view that's extremely prevalent in banking applications. We see it in the user profile management catalog data, such as what you would see maybe on Amazon, content management, online advertising, and big-time real data, social media.   00;03;36;05 - 00;03;59;20 And we also see it being used in the area of gaming. We've heard that Oracle NoSQL Database Cloud Service is extremely developer-friendly. How exactly is it developer-friendly? You can deploy your application to the data store in a matter of minutes. We have SDKs available in all the popular languages. We have Java, Python, Node.js, Go. We also have Spring.   00;03;59;22 - 00;04;24;24 We have open standards for our APIs, and we use the SQL language. Many, many folks already know and understand the SQL language and they can easily adapt to our APIs. We basically allow for simple and complex data types. We have our developer tools in Eclipse, IntelliJ, and Visual Studios. And for those who want to play with the service a little bit, you have full access to the service through the UI console.   00;04;24;27 - 00;04;48;05 Does Oracle NoSQL Database Cloud Service support different data models? You get to select that depending upon what you need. There's fixed schema, right? Sometimes referred to as a columnar store, sometimes referred to as just straight schema. And a JSON document? Sometimes it's referred to as just documents, and sometimes it's referred to as a JSON document. Other times, it gets referred to as schema lists.   00;04;48;08 - 00;05;07;17 We can store both of these within the same table, and we also have the ability to store a key value, which in some sense is really nothing more than a very simplified JSON document where you sort of have a primary key known as your key. Then you have your value and then oftentimes this value is really nothing more than a JSON document.   00;05;07;20 - 00;05;32;10 We have complete interoperability between either of these different types of data models. And what's the pricing like? Our pricing model is fairly straightforward. You basically pay for what you provision and different workflows can provision different amounts. The provision occurs on a per-table level that we have. We call it a read unit or write unit and storage. And each of those different parameters can be adjusted differently for each of the tables that you have.   00;05;32;12 - 00;05;44;08 So, it's a very, very simple model, very straightforward. And the cost for each one of those is extremely inexpensive.   00;05;44;10 - 00;06;14;09 Have you been wanting to earn an Oracle certification? Well, there's never been a better time than the present. Now through August 31st, you can choose from over 20 different Oracle certifications and take up to four exams for free, including foundation, associate, and professional-level Oracle Cloud Infrastructure certifications. You can also learn and get certified on Oracle Cloud Applications Business Processes for Human Capital Management, Financials, Customer Experience, Supply Chain, and Procurement.   00;06;14;13 - 00;06;40;25 And did I mention this was all free? Oracle Cloud training and certifications empower you to explore limitless possibilities in the cloud landscape. Gain the knowledge and skills needed to design, deploy, secure, and operate modern cloud infrastructure and applications with confidence. You can go to education.oracle.com for more details. What are you waiting for? Get certified today.   00;06;40;27 - 00;07;03;24 Welcome back. Now that we've covered all of that, let's get down to business. What is Oracle NoSQL Database Cloud Service? How does it help one's business? Well, really, it's a client server architecture. On the client side, an application interacts with NoSQL drivers, or sometimes more commonly referred to as our SDK. So, you develop the application.   00;07;03;25 - 00;07;31;08 And then at compile time, you include the SDK in that. Drivers are available for Java, Python, Node.js, Go, Spring, and C-Sharp. So then the application runs and it does database operations like insert, update, query, delete against the NoSQL tables that are stored on the server side. So from the developer's point of view, that's all they need to know. It's extremely simple. NoSQL tables can be created in seconds.   00;07;31;10 - 00;08;01;08 Developers can start right away to develop and deploy their applications. Businesses can focus on rapid innovations to better serve their customer's needs and expectations. So what you're saying is developers and IT don't need to manage any computing, infrastructure, or software updates. The NoSQL service comes with the high availability built in. So, all of the underlying compute services and software maintenance, all of that is fully managed by Oracle, which is hosting the NoSQL tables.   00;08;01;11 - 00;08;24;10 Database administrators will work on the authentication, the roles, the privileges, and the other types of access that are used to access the tables. Autumn, earlier on, we spoke about how easy it is to use Oracle NoSQL Database Cloud Service to develop your application. Can you talk about how NoSQL drivers connect to tables and perform database operations? So, each table has a couple of different key components.   00;08;24;12 - 00;08;49;16 The first one is the data component. So, it consists of a table definition or flexible data model, supports columnar key value or document models. We support many different data types, including integer, string, binary, long double, array, JSON, record, and a few others. Each column can be defined by a particular data type. So that could be integers, strings, and JSON columns, right?   00;08;49;16 - 00;09;06;21 Then we have a primary key which is identified. The primary key sort of doubles as the shard key and the shard key can be either a sort of complete copy of the primary key, or you can have a multicolumn key where some of those columns is your primary key and then other columns in that are your shard key.   00;09;06;24 - 00;09;30;25 The other component of a table is the capacity that is provisioned. What's an example of this? We have three units. We have write units, read units, and we have storage. Storage is expressed in gigabytes and this is the maximum amount of storage that is allocated for this particular table. Reads and writes are expressed in units. Each of those units represents a one kilobyte read or write for every second.   00;09;30;27 - 00;09;52;17 So, if you have an application where you wanted to do multiple reads a second, then you would allocate multiple read units for that particular table. And these can be dynamically adjusted. What are the different ways in which you can experience Oracle NoSQL Database Cloud Service? The first is accessing the cloud service to the service UI, probably more commonly referred to as the UI console.   00;09;52;19 - 00;10;20;12 The UI console provides basic capability. You can create and delete tables and then you can execute very simple, straightforward SQL statements against your table. If you want a richer experience, where you have an application that's developed. And then through all of our SDKs, you'll have the full experience and you'll be able to do the complete set of SQL statements that we offer. And then finally, we have what we call the NoSQL Cloud Simulator, essentially a single process version of our cloud.   00;10;20;15 - 00;10;40;06 It's very easy to use. Many of our customers use that for test and development, and the beauty with using that for testing development is there's no cost to you. There's no cost from the cloud service. You can develop your application, you can test it, and once you're ready to deploy it in the cloud, you might be able to do part of it through the UI or you could do it through your application.   00;10;40;06 - 00;11;07;14 Autumn, what makes Oracle NoSQL Database Cloud Service different? Well, there's a seamless multimodel. You have key value, fixed schema, you have schema-less, all at the same data store. The seamless SQL interoperates amongst any of these different kinds of data models. You have tunable ACID, you have shard local full ACID, you have parent tables for easy multiobject ACID. You can carefully balance the trade-offs of ACID and scale.   00;11;07;16 - 00;11;29;16 There is a fully managed cloud service. The throughput is provisioned, there is no lock-in. You have the ability to run as a fully managed service or you can take the NoSQL Database, run it anywhere. And if you want to run it in a hybrid environment, you can do that as well. Are there some additional resources that Oracle has, you know, where people can go to get more information?   00;11;29;18 - 00;11;56;04 I know we have the Developers Blog and blogs.oracle.com, but is there anything else? We have the Cloud Customer Connect, the developer community that we have for NoSQL. This gets monitored. We really have developers around the globe on the team so really this does get 24/7 coverage and we try to be very responsive to any types of questions that get posted on the forum and then we supply answers for all those questions.   00;11;56;06 - 00;12;18;19 Thank you so much, Autumn, for joining us through these last two episodes. We've learned so much from you. Learn more about the service by visiting mylearn.oracle.com and taking a look at our Oracle Cloud Data Management Foundations Workshop. You can also take skill checks to test your understanding of this topic. That brings us to the end of this episode.   00;12;18;19 - 00;12;41;26 In our next episode, we'll be joined by a very special guest who will talk about MySQL Document Store, a NoSQL solution that's built on top of MySQL. More on that next week. Until then, this is Lois Houston and Nikita Abraham signing off. That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes.   00;12;41;29 - 00;15;14;24 We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

It is follow up week on some topics we touched on earlier. We first break down our thoughts on C# 12's new Collection Literals, Apple Vision Pro + iCircuit, iOS 17, and some great developer productivity feature for .NET. Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us (https://itunes.apple.com/us/podcast/merge-conflict/id1133064277?mt=2&ls=1) ⭐⭐ Machine transcription available on http://mergeconflict.fm

  In our last episode, we learned about the Russian composer Sergei Rachmaninoff. You might recall learning that he composed in the Romantic style of music, and especially featured the piano in his work. Today we're going to take a more in-depth at some of his most famous piano compositions, his collection of preludes. While we won't learn about each and every one of them (he wrote one for each major and minor key!), we'll learn about the collection as a whole and some of the ones that are performed most frequently. MUSIC HEARD IN THIS EPISODE Rachmaninoff Prelude in C Sharp minor Op.3 No.2 Lisitsa Yuja Wang – Rachmaninov: Prelude in G Minor, Op. 23, No. 5 (Live at Philharmonie, Berlin / 2018) Ashkenazy plays Rachmaninov Prelude Op.32 No.12 in G sharp minor MUSIC LISTENING SCHEDULE FOR EPISODE 97 I've created a curated playlist on YouTube of some of the music from today's episode as well as complete performances of all Rachmaninoff's piano preludes. Listen to the playlist here. Subscribe & Review in Apple Podcasts Are you subscribed to my podcast? If you're not, head on over to do that today so you don't miss an episode. Click here to subscribe in Apple Podcasts! If you're feeling extra magnanimous, I would be really grateful if you left a review over on Apple Podcasts, too. Those reviews help other families find my podcast learn more about music. Just click here to review, select “Ratings and Reviews” and “Write a Review” and let me know what you love about Busy Kids Love Music. Thanks!

It is that time of year again! New C# features! That is right, .NET 8 Preview 3 just dropped and with it is the first preview features of C# 12 including Primary constructors for non-record classes and structs, using aliases for any type, and default values for lambda expression parameters. We break them all down! Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us (https://itunes.apple.com/us/podcast/merge-conflict/id1133064277?mt=2&ls=1) ⭐⭐ Machine transcription available on http://mergeconflict.fm

Few eras of gaming history are more legend filled than the British bedroom coder boom of the early 1980s.  Martin Wheeler wasn't just one of them but continues to be a pioneer or one-man coding in the VR space of today. Recorded March 2022. Get us on your mobile device: Android:  https://www.google.com/podcasts?feed=aHR0cHM6Ly92aWRlb2dhbWVuZXdzcm9vbXRpbWVtYWNoaW5lLmxpYnN5bi5jb20vcnNz iOS:      https://podcasts.apple.com/de/podcast/video-game-newsroom-time-machine And if you like what we are doing here at the podcast, don't forget to like us on your podcasting app of choice, YouTube, and/or support us on patreon! https://www.patreon.com/VGNRTM Send comments on twitter @videogamenewsr2 Or Instagram https://www.instagram.com/vgnrtm Or Mastodon https://oldbytes.space/@videogamenewsroomtimemachine Or videogamenewsroomtimemachine@gmail.com Links: https://recluseindustries.github.io/website/ https://www.linkedin.com/in/martinwheeler/?originalSubdomain=uk https://www.mobygames.com/developer/sheet/view/developerId,57393/ https://www.mobygames.com/game/dr-franky-and-the-monster https://www.mobygames.com/game/sorcery https://www.mobygames.com/game/zx-spectrum/dan-dare-pilot-of-the-future https://www.mobygames.com/game/dan-dare-pilot-of-the-future_ https://en.wikipedia.org/wiki/Dan_Dare https://www.mobygames.com/game/zx-spectrum/action-force-ii-international-heroes https://www.mobygames.com/game/prohibition https://www.mobygames.com/company/system-3-software-limited https://www.mobygames.com/game/dominator https://www.mobygames.com/company/bits-studios-ltd https://www.mobygames.com/game/gameboy/t2-terminator-2-judgment-day/screenshots/gameShotId,201379/ https://www.mobygames.com/game/warlocked https://en.wikipedia.org/wiki/Unity_(game_engine) https://en.wikipedia.org/wiki/ActionScript https://en.wikipedia.org/wiki/C_Sharp_(programming_language) Surveillant - https://www.youtube.com/watch?v=AQ6DwiUIPk8 https://en.wikipedia.org/wiki/PlayStation_VR https://www.mobygames.com/game/sentry_ https://www.mobygames.com/game/playstation-4/separation https://www.mobygames.com/game/ico  

Array Cast - January 20, 2023 Show NotesThanks to Bob Therriault for gathering these links:[01] 00:04:38 JSON for BQN https://github.com/mlochbaum/bqn-libs/blob/master/json.bqn[02] 00:05:32 Change the Way You Think talk https://www.youtube.com/watch?v=KOuwZEtHZ_U[03] 00:07:04 Ashok Reddy https://www.ajbell.co.uk/articles/latestnews/248261/fd-technologies-appoints-ashok-reddy-ceo-kx-division[04] 00:08:23 Sharp 1500 Pocket Computer https://en.wikipedia.org/wiki/Sharp_PC-1500 Newton-Raphson Interpolation https://web.mit.edu/10.001/Web/Course_Notes/NLAE/node6.html J#.NET https://en.wikipedia.org/wiki/Visual_J_Sharp [05] 00:10:15 Grady Booch https://en.wikipedia.org/wiki/Grady_Booch Jim Rumbaugh https://en.wikipedia.org/wiki/James_Rumbaugh UML https://en.wikipedia.org/wiki/Unified_Modeling_Language Cobol Programming Language https://en.wikipedia.org/wiki/COBOL Nick Psaris ArrayCast episode https://www.arraycast.com/episodes/episode42-nick-psaris-q[06] 00:14:36 Java programming Language https://en.wikipedia.org/wiki/Java_(programming_language) C# programming language https://en.wikipedia.org/wiki/C_Sharp_(programming_language) J++ programming language https://en.wikipedia.org/wiki/Visual_J%2B%2B LINQ https://en.wikipedia.org/wiki/Language_Integrated_Query SQL programming language https://en.wikipedia.org/wiki/SQL[07] 00:17:13 VisiCalc https://en.wikipedia.org/wiki/VisiCalc q programming language https://aplwiki.com/wiki/Q k programming language https://aplwiki.com/wiki/K[08] 00:19:55 Python programming language https://www.python.org/ ChatGPT https://en.wikipedia.org/wiki/ChatGPT Arthur Whitney https://en.wikipedia.org/wiki/Arthur_Whitney_(computer_scientist)[09] 00:23:19 Kdb+ https://en.wikipedia.org/wiki/Kdb%2B[10] 00:30:01 Asof Join https://code.kx.com/q/ref/aj/[11] 00:36:45 APL programming language https://en.wikipedia.org/wiki/APL_(programming_language)[12] 00:42:50 Clinical trials https://bccancerfoundation.com/news-and-media/blog/what-clinical-trial/[13] 00:44:20 Matlab https://en.wikipedia.org/wiki/MATLAB[14] 00:46:08 Formula One https://www.formula1.com/ Alpine Formula One Team https://www.formula1.com/en/teams/Alpine.html Red Bull Formula One Team https://www.redbullracing.com/int-en KX Red Bull video https://www.youtube.com/watch?v=QxfdFWKo_pQ&t=2s[15] 00:49:40 Fingrid https://www.fingrid.fi/en/[16] 00:53:20 Stent https://www.nhlbi.nih.gov/health/stents[17] 00:55:05 KX Insights Release https://kx.com/news/kx-and-enterpriseweb-enable-unprecedented-performance-and-efficiency-for-network-services-at-the-edge/[18] 00:57:26 PyKX https://kx.com/pykx/[19] 01:01:38 q for personal use https://kx.com/kdb-personal-edition-download/[20] 01:02:25 Visual Studio Code https://code.visualstudio.com/[21] 01:09:00 SnowFlake https://www.snowflake.com/en/ SnowPark https://www.snowflake.com/en/data-cloud/snowpark/[22] 01:16:55 Contact AT ArrayCast DOT com

.NET 7 is a major update to the .NET platform and it comes packed with some awesome new features! In this podcast, we'll take a look at some of the most important new features in .NET 7 and what you need to know about them if you're using .NET 7 in your development work. https://www.youtube.com/watch?v=0BvCzZ9P7UY Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us (https://itunes.apple.com/us/podcast/merge-conflict/id1133064277?mt=2&ls=1) ⭐⭐ Machine transcription available on http://mergeconflict.fm

Produção de alto prestígio, Ilusões Perdidas, dirigido por Xavier Giannoli, consuma o grande feito de ser ao mesmo tempo uma excelente adaptação do romance homônimo de Balzac, em especial a parte 2 do romance, e uma crítica da sociedade parisiense da primeira metade do século XIX surpreendentemente ressonante com os nossos tempos. Este episódio do Sala em especial está imperdível. Além da nossa discussão sobre a ascensão da burguesia e a decadência da nobreza, o desvirtuamento da arte e do jornalismo pelo capitalismo, idealismo vs. cinismo e desilusão e maturidade, confira o episódio até o fim, onde explicamos porque vamos dar uma breve pausa. Sim, queridos ouvintes, infelizmente eu, Diego Nunes, Gustavo Leal e André Vicente vamos nos ausentar por alguns meses. Gustavo e André estão bem ocupados com a recente paternidade e eu estou de mudança de Tóquio para Brasília muito em breve, o que nos impossibilita dedicarmos tempo suficiente para assistir aos filmes, preparar os episódios, ouvir as edições e outras várias tarefas necessárias para garantir o mínimo de qualidade ao programa. Não se aflijam, Felipe e Igor estão preparando um conteúdo especial para vocês, num formato diferente, mais enxuto, mais leve e mais informativo. Espero que gostem! Um grande abraço e muito obrigado pela audiência! Voltaremos em breve. Ficha do Filme: Ilusões Perdidas (Illusions Perdues), 2021. Direção: Xavier Giannoli. Roteiro: Xavier Giannoli e Jacques Fieschi. Elenco: Benjamin Voisin, Xavier Dolan, Vincent Lacoste, Cécile de France, Gérard Depardieu, Jeanne Balibar. 141 min. França. -- Créditos: Ilustração: Felipe Sobreiro (sobreiro.com) Edição e Identidade Visual: Thiago Vergara (thiagommvergara@gmail.com) Música de Introdução: https://www.bensound.com Músicas do filme: Capriccio in B Minor , Op 76 No 2 - Johannes Brahms, Arcadi Volodos Fugue in D Minor OP 72 No 1 Nicht schnell - Robert schumann - YaaraTal Für Elise. WoO 59 - Ludwig van Beethoven, Nelly Kokinos La Traviata Act III - Preludio Scena e Aria - Or Fate Core - Giuseppe Verdi - Teodor Currentzis L'elisir d'amore, Act II Una furtiva lagrima - Vittorio Grigolo - The Italian Tenor Minuet in E Major D 335 - Franz Schubert - Arcadi Volodos Piano Sonata No 14 in C-Sharp minor OP 27 No 2 Moonlight I Adagio sostenuto - Ludwig van Beethoven - Igor Levit Sonata in D Minor K32 - Lucas Debargue Summer 1 - 2012 - Max Richter The Four Seasons Recomposed Sprin I - Epic Orchestra - New Sound of Classical Violin Concerto in D Major, RV 234 L'inquietudine II Largo - Chamber Orchestra of Europe, Daniel Hope Música de Crédito ao Editor: Dança da Solidão - Paulinho da Viola

We are back for College Football Week 6 Picks and Preview betting show. The guys look to continue the hot run after coming off a 7-3-1 Week 5 Picks. Our first best bet for Week 6 College Football is 8th ranked Tennessee who are -2.5 favorites vs 25th ranked LSU. We have a double best bet on this game from both BDiddy and C Sharp. And the guys don't stop there because the next best bet is another double best bet on Maryland facing Purdue in the early game match up Moss Money and the team pulls all the game analytics, all the gambling information, that will help new and casual bettors put in their best bets of the day. Since the start of the College Football podcast the guys have been hitting at 62%. Professional gamblers' win rate is about 57%. So join the guys and make sure you hit that like button! Money Podcast teaches casual and new sport bettors fans about different types of bets from straight, teasers, super teasers, parlays, and round robins. Even though well versed in sports betting, always bet at your own risk as the guys are not professional gamblers. If you're looking to get some free bets and learn about sports betting. MoneyPot Podcast will ensure that you will understanding Sports Betting 101

Jason is in love with the ORRRRANGE on his new Apple Watch Ultra, Andrew is enjoying a cappuccino (but has trouble spelling it) and Martin gets into mirrorless! Coaster Corner 00:00:00 Who doesn't want a Feld Coaster!?

En el episodio 72 del podcast de Entre Dev y Ops hablaremos con Federico Mena Quintero. Blog Entre Dev y Ops - https://www.entredevyops.es Telegram Entre Dev y Ops - https://t.me/entredevyops Twitter Entre Dev y Ops - https://twitter.com/entredevyops LinkedIn Entre Dev y Ops - https://www.linkedin.com/company/entredevyops/ Patreon Entre Dev y Ops - https://www.patreon.com/edyo Amazon Entre Dev y Ops - https://amzn.to/2HrlmRw Enlaces comentados: Episodio 67: Rust con Alberto Ruiz - https://www.entredevyops.es/podcasts/podcast-67.html GNOME - https://www.gnome.org/ SUSE - https://www.suse.com/ Ximian - https://en.wikipedia.org/wiki/Ximian libsvg - https://gitlab.gnome.org/GNOME/librsvg Nautilus - https://apps.gnome.org/en-GB/app/org.gnome.Nautilus/ Midnight Commander - https://midnight-commander.org/ QT - https://www.qt.io/ GTK - https://www.gtk.org/ Gimp - https://www.gimp.org/ GUADEC Mexico - https://foundation.gnome.org/2022/02/21/guadec-2022-in-guadalajara-mexico/ Proyecto GNU - https://www.gnu.org/ Kernel de Linux - https://www.kernel.org/ KDE - https://kde.org/ El libro de los gnomos - https://es.wikipedia.org/wiki/El_libro_secreto_de_los_gnomos Microsoft COM - https://en.wikipedia.org/wiki/Component_Object_Model ILU Xerox - https://en.wikipedia.org/wiki/Inter-Language_Unification CORBA - https://en.wikipedia.org/wiki/Common_Object_Request_Broker_Architecture D-bus - https://www.freedesktop.org/wiki/Software/dbus/ Fundación GNOME - https://foundation.gnome.org/ GNOME Circle - https://circle.gnome.org/ Offtopic: La guerra perdida - https://amzn.to/3NPI2fz Offtopic: Ese Principe que fui - https://amzn.to/3bWLdoj GStreamer - https://gstreamer.freedesktop.org/ Rust - https://www.rust-lang.org/ Vala - https://vala.dev/ Haskell - https://www.haskell.org/ C# - https://en.wikipedia.org/wiki/C_Sharp_(programming_language) F# - https://en.wikipedia.org/wiki/F_Sharp_(programming_language) Mono - https://www.mono-project.com/ .NET - https://dotnet.microsoft.com/ Proyecto Accesibilidad GNOME - https://wiki.gnome.org/Accessibility Sun Microsystems - https://en.wikipedia.org/wiki/Sun_Microsystems Oracle - https://www.oracle.com/ Mate - https://mate-desktop.org/ libjpeg - https://en.wikipedia.org/wiki/Libjpeg GitLab Gnome - http://gitlab.gnome.org/ Mastodon Federico - https://mstdn.mx/@federicomena Twitter Federico - https://twitter.com/federicomena Blog de Federico - https://viruta.org/

It is a random topic week because we don't know what to talk about in-depth, so we chat up iOS 16 Beta, C# partial methods, scoped keyword, and running python inside of C# on an iPhone with IronPython! Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us (https://itunes.apple.com/us/podcast/merge-conflict/id1133064277?mt=2&ls=1) ⭐⭐ Machine transcription available on http://mergeconflict.fm

It is a random topic week because we don't know what to talk about in-depth, so we chat up iOS 16 Beta, C# partial methods, scoped keyword, and running python inside of C# on an iPhone with IronPython! Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us (https://itunes.apple.com/us/podcast/merge-conflict/id1133064277?mt=2&ls=1) ⭐⭐ Machine transcription available on http://mergeconflict.fm

Find out what visual logic is and how you can build smart templates that can control conditional animations, position of objects and a variety of different parameters without having to use scripts. We're going to show you how to use Visual Studio to write a C Sharp or Visual Basic Application that will connect to the dot net interface of XPression to be able to control your graphics. Living Live! with Ross Video www.rossvideo.com/XPression-U

This is a quick intro on how to write a C Sharp application to control your graphics which can make the workflow sometimes easier depending on what you're aiming to do. Living Live! with Ross Video www.rossvideo.com/XPression-U

Frank had his first PR merged into iOS and macOS for .NET! We explore his journey to getting it accepted Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us (https://itunes.apple.com/us/podcast/merge-conflict/id1133064277?mt=2&ls=1) ⭐⭐ Machine transcription available on http://mergeconflict.fm

Frank had his first PR merged into iOS and macOS for .NET! We explore his journey to getting it accepted Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us (https://itunes.apple.com/us/podcast/merge-conflict/id1133064277?mt=2&ls=1) ⭐⭐ Machine transcription available on http://mergeconflict.fm

Stephan Beneking: Nocturne in C Sharp Major, No. 3 by Carlos Márquez

C# 11 is coming in hot with some awesome new previews and we break down our favorite features. Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us (https://itunes.apple.com/us/podcast/merge-conflict/id1133064277?mt=2&ls=1) ⭐⭐ Machine transcription available on http://mergeconflict.fm

C# 11 is coming in hot with some awesome new previews and we break down our favorite features. Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us (https://itunes.apple.com/us/podcast/merge-conflict/id1133064277?mt=2&ls=1) ⭐⭐ Machine transcription available on http://mergeconflict.fm

It's here already…!!!??!!!! That's right, .NET 7 is on its way with awesome new features. Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us (https://itunes.apple.com/us/podcast/merge-conflict/id1133064277?mt=2&ls=1) ⭐⭐ Machine transcription available on http://mergeconflict.fm

From VBS, PowerShell, C Sharp, Process Hollowing to RAT https://isc.sans.edu/forums/diary/From+VBS+PowerShell+C+Sharp+Process+Hollowing+to+RAT/27168/ Cisco Patches Snort Related Vulnerabilities https://tools.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-snort-ethernet-dos-HGXgJH8n VMWare View Planner Update https://www.vmware.com/security/advisories/VMSA-2021-0003.html Google's FLoC Algorithm https://www.eff.org/deeplinks/2021/03/googles-floc-terrible-idea Supermicro Trickbot Patch https://www.supermicro.com/en/support/security/trickbot

Listen to this episode to learn:The importance of cybersecurity in our lives.The main characteristic of cyberattacks.The importance of using a password manager and how to turn it into a habit.How technology can protect us.Why cybersecurity can be understood by anyone, regardless of their area of expertise.A few ideas that stuck with me:Anyone can become a victim of cyberattacks: Our entire life is online nowadays, whether we realize it or not. It's become almost second-nature to us. We're all users of technology to some extent, and this means we're also responsible for protecting everything that we put on our devices. Back in the day, we might have thought that only big companies could be hacked. But now, since we're all connected, we can be victims of random attacks that can erase our entire digital memory, in a second.Cybersecurity impacts our decision-making process: Once we become aware of the risks in the virtual world, we start paying more attention to what we do offline. We become more careful with the data we provide to different organizations - such as hotels - and we take measures to better protect our accounts – by using password managers, two-factor authentication or any other methods.Cybersecurity should be taught in schools: Kids nowadays were basically born with a smartphone in their hands and many of them don't understand the concept of security and protecting their data. It's up to us to teach them the risks and one way we can do that is by introducing the subject into their school curriculums. This can help to raise awareness to a larger public, such as their parents and even grandparents and it can also lead them towards becoming information security specialists themselves. About John Opdenakker: John started his career as a developer for desktop applications, C++, C-Sharp, and web applications. As time went by, and he built and launched increasingly more web applications, one question in particular concerned him: how could he protect all the apps users' data against attackers? To find the answer to this, John began to dig deep into the cybersecurity world, thus becoming an expert in this field.John now tries to raise awareness on this topic by writing and publishing approachable, easy to understand articles on his blog, all on cybersecurity topics. He's also very active on Twitter, where he tries to answer any question the general public might have and engage other Twitter users in constructive conversations about their data protection habits and perceptions.  Key Discussion Points:03:51 - The main reason why most people have a difficult time relating to cybersecurity;08:17 - What attracted John to the information security industry;09:35 - Hack Yourself First – how a workshop that helps you see yourself through the eyes of an attacker changed his perception of how vulnerable he was online;19:26 - What changed in John's offline behavior, once he started learning more about online security;23:08 - The importance of using a simple security measure, such as two-factor authentication;26:33 - How to understand the concept of risk and why risk is important to decision-making regarding security;32:18 - How to handle decision fatigue, as a cybersecurity professional;37:13 – How a penetration test (pentest) can be useful for a fact-based perception and management of risk;40:42 – The reasons we don't perceive online risks as important to our safety as the offline ones are.Connect with John:LinkedInBlogTwitterResources mentioned in the episode:Workshop: Hack Yourself FirstResources not mentioned in this show but that I created to help you improve your online security:this cybersecurity glossary so you can understand what these technical terms are all about this Cybersecurity for Beginners course I created a few years ago with my former team at Heimdal, taken by tens of thousands of people around the worldThe Daily Security Tip: a string of daily, fun emails you can get in your inbox. Get a practical tip each day and a fun GIF to make securing your online stuff anything but boring 

In this episode I am joined by Oren Eini, who is sometimes referred to as Ayende Rahien.  Oren is the creator of RavenDB, a popular NoSQL document database for .NET developers.  I am also joined by my friend and colleague, Matthew Groves, who is a .NET developer. Matthew helps me get all the details from Oren when it comes to RavenDB such as how it operates from a technical perspective, who the target audience is, and what kind of frameworks or SDKs are available. If you'd like to reach Oren, he can be found on Twitter at @ayende.  Matt Groves can also be found on Twitter at @mgroves. If you have any questions regarding this episode, send them to advocates@couchbase.com and they'll be answered as soon as possible.  

On the latest edition of the Politically Speaking podcast, we take things in a slightly different direction by interviewing St. Louis musician C-Sharp about his get-out-the-vote initiative. The St. Louis County native has launched “YouTurn 2016.” In addition to talking with St. Louis Public Radio's Jason Rosenbaum and Willis Ryder Arnold about the importance of voting, C-Sharp is barnstorming across the city to talk about the value of voter participation.