Podcasts about alphacode

The full schedule for Latent Space LIVE! at NeurIPS has been announced, featuring Best of 2024 overview talks for the AI Startup Landscape, Computer Vision, Open Models, Transformers Killers, Synthetic Data, Agents, and Scaling, and speakers from Sarah Guo of Conviction, Roboflow, AI2/Meta, Recursal/Together, HuggingFace, OpenHands and SemiAnalysis. Join us for the IRL event/Livestream! Alessio will also be holding a meetup at AWS Re:Invent in Las Vegas this Wednesday. See our new Events page for dates of AI Engineer Summit, Singapore, and World's Fair in 2025. LAST CALL for questions for our big 2024 recap episode! Submit questions and messages on Speakpipe here for a chance to appear on the show!When we first observed that GPT Wrappers are Good, Actually, we did not even have Bolt on our radar. Since we recorded our Anthropic episode discussing building Agents with the new Claude 3.5 Sonnet, Bolt.new (by Stackblitz) has easily cleared the $8m ARR bar, repeating and accelerating its initial $4m feat.There are very many AI code generators and VS Code forks out there, but Bolt probably broke through initially because of its incredible zero shot low effort app generation:But as we explain in the pod, Bolt also emphasized deploy (Netlify)/ backend (Supabase)/ fullstack capabilities on top of Stackblitz's existing WebContainer full-WASM-powered-developer-environment-in-the-browser tech. Since then, the team has been shipping like mad (with weekly office hours), with bugfixing, full screen, multi-device, long context, diff based edits (using speculative decoding like we covered in Inference, Fast and Slow).All of this has captured the imagination of low/no code builders like Greg Isenberg and many others on YouTube/TikTok/Reddit/X/Linkedin etc:Just as with Fireworks, our relationship with Bolt/Stackblitz goes a bit deeper than normal - swyx advised the launch and got a front row seat to this epic journey, as well as demoed it with Realtime Voice at the recent OpenAI Dev Day. So we are very proud to be the first/closest to tell the full open story of Bolt/Stackblitz!Flow Engineering + Qodo/AlphaCodium UpdateIn year 2 of the pod we have been on a roll getting former guests to return as guest cohosts (Harrison Chase, Aman Sanger, Jon Frankle), and it was a pleasure to catch Itamar Friedman back on the pod, giving us an update on all things Qodo and Testing Agents from our last catchup a year and a half ago:Qodo (they renamed in September) went viral in early January this year with AlphaCodium (paper here, code here) beating DeepMind's AlphaCode with high efficiency:With a simple problem solving code agent:* The first step is to have the model reason about the problem. They describe it using bullet points and focus on the goal, inputs, outputs, rules, constraints, and any other relevant details.* Then, they make the model reason about the public tests and come up with an explanation of why the input leads to that particular output. * The model generates two to three potential solutions in text and ranks them in terms of correctness, simplicity, and robustness. * Then, it generates more diverse tests for the problem, covering cases not part of the original public tests. * Iteratively, pick a solution, generate the code, and run it on a few test cases. * If the tests fail, improve the code and repeat the process until the code passes every test.swyx has previously written similar thoughts on types vs tests for putting bounds on program behavior, but AlphaCodium extends this to AI generated tests and code.More recently, Itamar has also shown that AlphaCodium's techniques also extend well to the o1 models:Making Flow Engineering a useful technique to improve code model performance on every model. This is something we see AI Engineers uniquely well positioned to do compared to ML Engineers/Researchers.Full Video PodcastLike and subscribe!Show Notes* Itamar* Qodo* First episode* Eric* Bolt* StackBlitz* Thinkster* AlphaCodium* WebContainersChapters* 00:00:00 Introductions & Updates* 00:06:01 Generic vs. Specific AI Agents* 00:07:40 Maintaining vs Creating with AI* 00:17:46 Human vs Agent Computer Interfaces* 00:20:15 Why Docker doesn't work for Bolt* 00:24:23 Creating Testing and Code Review Loops* 00:28:07 Bolt's Task Breakdown Flow* 00:31:04 AI in Complex Enterprise Environments* 00:41:43 AlphaCodium* 00:44:39 Strategies for Breaking Down Complex Tasks* 00:45:22 Building in Open Source* 00:50:35 Choosing a product as a founder* 00:59:03 Reflections on Bolt Success* 01:06:07 Building a B2C GTM* 01:18:11 AI Capabilities and Pricing Tiers* 01:20:28 What makes Bolt unique* 01:23:07 Future Growth and Product Development* 01:29:06 Competitive Landscape in AI Engineering* 01:30:01 Advice to Founders and Embracing AI* 01:32:20 Having a baby and completing an Iron ManTranscriptAlessio [00:00:00]: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol.ai.Swyx [00:00:12]: Hey, and today we're still in our sort of makeshift in-between studio, but we're very delighted to have a former returning guest host, Itamar. Welcome back.Itamar [00:00:21]: Great to be here after a year or more. Yeah, a year and a half.Swyx [00:00:24]: You're one of our earliest guests on Agents. Now you're CEO co-founder of Kodo. Right. Which has just been renamed. You also raised a $40 million Series A, and we can get caught up on everything, but we're also delighted to have our new guest, Eric. Welcome.Eric [00:00:42]: Thank you. Excited to be here. Should I say Bolt or StackBlitz?Swyx [00:00:45]: Like, is it like its own company now or?Eric [00:00:47]: Yeah. Bolt's definitely bolt.new. That's the thing that we're probably the most known for, I imagine, at this point.Swyx [00:00:54]: Which is ridiculous to say because you were working at StackBlitz for so long.Eric [00:00:57]: Yeah. I mean, within a week, we were doing like double the amount of traffic. And StackBlitz had been online for seven years, and we were like, what? But anyways, yeah. So we're StackBlitz, the company behind bolt.new. If you've heard of bolt.new, that's our stuff. Yeah.Swyx [00:01:12]: Yeah.Itamar [00:01:13]: Excellent. I see, by the way, that the founder mode, you need to know to capture opportunities. So kudos on doing that, right? You're working on some technology, and then suddenly you can exploit that to a new world. Yeah.Eric [00:01:24]: Totally. And I think, well, not to jump, but 100%, I mean, a couple of months ago, we had the idea for Bolt earlier this year, but we haven't really shared this too much publicly. But we actually had tried to build it with some of those state-of-the-art models back in January, February, you can kind of imagine which, and they just weren't good enough to actually do the code generation where the code was accurate and it was fast and whatever have you without a ton of like rag, but then there was like issues with that. So we put it on the shelf and then we got kind of a sneak peek of some of the new models that have come out in the past couple of months now. And so once we saw that, once we actually saw the code gen from it, we were like, oh my God, like, okay, we can build a product around this. And so that was really the impetus of us building the thing. But with that, it was StackBlitz, the core StackBlitz product the past seven years has been an IDE for developers. So the entire user experience flow we've built up just didn't make sense. And so when we kind of went out to build Bolt, we just thought, you know, if we were inventing our product today, what would the interface look like given what is now possible with the AI code gen? And so there's definitely a lot of conversations we had internally, but you know, just kind of when we logically laid it out, we were like, yeah, I think it makes sense to just greenfield a new thing and let's see what happens. If it works great, then we'll figure it out. If it doesn't work great, then it'll get deleted at some point. So that's kind of how it actually came to be.Swyx [00:02:49]: I'll mention your background a little bit. You were also founder of Thinkster before you started StackBlitz. So both of you are second time founders. Both of you have sort of re-founded your company recently. Yours was more of a rename. I think a slightly different direction as well. And then we can talk about both. Maybe just chronologically, should we get caught up on where Kodo is first and then you know, just like what people should know since the last pod? Sure.Itamar [00:03:12]: The last pod was two months after we launched and we basically had the vision that we talked about. The idea that software development is about specification, test and code, etc. We are more on the testing part as in essence, we think that if you solve testing, you solve software development. The beautiful chart that we'll put up on screen. And testing is a really big field, like there are many dimensions, unit testing, the level of the component, how big it is, how large it is. And then there is like different type of testing, is it regression or smoke or whatever. So back then we only had like one ID extension with unit tests as in focus. One and a half year later, first ID extension supports more type of testing as context aware. We index local, local repos, but also 10,000s of repos for Fortune 500 companies. We have another agent, another tool that is called, the pure agent is the open source and the commercial one is CodoMerge. And then we have another open source called CoverAgent, which is not yet a commercial product coming very soon. It's very impressive. It could be that already people are approving automated pull requests that they don't even aware in really big open sources. So once we have enough of these, we will also launch another agent. So for the first one and a half year, what we did is grew in our offering and mostly on the side of, does this code actually works, testing, code review, et cetera. And we believe that's the critical milestone that needs to be achieved to actually have the AI engineer for enterprise software. And then like for the first year was everything bottom up, getting to 1 million installation. 2024, that was 2023, 2024 was starting to monetize, to feel like how it is to make the first buck. So we did the teams offering, it went well with a thousand of teams, et cetera. And then we started like just a few months ago to do enterprise with everything you need, which is a lot of things that discussed in the last post that was just released by Codelm. So that's how we call it at Codelm. Just opening the brackets, our company name was Codelm AI, and we renamed to Codo and we call our models Codelm. So back to my point, so we started Enterprise Motion and already have multiple Fortune 100 companies. And then with that, we raised a series of $40 million. And what's exciting about it is that enables us to develop more agents. That's our focus. I think it's very different. We're not coming very soon with an ID or something like that.Swyx [00:06:01]: You don't want to fork this code?Itamar [00:06:03]: Maybe we'll fork JetBrains or something just to be different.Swyx [00:06:08]: I noticed that, you know, I think the promise of general purpose agents has kind of died. Like everyone is doing kind of what you're doing. There's Codogen, Codomerge, and then there's a third one. What's the name of it?Itamar [00:06:17]: Yeah. Codocover. Cover. Which is like a commercial version of a cover agent. It's coming soon.Swyx [00:06:23]: Yeah. It's very similar with factory AI, also doing like droids. They all have special purpose doing things, but people don't really want general purpose agents. Right. The last time you were here, we talked about AutoGBT, the biggest thing of 2023. This year, not really relevant anymore. And I think it's mostly just because when you give me a general purpose agent, I don't know what to do with it.Eric [00:06:42]: Yeah.Itamar [00:06:43]: I totally agree with that. We're seeing it for a while and I think it will stay like that despite the computer use, et cetera, that supposedly can just replace us. You can just like prompt it to be, hey, now be a QA or be a QA person or a developer. I still think that there's a few reasons why you see like a dedicated agent. Again, I'm a bit more focused, like my head is more on complex software for big teams and enterprise, et cetera. And even think about permissions and what are the data sources and just the same way you manage permissions for users. Developers, you probably want to have dedicated guardrails and dedicated approvals for agents. I intentionally like touched a point on not many people think about. And of course, then what you can think of, like maybe there's different tools, tool use, et cetera. But just the first point by itself is a good reason why you want to have different agents.Alessio [00:07:40]: Just to compare that with Bot.new, you're almost focused on like the application is very complex and now you need better tools to kind of manage it and build on top of it. On Bot.new, it's almost like I was using it the other day. There's basically like, hey, look, I'm just trying to get started. You know, I'm not very opinionated on like how you're going to implement this. Like this is what I want to do. And you build a beautiful app with it. What people ask as the next step, you know, going back to like the general versus like specific, have you had people say, hey, you know, this is great to start, but then I want a specific Bot.new dot whatever else to do a more vertical integration and kind of like development or what's the, what do people say?Eric [00:08:18]: Yeah. I think, I think you kind of hit the, hit it head on, which is, you know, kind of the way that we've, we've kind of talked about internally is it's like people are using Bolt to go from like 0.0 to 1.0, like that's like kind of the biggest unlock that Bolt has versus most other things out there. I mean, I think that's kind of what's, what's very unique about Bolt. I think the, you know, the working on like existing enterprise applications is, I mean, it's crazy important because, you know, there's a, you look, when you look at the fortune 500, I mean, these code bases, some of these have been around for 20, 30 plus years. And so it's important to be going from, you know, 101.3 to 101.4, et cetera. I think for us, so what's been actually pretty interesting is we see there's kind of two different users for us that are coming in and it's very distinct. It's like people that are developers already. And then there's people that have never really written software and more if they have, it's been very, very minimal. And so in the first camp, what these developers are doing, like to go from zero to one, they're coming to Bolt and then they're ejecting the thing to get up or just downloading it and, you know, opening cursor, like whatever to, to, you know, keep iterating on the thing. And sometimes they'll bring it back to Bolt to like add in a huge piece of functionality or something. Right. But for the people that don't know how to code, they're actually just, they, they live in this thing. And that was one of the weird things when we launched is, you know, within a day of us being online, one of the most popular YouTube videos, and there's been a ton since, which was, you know, there's like, oh, Bolt is the cursor killer. And I originally saw the headlines and I was like, thanks for the views. I mean, I don't know. This doesn't make sense to me. That's not, that's not what we kind of thought.Swyx [00:09:44]: It's how YouTubers talk to each other. Well, everything kills everything else.Eric [00:09:47]: Totally. But what blew my mind was that there was any comparison because it's like cursor is a, is a local IDE product. But when, when we actually kind of dug into it and we, and we have people that are using our product saying this, I'm not using cursor. And I was like, what? And it turns out there are hundreds of thousands of people that we have seen that we're using cursor and we're trying to build apps with that where they're not traditional software does, but we're heavily leaning on the AI. And as you can imagine, it is very complicated, right? To do that with cursor. So when Bolt came out, they're like, wow, this thing's amazing because it kind of inverts the complexity where it's like, you know, it's not an IDE, it's, it's a, it's a chat-based sort of interface that we have. So that's kind of the split, which is rather interesting. We've had like the first startups now launch off of Bolt entirely where this, you know, tomorrow I'm doing a live stream with this guy named Paul, who he's built an entire CRM using this thing and you know, with backend, et cetera. And people have made their first money on the internet period, you know, launching this with Stripe or whatever have you. So that's, that's kind of the two main, the two main categories of folks that we see using Bolt though.Itamar [00:10:51]: I agree that I don't understand the comparison. It doesn't make sense to me. I think like we have like two type of families of tools. One is like we re-imagine the software development. I think Bolt is there and I think like a cursor is more like a evolution of what we already have. It's like taking the IDE and it's, it's amazing and it's okay, let's, let's adapt the IDE to an era where LLMs can do a lot for us. And Bolt is more like, okay, let's rethink everything totally. And I think we see a few tools there, like maybe Vercel, Veo and maybe Repl.it in that area. And then in the area of let's expedite, let's change, let's, let's progress with what we already have. You can see Cursor and Kodo, but we're different between ourselves, Cursor and Kodo, but definitely I think that comparison doesn't make sense.Alessio [00:11:42]: And just to set the context, this is not a Twitter demo. You've made 4 million of revenue in four weeks. So this is, this is actually working, you know, it's not a, what, what do you think that is? Like, there's been so many people demoing coding agents on Twitter and then it doesn't really work. And then you guys were just like, here you go, it's live, go use it, pay us for it. You know, is there anything in the development that was like interesting and maybe how that compares to building your own agents?Eric [00:12:08]: We had no idea, honestly, like we, we, we've been pretty blown away and, and things have just kind of continued to grow faster since then. We're like, oh, today is week six. So I, I kind of came back to the point you just made, right, where it's, you, you kind of outlined, it's like, there's kind of this new market of like kind of rethinking the software development and then there's heavily augmenting existing developers. I think that, you know, both of which are, you know, AI code gen being extremely good, it's allowed existing developers, it's allowing existing developers to camera out software far faster than they could have ever before, right? It's like the ultimate power tool for an existing developer. But this code gen stuff is now so good. And then, and we saw this over the past, you know, from the beginning of the year when we tried to first build, it's actually lowered the barrier to people that, that aren't traditionally software engineers. But the kind of the key thing is if you kind of think about it from, imagine you've never written software before, right? My co-founder and I, he and I grew up down the street from each other in Chicago. We learned how to code when we were 13 together and we've been building stuff ever since. And this is back in like the mid 2000s or whatever, you know, there was nothing for free to learn from online on the internet and how to code. For our 13th birthdays, we asked our parents for, you know, O'Reilly books cause you couldn't get this at the library, right? And so instead of like an Xbox, we got, you know, programming books. But the hardest part for everyone learning to code is getting an environment set up locally, you know? And so when we built StackBlitz, like kind of the key thesis, like seven years ago, the insight we had was that, Hey, it seems like the browser has a lot of new APIs like WebAssembly and service workers, et cetera, where you could actually write an operating system that ran inside the browser that could boot in milliseconds. And you, you know, basically there's this missing capability of the web. Like the web should be able to build apps for the web, right? You should be able to build the web on the web. Every other platform has that, Visual Studio for Windows, Xcode for Mac. The web has no built in primitive for this. And so just like our built in kind of like nerd instinct on this was like, that seems like a huge hole and it's, you know, it will be very valuable or like, you know, very valuable problem to solve. So if you want to set up that environments, you know, this is what we spent the past seven years doing. And the reality is existing developers have running locally. They already know how to set up that environment. So the problem isn't as acute for them. When we put Bolt online, we took that technology called WebContainer and married it with these, you know, state of the art frontier models. And the people that have the most pain with getting stuff set up locally is people that don't code. I think that's been, you know, really the big explosive reason is no one else has been trying to make dev environments work inside of a browser tab, you know, for the past if since ever, other than basically our company, largely because there wasn't an immediate demand or need. So I think we kind of find ourselves at the right place at the right time. And again, for this market of people that don't know how to write software, you would kind of expect that you should be able to do this without downloading something to your computer in the same way that, hey, I don't have to download Photoshop now to make designs because there's Figma. I don't have to download Word because there's, you know, Google Docs. They're kind of looking at this as that sort of thing, right? Which was kind of the, you know, our impetus and kind of vision from the get-go. But you know, the code gen, the AI code gen stuff that's come out has just been, you know, an order of magnitude multiplier on how magic that is, right? So that's kind of my best distillation of like, what is going on here, you know?Alessio [00:15:21]: And you can deploy too, right?Eric [00:15:22]: Yeah.Alessio [00:15:23]: Yeah.Eric [00:15:24]: And so that's, what's really cool is it's, you know, we have deployment built in with Netlify and this is actually, I think, Sean, you actually built this at Netlify when you were there. Yeah. It's one of the most brilliant integrations actually, because, you know, effectively the API that Sean built, maybe you can speak to it, but like as a provider, we can just effectively give files to Netlify without the user even logging in and they have a live website. And if they want to keep, hold onto it, they can click a link and claim it to their Netlify account. But it basically is just this really magic experience because when you come to Bolt, you say, I want a website. Like my mom, 70, 71 years old, made her first website, you know, on the internet two weeks ago, right? It was about her nursing days.Swyx [00:16:03]: Oh, that's fantastic though. It wouldn't have been made.Eric [00:16:06]: A hundred percent. Cause even in, you know, when we've had a lot of people building personal, like deeply personal stuff, like in the first week we launched this, the sales guy from the East Coast, you know, replied to a tweet of mine and he said, thank you so much for building this to your team. His daughter has a medical condition and so for her to travel, she has to like line up donors or something, you know, so ahead of time. And so he actually used Bolt to make a website to do that, to actually go and send it to folks in the region she was going to travel to ahead of time. I was really touched by it, but I also thought like, why, you know, why didn't he use like Wix or Squarespace? Right? I mean, this is, this is a solved problem, quote unquote, right? And then when I thought, I actually use Squarespace for my, for my, uh, the wedding website for my wife and I, like back in 2021, so I'm familiar, you know, it was, it was faster. I know how to code. I was like, this is faster. Right. And I thought back and I was like, there's a whole interface you have to learn how to use. And it's actually not that simple. There's like a million things you can configure in that thing. When you come to Bolt, there's a, there's a text box. You just say, I need a, I need a wedding website. Here's the date. Here's where it is. And here's a photo of me and my wife, put it somewhere relevant. It's actually the simplest way. And that's what my, when my mom came, she said, uh, I'm Pat Simons. I was a nurse in the seventies, you know, and like, here's the things I did and a website came out. So coming back to why is this such a, I think, why are we seeing this sort of growth? It's, this is the simplest interface I think maybe ever created to actually build it, a deploy a website. And then that website, my mom made, she's like, okay, this looks great. And there's, there's one button, you just click it, deploy, and it's live and you can buy a domain name, attach it to it. And you know, it's as simple as it gets, it's getting even simpler with some of the stuff we're working on. But anyways, so that's, it's, it's, uh, it's been really interesting to see some of the usage like that.Swyx [00:17:46]: I can offer my perspective. So I, you know, I probably should have disclosed a little bit that, uh, I'm a, uh, stack list investor.Alessio [00:17:53]: Canceled the episode. I know, I know. Don't play it now. Pause.Eric actually reached out to ShowMeBolt before the launch. And we, you know, we talked a lot about, like, the framing of, of what we're going to talk about how we marketed the thing, but also, like, what we're So that's what Bolt was going to need, like a whole sort of infrastructure.swyx: Netlify, I was a maintainer but I won't take claim for the anonymous upload. That's actually the origin story of Netlify. We can have Matt Billman talk about it, but that was [00:18:00] how Netlify started. You could drag and drop your zip file or folder from your desktop onto a website, it would have a live URL with no sign in.swyx: And so that was the origin story of Netlify. And it just persists to today. And it's just like it's really nice, interesting that both Bolt and CognitionDevIn and a bunch of other sort of agent type startups, they all use Netlify to deploy because of this one feature. They don't really care about the other features.swyx: But, but just because it's easy for computers to use and talk to it, like if you build an interface for computers specifically, that it's easy for them to Navigate, then they will be used in agents. And I think that's a learning that a lot of developer tools companies are having. That's my bolt launch story and now if I say all that stuff.swyx: And I just wanted to come back to, like, the Webcontainers things, right? Like, I think you put a lot of weight on the technical modes. I think you also are just like, very good at product. So you've, you've like, built a better agent than a lot of people, the rest of us, including myself, who have tried to build these things, and we didn't get as far as you did.swyx: Don't shortchange yourself on products. But I think specifically [00:19:00] on, on infra, on like the sandboxing, like this is a thing that people really want. Alessio has Bax E2B, which we'll have on at some point, talking about like the sort of the server full side. But yours is, you know, inside of the browser, serverless.swyx: It doesn't cost you anything to serve one person versus a million people. It doesn't, doesn't cost you anything. I think that's interesting. I think in theory, we should be able to like run tests because you can run the full backend. Like, you can run Git, you can run Node, you can run maybe Python someday.swyx: We talked about this. But ideally, you should be able to have a fully gentic loop, running code, seeing the errors, correcting code, and just kind of self healing, right? Like, I mean, isn't that the dream?Eric: Totally.swyx: Yeah,Eric: totally. At least in bold, we've got, we've got a good amount of that today. I mean, there's a lot more for us to do, but one of the nice things, because like in web container, you know, there's a lot of kind of stuff you go Google like, you know, turn docker container into wasm.Eric: You'll find a lot of stuff out there that will do that. The problem is it's very big, it's slow, and that ruins the experience. And so what we ended up doing is just writing an operating system from [00:20:00] scratch that was just purpose built to, you know, run in a browser tab. And the reason being is, you know, Docker 2 awesome things will give you an image that's like out 60 to 100 megabits, you know, maybe more, you know, and our, our OS, you know, kind of clocks in, I think, I think we're in like a, maybe, maybe a megabyte or less or something like that.Eric: I mean, it's, it's, you know, really, really, you know, stripped down.swyx: This is basically the task involved is I understand that it's. Mapping every single, single Linux call to some kind of web, web assembly implementation,Eric: but more or less, and, and then there's a lot of things actually, like when you're looking at a dev environment, there's a lot of things that you don't need that a traditional OS is gonna have, right?Eric: Like, you know audio drivers or you like, there's just like, there's just tons of things. Oh, yeah. Right. Yeah. That goes . Yeah. You can just kind, you can, you can kind of tos them. Or alternatively, what you can do is you can actually be the nice thing. And this is, this kind of comes back to the origins of browsers, which is, you know, they're, they're at the beginning of the web and, you know, the late nineties, there was two very different kind of visions for the web where Alan Kay vehemently [00:21:00] disagree with the idea that should be document based, which is, you know, Tim Berners Lee, you know, that, and that's kind of what ended up winning, winning was this document based kind of browsing documents on the web thing.Eric: Alan Kay, he's got this like very famous quote where he said, you know, you want web browsers to be mini operating systems. They should download little mini binaries and execute with like a little mini virtualized operating system in there. And what's kind of interesting about the history, not to geek out on this aspect, what's kind of interesting about the history is both of those folks ended up being right.Eric: Documents were actually the pragmatic way that the web worked. Was, you know, became the most ubiquitous platform in the world to the degree now that this is why WebAssembly has been invented is that we're doing, we need to do more low level things in a browser, same thing with WebGPU, et cetera. And so all these APIs, you know, to build an operating system came to the browser.Eric: And that was actually the realization we had in 2017 was, holy heck, like you can actually, you know, service workers, which were designed for allowing your app to work offline. That was the kind of the key one where it was like, wait a second, you can actually now run. Web servers within a [00:22:00] browser, like you can run a server that you open up.Eric: That's wild. Like full Node. js. Full Node. js. Like that capability. Like, I can have a URL that's programmatically controlled. By a web application itself, boom. Like the web can build the web. The primitive is there. Everyone at the time, like we talked to people that like worked on, you know Chrome and V8 and they were like, uhhhh.Eric: You know, like I don't know. But it's one of those things you just kind of have to go do it to find out. So we spent a couple of years, you know, working on it and yeah. And, and, and got to work in back in 2021 is when we kind of put the first like data of web container online. Butswyx: in partnership with Google, right?swyx: Like Google actually had to help you get over the finish line with stuff.Eric: A hundred percent, because well, you know, over the years of when we were doing the R and D on the thing. Kind of the biggest challenge, the two ways that you can kind of test how powerful and capable a platform are, the two types of applications are one, video games, right, because they're just very compute intensive, a lot of calculations that have to happen, right?Eric: The second one are IDEs, because you're talking about actually virtualizing the actual [00:23:00] runtime environment you are in to actually build apps on top of it, which requires sophisticated capabilities, a lot of access to data. You know, a good amount of compute power, right, to effectively, you know, building app in app sort of thing.Eric: So those, those are the stress tests. So if your platform is missing stuff, those are the things where you find out. Those are, those are the people building games and IDEs. They're the ones filing bugs on operating system level stuff. And for us, browser level stuff.Eric [00:23:47]: yeah, what ended up happening is we were just hammering, you know, the Chromium bug tracker, and they're like, who are these guys? Yeah. And, and they were amazing because I mean, just making Chrome DevTools be able to debug, I mean, it's, it's not, it wasn't originally built right for debugging an operating system, right? They've been phenomenal working with us and just kind of really pushing the limits, but that it's a rising tide that's kind of lifted all boats because now there's a lot of different types of applications that you can debug with Chrome Dev Tools that are running a browser that runs more reliably because just the stress testing that, that we and, you know, games that are coming to the web are kind of pushing as well, but.Itamar [00:24:23]: That's awesome. About the testing, I think like most, let's say coding assistant from different kinds will need this loop of testing. And even I would add code review to some, to some extent that you mentioned. How is testing different from code review? Code review could be, for example, PR review, like a code review that is done at the point of when you want to merge branches. But I would say that code review, for example, checks best practices, maintainability, and so on. It's not just like CI, but more than CI. And testing is like a more like checking functionality, et cetera. So it's different. We call, by the way, all of these together code integrity, but that's a different story. Just to go back to the, to the testing and specifically. Yeah. It's, it's, it's since the first slide. Yeah. We're consistent. So if we go back to the testing, I think like, it's not surprising that for us testing is important and for Bolt it's testing important, but I want to shed some light on a different perspective of it. Like let's think about autonomous driving. Those startups that are doing autonomous driving for highway and autonomous driving for the city. And I think like we saw the autonomous of the highway much faster and reaching to a level, I don't know, four or so much faster than those in the city. Now, in both cases, you need testing and quote unquote testing, you know, verifying validation that you're doing the right thing on the road and you're reading and et cetera. But it's probably like so different in the city that it could be like actually different technology. And I claim that we're seeing something similar here. So when you're building the next Wix, and if I was them, I was like looking at you and being a bit scared. That's what you're disrupting, what you just said. Then basically, I would say that, for example, the UX UI is freaking important. And because you're you're more aiming for the end user. In this case, maybe it's an end user that doesn't know how to develop for developers. It's also important. But let alone those that do not know to develop, they need a slick UI UX. And I think like that's one reason, for example, I think Cursor have like really good technology. I don't know the underlying what's under the hood, but at least what they're saying. But I think also their UX UI is great. It's a lot because they did their own ID. While if you're aiming for the city AI, suddenly like there's a lot of testing and code review technology that it's not necessarily like that important. For example, let's talk about integration tests. Probably like a lot of what you're building involved at the moment is isolated applications. Maybe the vision or the end game is maybe like having one solution for everything. It could be that eventually the highway companies will go into the city and the other way around. But at the beginning, there is a difference. And integration tests are a good example. I guess they're a bit less important. And when you think about enterprise software, they're really important. So to recap, like I think like the idea of looping and verifying your test and verifying your code in different ways, testing or code review, et cetera, seems to be important in the highway AI and the city AI, but in different ways and different like critical for the city, even more and more variety. Actually, I was looking to ask you like what kind of loops you guys are doing. For example, when I'm using Bolt and I'm enjoying it a lot, then I do see like sometimes you're trying to catch the errors and fix them. And also, I noticed that you're breaking down tasks into smaller ones and then et cetera, which is already a common notion for a year ago. But it seems like you're doing it really well. So if you're willing to share anything about it.Eric [00:28:07]: Yeah, yeah. I realized I never actually hit the punchline of what I was saying before. I mentioned the point about us kind of writing an operating system from scratch because what ended up being important about that is that to your point, it's actually a very, like compared to like a, you know, if you're like running cursor on anyone's machine, you kind of don't know what you're dealing with, with the OS you're running on. There could be an error happens. It could be like a million different things, right? There could be some config. There could be, it could be God knows what, right? The thing with WebConnect is because we wrote the entire thing from scratch. It's actually a unified image basically. And we can instrument it at any level that we think is going to be useful, which is exactly what we did when we started building Bolt is we instrumented stuff at like the process level, at the runtime level, you know, et cetera, et cetera, et cetera. Stuff that would just be not impossible to do on local, but to do that in a way that works across any operating system, whatever is, I mean, would just be insanely, you know, insanely difficult to do right and reliably. And that's what you saw when you've used Bolt is that when an error actually will occur, whether it's in the build process or the actual web application itself is failing or anything kind of in between, you can actually capture those errors. And today it's a very primitive way of how we've implemented it largely because the product just didn't exist 90 days ago. So we're like, we got some work ahead of us and we got to hire some more a little bit, but basically we present and we say, Hey, this is, here's kind of the things that went wrong. There's a fix it button and then a ignore button, and then you can just hit fix it. And then we take all that telemetry through our agent, you run it through our agent and say, kind of, here's the state of the application. Here's kind of the errors that we got from Node.js or the browser or whatever, and like dah, dah, dah, dah. And it can take a crack at actually solving it. And it's actually pretty darn good at being able to do that. That's kind of been a, you know, closing the loop and having it be a reliable kind of base has seemed to be a pretty big upgrade over doing stuff locally, just because I think that's a pretty key ingredient of it. And yeah, I think breaking things down into smaller tasks, like that's, that's kind of a key part of our agent. I think like Claude did a really good job with artifacts. I think, you know, us and kind of everyone else has, has kind of taken their approach of like actually breaking out certain tasks in a certain order into, you know, kind of a concrete way. And, and so actually the core of Bolt, I know we actually made open source. So you can actually go and check out like the system prompts and et cetera, and you can run it locally and whatever have you. So anyone that's interested in this stuff, I'd highly recommend taking a look at. There's not a lot of like stuff that's like open source in this realm. It's, that was one of the fun things that we've we thought would be cool to do. And people, people seem to like it. I mean, there's a lot of forks and people adding different models and stuff. So it's been cool to see.Swyx [00:30:41]: Yeah. I'm happy to add, I added real-time voice for my opening day demo and it was really fun to hack with. So thank you for doing that. Yeah. Thank you. I'm going to steal your code.Eric [00:30:52]: Because I want that.Swyx [00:30:52]: It's funny because I built on top of the fork of Bolt.new that already has the multi LLM thing. And so you just told me you're going to merge that in. So then you're going to merge two layers of forks down into this thing. So it'll be fun.Eric [00:31:03]: Heck yeah.Alessio [00:31:04]: Just to touch on like the environment, Itamar, you maybe go into the most complicated environments that even the people that work there don't know how to run. How much of an impact does that have on your performance? Like, you know, it's most of the work you're doing actually figuring out environment and like the libraries, because I'm sure they're using outdated version of languages, they're using outdated libraries, they're using forks that have not been on the public internet before. How much of the work that you're doing is like there versus like at the LLM level?Itamar [00:31:32]: One of the reasons I was asking about, you know, what are the steps to break things down, because it really matters. Like, what's the tech stack? How complicated the software is? It's hard to figure it out when you're dealing with the real world, any environment of enterprise as a city, when I'm like, while maybe sometimes like, I think you do enable like in Bolt, like to install stuff, but it's quite a like controlled environment. And that's a good thing to do, because then you narrow down and it's easier to make things work. So definitely, there are two dimensions, I think, actually spaces. One is the fact just like installing our software without yet like doing anything, making it work, just installing it because we work with enterprise and Fortune 500, etc. Many of them want on prem solution.Swyx [00:32:22]: So you have how many deployment options?Itamar [00:32:24]: Basically, we had, we did a metric metrics, say 96 options, because, you know, they're different dimensions. Like, for example, one dimension, we connect to your code management system to your Git. So are you having like GitHub, GitLab? Subversion? Is it like on cloud or deployed on prem? Just an example. Which model agree to use its APIs or ours? Like we have our Is it TestGPT? Yeah, when we started with TestGPT, it was a huge mistake name. It was cool back then, but I don't think it's a good idea to name a model after someone else's model. Anyway, that's my opinion. So we gotSwyx [00:33:02]: I'm interested in these learnings, like things that you change your mind on.Itamar [00:33:06]: Eventually, when you're building a company, you're building a brand and you want to create your own brand. By the way, when I thought about Bolt.new, I also thought about if it's not a problem, because when I think about Bolt, I do think about like a couple of companies that are already called this way.Swyx [00:33:19]: Curse companies. You could call it Codium just to...Itamar [00:33:24]: Okay, thank you. Touche. Touche.Eric [00:33:27]: Yeah, you got to imagine the board meeting before we launched Bolt, one of our investors, you can imagine they're like, are you sure? Because from the investment side, it's kind of a famous, very notorious Bolt. And they're like, are you sure you want to go with that name? Oh, yeah. Yeah, absolutely.Itamar [00:33:43]: At this point, we have actually four models. There is a model for autocomplete. There's a model for the chat. There is a model dedicated for more for code review. And there is a model that is for code embedding. Actually, you might notice that there isn't a good code embedding model out there. Can you name one? Like dedicated for code?Swyx [00:34:04]: There's code indexing, and then you can do sort of like the hide for code. And then you can embed the descriptions of the code.Itamar [00:34:12]: Yeah, but you do see a lot of type of models that are dedicated for embedding and for different spaces, different fields, etc. And I'm not aware. And I know that if you go to the bedrock, try to find like there's a few code embedding models, but none of them are specialized for code.Swyx [00:34:31]: Is there a benchmark that you would tell us to pay attention to?Itamar [00:34:34]: Yeah, so it's coming. Wait for that. Anyway, we have our models. And just to go back to the 96 option of deployment. So I'm closing the brackets for us. So one is like dimensional, like what Git deployment you have, like what models do you agree to use? Dotter could be like if it's air-gapped completely, or you want VPC, and then you have Azure, GCP, and AWS, which is different. Do you use Kubernetes or do not? Because we want to exploit that. There are companies that do not do that, etc. I guess you know what I mean. So that's one thing. And considering that we are dealing with one of all four enterprises, we needed to deal with that. So you asked me about how complicated it is to solve that complex code. I said, it's just a deployment part. And then now to the software, we see a lot of different challenges. For example, some companies, they did actually a good job to build a lot of microservices. Let's not get to if it's good or not, but let's first assume that it is a good thing. A lot of microservices, each one of them has their own repo. And now you have tens of thousands of repos. And you as a developer want to develop something. And I remember me coming to a corporate for the first time. I don't know where to look at, like where to find things. So just doing a good indexing for that is like a challenge. And moreover, the regular indexing, the one that you can find, we wrote a few blogs on that. By the way, we also have some open source, different than yours, but actually three and growing. Then it doesn't work. You need to let the tech leads and the companies influence your indexing. For example, Mark with different repos with different colors. This is a high quality repo. This is a lower quality repo. This is a repo that we want to deprecate. This is a repo we want to grow, etc. And let that be part of your indexing. And only then things actually work for enterprise and they don't get to a fatigue of, oh, this is awesome. Oh, but I'm starting, it's annoying me. I think Copilot is an amazing tool, but I'm quoting others, meaning GitHub Copilot, that they see not so good retention of GitHub Copilot and enterprise. Ooh, spicy. Yeah. I saw snapshots of people and we have customers that are Copilot users as well. And also I saw research, some of them is public by the way, between 38 to 50% retention for users using Copilot and enterprise. So it's not so good. By the way, I don't think it's that bad, but it's not so good. So I think that's a reason because, yeah, it helps you auto-complete, but then, and especially if you're working on your repo alone, but if it's need that context of remote repos that you're code-based, that's hard. So to make things work, there's a lot of work on that, like giving the controllability for the tech leads, for the developer platform or developer experience department in the organization to influence how things are working. A short example, because if you have like really old legacy code, probably some of it is not so good anymore. If you just fine tune on these code base, then there is a bias to repeat those mistakes or old practices, etc. So you need, for example, as I mentioned, to influence that. For example, in Coda, you can have a markdown of best practices by the tech leads and Coda will include that and relate to that and will not offer suggestions that are not according to the best practices, just as an example. So that's just a short list of things that you need to do in order to deal with, like you mentioned, the 100.1 to 100.2 version of software. I just want to say what you're doing is extremelyEric [00:38:32]: impressive because it's very difficult. I mean, the business of Stackplus, kind of before bulk came online, we sold a version of our IDE that went on-prem. So I understand what you're saying about the difficulty of getting stuff just working on-prem. Holy heck. I mean, that is extremely hard. I guess the question I have for you is, I mean, we were just doing that with kind of Kubernetes-based stuff, but the spread of Fortune 500 companies that you're working with, how are they doing the inference for this? Are you kind of plugging into Azure's OpenAI stuff and AWS's Bedrock, you know, Cloud stuff? Or are they just like running stuff on GPUs? Like, what is that? How are these folks approaching that? Because, man, what we saw on the enterprise side, I mean, I got to imagine that that's a huge challenge. Everything you said and more, like,Itamar [00:39:15]: for example, like someone could be, and I don't think any of these is bad. Like, they made their decision. Like, for example, some people, they're, I want only AWS and VPC on AWS, no matter what. And then they, some of them, like there is a subset, I will say, I'm willing to take models only for from Bedrock and not ours. And we have a problem because there is no good code embedding model on Bedrock. And that's part of what we're doing now with AWS to solve that. We solve it in a different way. But if you are willing to run on AWS VPC, but run your run models on GPUs or inferentia, like the new version of the more coming out, then our models can run on that. But everything you said is right. Like, we see like on-prem deployment where they have their own GPUs. We see Azure where you're using OpenAI Azure. We see cases where you're running on GCP and they want OpenAI. Like this cross, like a case, although there is Gemini or even Sonnet, I think is available on GCP, just an example. So all the options, that's part of the challenge. I admit that we thought about it, but it was even more complicated. And it took us a few months to actually, that metrics that I mentioned, to start clicking each one of the blocks there. A few months is impressive. I mean,Eric [00:40:35]: honestly, just that's okay. Every one of these enterprises is, their networking is different. Just everything's different. Every single one is different. I see you understand. Yeah. So that just cannot be understated. That it is, that's extremely impressive. Hats off.Itamar [00:40:50]: It could be, by the way, like, for example, oh, we're only AWS, but our GitHub enterprise is on-prem. Oh, we forgot. So we need like a private link or whatever, like every time like that. It's not, and you do need to think about it if you want to work with an enterprise. And it's important. Like I understand like their, I respect their point of view.Swyx [00:41:10]: And this primarily impacts your architecture, your tech choices. Like you have to, you can't choose some vendors because...Itamar [00:41:15]: Yeah, definitely. To be frank, it makes us hard for a startup because it means that we want, we want everyone to enjoy all the variety of models. By the way, it was hard for us with our technology. I want to open a bracket, like a window. I guess you're familiar with our Alpha Codium, which is an open source.Eric [00:41:33]: We got to go over that. Yeah. So I'll do that quickly.Itamar [00:41:36]: Yeah. A pin in that. Yeah. Actually, we didn't have it in the last episode. So, so, okay.Swyx [00:41:41]: Okay. We'll come back to that later, but let's talk about...Itamar [00:41:43]: Yeah. So, so just like shortly, and then we can double click on Alpha Codium. But Alpha Codium is a open source tool. You can go and try it and lets you compete on CodeForce. This is a website and a competition and actually reach a master level level, like 95% with a click of a button. You don't need to do anything. And part of what we did there is taking a problem and breaking it to different, like smaller blocks. And then the models are doing a much better job. Like we all know it by now that taking small tasks and solving them, by the way, even O1, which is supposed to be able to do system two thinking like Greg from OpenAI like hinted, is doing better on these kinds of problems. But still, it's very useful to break it down for O1, despite O1 being able to think by itself. And that's what we presented like just a month ago, OpenAI released that now they are doing 93 percentile with O1 IOI left and International Olympiad of Formation. Sorry, I forgot. Exactly. I told you I forgot. And we took their O1 preview with Alpha Codium and did better. Like it just shows like, and there is a big difference between the preview and the IOI. It shows like that these models are not still system two thinkers, and there is a big difference. So maybe they're not complete system two. Yeah, they need some guidance. I call them system 1.5. We can, we can have it. I thought about it. Like, you know, I care about this philosophy stuff. And I think like we didn't see it even close to a system two thinking. I can elaborate later. But closing the brackets, like we take Alpha Codium and as our principle of thinking, we take tasks and break them down to smaller tasks. And then we want to exploit the best model to solve them. So I want to enable anyone to enjoy O1 and SONET and Gemini 1.5, etc. But at the same time, I need to develop my own models as well, because some of the Fortune 500 want to have all air gapped or whatever. So that's a challenge. Now you need to support so many models. And to some extent, I would say that the flow engineering, the breaking down to two different blocks is a necessity for us. Why? Because when you take a big block, a big problem, you need a very different prompt for each one of the models to actually work. But when you take a big problem and break it into small tasks, we can talk how we do that, then the prompt matters less. What I want to say, like all this, like as a startup trying to do different deployment, getting all the juice that you can get from models, etc. is a big problem. And one need to think about it. And one of our mitigation is that process of taking tasks and breaking them down. That's why I'm really interested to know how you guys are doing it. And part of what we do is also open source. So you can see.Swyx [00:44:39]: There's a lot in there. But yeah, flow over prompt. I do believe that that does make sense. I feel like there's a lot that both of you can sort of exchange notes on breaking down problems. And I just want you guys to just go for it. This is fun to watch.Eric [00:44:55]: Yeah. I mean, what's super interesting is the context you're working in is, because for us too with Bolt, we've started thinking because our kind of existing business line was going behind the firewall, right? We were like, how do we do this? Adding the inference aspect on, we're like, okay, how does... Because I mean, there's not a lot of prior art, right? I mean, this is all new. This is all new. So I definitely am going to have a lot of questions for you.Itamar [00:45:17]: I'm here. We're very open, by the way. We have a paper on a blog or like whatever.Swyx [00:45:22]: The Alphacodeum, GitHub, and we'll put all this in the show notes.Itamar [00:45:25]: Yeah. And even the new results of O1, we published it.Eric [00:45:29]: I love that. And I also just, I think spiritually, I like your approach of being transparent. Because I think there's a lot of hype-ium around AI stuff. And a lot of it is, it's just like, you have these companies that are just kind of keep their stuff closed source and then just max hype it, but then it's kind of nothing. And I think it kind of gives a bad rep to the incredible stuff that's actually happening here. And so I think it's stuff like what you're doing where, I mean, true merit and you're cracking open actual code for others to learn from and use. That strikes me as the right approach. And it's great to hear that you're making such incredible progress.Itamar [00:46:02]: I have something to share about the open source. Most of our tools are, we have an open source version and then a premium pro version. But it's not an easy decision to do that. I actually wanted to ask you about your strategy, but I think in your case, there is, in my opinion, relatively a good strategy where a lot of parts of open source, but then you have the deployment and the environment, which is not right if I get it correctly. And then there's a clear, almost hugging face model. Yeah, you can do that, but why should you try to deploy it yourself, deploy it with us? But in our case, and I'm not sure you're not going to hit also some competitors, and I guess you are. I wanted to ask you, for example, on some of them. In our case, one day we looked on one of our competitors that is doing code review. We're a platform. We have the code review, the testing, et cetera, spread over the ID to get. And in each agent, we have a few startups or a big incumbents that are doing only that. So we noticed one of our competitors having not only a very similar UI of our open source, but actually even our typo. And you sit there and you're kind of like, yeah, we're not that good. We don't use enough Grammarly or whatever. And we had a couple of these and we saw it there. And then it's a challenge. And I want to ask you, Bald is doing so well, and then you open source it. So I think I know what my answer was. I gave it before, but still interestingEric [00:47:29]: to hear what you think. GeoHot said back, I don't know who he was up to at this exact moment, but I think on comma AI, all that stuff's open source. And someone had asked him, why is this open source? And he's like, if you're not actually confident that you can go and crush it and build the best thing, then yeah, you should probably keep your stuff closed source. He said something akin to that. I'm probably kind of butchering it, but I thought it was kind of a really good point. And that's not to say that you should just open source everything, because for obvious reasons, there's kind of strategic things you have to kind of take in mind. But I actually think a pretty liberal approach, as liberal as you kind of can be, it can really make a lot of sense. Because that is so validating that one of your competitors is taking your stuff and they're like, yeah, let's just kind of tweak the styles. I mean, clearly, right? I think it's kind of healthy because it keeps, I'm sure back at HQ that day when you saw that, you're like, oh, all right, well, we have to grind even harder to make sure we stay ahead. And so I think it's actually a very useful, motivating thing for the teams. Because you might feel this period of comfort. I think a lot of companies will have this period of comfort where they're not feeling the competition and one day they get disrupted. So kind of putting stuff out there and letting people push it forces you to face reality soon, right? And actually feel that incrementally so you can kind of adjust course. And that's for us, the open source version of Bolt has had a lot of features people have been begging us for, like persisting chat messages and checkpoints and stuff. Within the first week, that stuff was landed in the open source versions. And they're like, why can't you ship this? It's in the open, so people have forked it. And we're like, we're trying to keep our servers and GPUs online. But it's been great because the folks in the community did a great job, kept us on our toes. And we've got to know most of these folks too at this point that have been building these things. And so it actually was very instructive. Like, okay, well, if we're going to go kind of land this, there's some UX patterns we can kind of look at and the code is open source to this stuff. What's great about these, what's not. So anyways, NetNet, I think it's awesome. I think from a competitive point of view for us, I think in particular, what's interesting is the core technology of WebContainer going. And I think that right now, there's really nothing that's kind of on par with that. And we also, we have a business of, because WebContainer runs in your browser, but to make it work, you have to install stuff from NPM. You have to make cores bypass requests, like connected databases, which all require server-side proxying or acceleration. And so we actually sell WebContainer as a service. One of the core reasons we open-sourced kind of the core components of Bolt when we launched was that we think that there's going to be a lot more of these AI, in-your-browser AI co-gen experiences, kind of like what Anthropic did with Artifacts and Clod. By the way, Artifacts uses WebContainers. Not yet. No, yeah. Should I strike that? I think that they've got their own thing at the moment, but there's been a lot of interest in WebContainers from folks doing things in that sort of realm and in the AI labs and startups and everything in between. So I think there'll be, I imagine, over the coming months, there'll be lots of things being announced to folks kind of adopting it. But yeah, I think effectively...Swyx [00:50:35]: Okay, I'll say this. If you're a large model lab and you want to build sandbox environments inside of your chat app, you should call Eric.Itamar [00:50:43]: But wait, wait, wait, wait, wait, wait. I have a question about that. I think OpenAI, they felt that people are not using their model as they would want to. So they built ChatGPT. But I would say that ChatGPT now defines OpenAI. I know they're doing a lot of business from their APIs, but still, is this how you think? Isn't Bolt.new your business now? Why don't you focus on that instead of the...Swyx [00:51:16]: What's your advice as a founder?Eric [00:51:18]: You're right. And so going into it, we, candidly, we were like, Bolt.new, this thing is super cool. We think people are stoked. We think people will be stoked. But we were like, maybe that's allowed. Best case scenario, after month one, we'd be mind blown if we added a couple hundred K of error or something. And we were like, but we think there's probably going to be an immediate huge business. Because there was some early poll on folks wanting to put WebContainer into their product offerings, kind of similar to what Bolt is doing or whatever. We were actually prepared for the inverse outcome here. But I mean, well, I guess we've seen poll on both. But I mean, what's happened with Bolt, and you're right, it's actually the same strategy as like OpenAI or Anthropic, where we have our ChatGPT to OpenAI's APIs is Bolt to WebContainer. And so we've kind of taken that same approach. And we're seeing, I guess, some of the similar results, except right now, the revenue side is extremely lopsided to Bolt.Itamar [00:52:16]: I think if you ask me what's my advice, I think you have three options. One is to focus on Bolt. The other is to focus on the WebContainer. The third is to raise one billion dollars and do them both. I'm serious. I think otherwise, you need to choose. And if you raise enough money, and I think it's big bucks, because you're going to be chased by competitors. And I think it will be challenging to do both. And maybe you can. I don't know. We do see these numbers right now, raising above $100 million, even without havingEric [00:52:49]: a product. You can see these. It's excellent advice. And I think what's been amazing, but also kind of challenging is we're trying to forecast, okay, well, where are these things going? I mean, in the initial weeks, I think us and all the investors in the company that we're sharing this with, it was like, this is cool. Okay, we added 500k. Wow, that's crazy. Wow, we're at a million now. Most things, you have this kind of the tech crunch launch of initiation and then the thing of sorrow. And if there's going to be a downtrend, it's just not coming yet. Now that we're kind of looking ahead, we're six weeks in. So now we're getting enough confidence in our convictions to go, okay, this se

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Demis Hassabis - Google DeepMind: The Podcast, published by Zach Stein-Perlman on August 16, 2024 on LessWrong. The YouTube "chapters" are mixed up, e.g. the question about regulation comes 5 minutes after the regulation chapter ends. Ignore them. Noteworthy parts: 8:40: Near-term AI is hyped too much (think current startups, VCs, exaggerated claims about what AI can do, crazy ideas that aren't ready) but AGI is under-hyped and under-appreciated. 16:45: "Gemini is a project that has only existed for a year . . . our trajectory is very good; when we talk next time we should hopefully be right at the forefront." 17:20-18:50: Current AI doesn't work as a digital assistant. The next era/generation is agents. DeepMind is well-positioned to work on agents: "combining AlphaGo with Gemini." 24:00: Staged deployment is nice: red-teaming then closed beta then public deployment. 28:37 Openness (at Google: e.g. publishing transformers, AlphaCode, AlphaFold) is almost always a universal good. But dual-use technology - including AGI - is an exception. With dual-use technology, you want good scientists to still use the technology and advance as quickly as possible, but also restrict access for bad actors. Openness is fine today but in 2-4 years or when systems are more agentic it'll be dangerous. Maybe labs should only open-source models that are lagging a year behind the frontier (and DeepMind will probably take this approach, and indeed is currently doing ~this by releasing Gemma weights). 31:20 "The problem with open source is if something goes wrong you can't recall it. With a proprietary model if your bad actor starts using it in a bad way you can close the tap off . . . but once you open-source something there's no pulling it back. It's a one-way door, so you should be very sure when you do that." 31:42: Can an AGI be contained? We don't know how to do that [this suggests a misalignment/escape threat model but it's not explicit]. Sandboxing and normal security is good for intermediate systems but won't be good enough to contain an AGI smarter than us. We'll have to design protocols for AGI in the future: "when that time comes we'll have better ideas for how to contain that, potentially also using AI systems and tools to monitor the next versions of the AI system." 33:00: Regulation? It's good that people in government are starting to understand AI and AISIs are being set up before the stakes get really high. International cooperation on safety and deployment norms will be needed since AI is digital and if e.g. China deploys an AI it won't be contained to China. Also: Because the technology is changing so fast, we've got to be very nimble and light-footed with regulation so that it's easy to adapt it to where the latest technology's going. If you'd regulated AI five years ago, you'd have regulated something completely different to what we see today, which is generative AI. And it might be different again in five years; it might be these agent-based systems that [] carry the highest risks. So right now I would [] beef up existing regulations in domains that already have them - health, transport, and so on - I think you can update them for AI just like they were updated for mobile and internet. That's probably the first thing I'd do, while . . . making sure you understand and test the frontier systems. And then as things become [clearer] start regulating around that, maybe in a couple years time would make sense. One of the things we're missing is [benchmarks and tests for dangerous capabilities]. My #1 emerging dangerous capability to test for is deception because if the AI can be deceptive then you can't trust other tests [deceptive alignment threat model but not explicit]. Also agency and self-replication. 37:10: We don't know how to design a system that could come up with th...

Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Demis Hassabis - Google DeepMind: The Podcast, published by Zach Stein-Perlman on August 16, 2024 on LessWrong. The YouTube "chapters" are mixed up, e.g. the question about regulation comes 5 minutes after the regulation chapter ends. Ignore them. Noteworthy parts: 8:40: Near-term AI is hyped too much (think current startups, VCs, exaggerated claims about what AI can do, crazy ideas that aren't ready) but AGI is under-hyped and under-appreciated. 16:45: "Gemini is a project that has only existed for a year . . . our trajectory is very good; when we talk next time we should hopefully be right at the forefront." 17:20-18:50: Current AI doesn't work as a digital assistant. The next era/generation is agents. DeepMind is well-positioned to work on agents: "combining AlphaGo with Gemini." 24:00: Staged deployment is nice: red-teaming then closed beta then public deployment. 28:37 Openness (at Google: e.g. publishing transformers, AlphaCode, AlphaFold) is almost always a universal good. But dual-use technology - including AGI - is an exception. With dual-use technology, you want good scientists to still use the technology and advance as quickly as possible, but also restrict access for bad actors. Openness is fine today but in 2-4 years or when systems are more agentic it'll be dangerous. Maybe labs should only open-source models that are lagging a year behind the frontier (and DeepMind will probably take this approach, and indeed is currently doing ~this by releasing Gemma weights). 31:20 "The problem with open source is if something goes wrong you can't recall it. With a proprietary model if your bad actor starts using it in a bad way you can close the tap off . . . but once you open-source something there's no pulling it back. It's a one-way door, so you should be very sure when you do that." 31:42: Can an AGI be contained? We don't know how to do that [this suggests a misalignment/escape threat model but it's not explicit]. Sandboxing and normal security is good for intermediate systems but won't be good enough to contain an AGI smarter than us. We'll have to design protocols for AGI in the future: "when that time comes we'll have better ideas for how to contain that, potentially also using AI systems and tools to monitor the next versions of the AI system." 33:00: Regulation? It's good that people in government are starting to understand AI and AISIs are being set up before the stakes get really high. International cooperation on safety and deployment norms will be needed since AI is digital and if e.g. China deploys an AI it won't be contained to China. Also: Because the technology is changing so fast, we've got to be very nimble and light-footed with regulation so that it's easy to adapt it to where the latest technology's going. If you'd regulated AI five years ago, you'd have regulated something completely different to what we see today, which is generative AI. And it might be different again in five years; it might be these agent-based systems that [] carry the highest risks. So right now I would [] beef up existing regulations in domains that already have them - health, transport, and so on - I think you can update them for AI just like they were updated for mobile and internet. That's probably the first thing I'd do, while . . . making sure you understand and test the frontier systems. And then as things become [clearer] start regulating around that, maybe in a couple years time would make sense. One of the things we're missing is [benchmarks and tests for dangerous capabilities]. My #1 emerging dangerous capability to test for is deception because if the AI can be deceptive then you can't trust other tests [deceptive alignment threat model but not explicit]. Also agency and self-replication. 37:10: We don't know how to design a system that could come up with th...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Getting 50% (SoTA) on ARC-AGI with GPT-4o, published by ryan greenblatt on June 17, 2024 on LessWrong. I recently got to 50%[1] accuracy on the public test set for ARC-AGI by having GPT-4o generate a huge number of Python implementations of the transformation rule (around 8,000 per problem) and then selecting among these implementations based on correctness of the Python programs on the examples (if this is confusing, go here)[2]. I use a variety of additional approaches and tweaks which overall substantially improve the performance of my method relative to just sampling 8,000 programs. [This post is on a pretty different topic than the usual posts I make about AI safety.] The additional approaches and tweaks are: I use few-shot prompts which perform meticulous step-by-step reasoning. I have GPT-4o try to revise some of the implementations after seeing what they actually output on the provided examples. I do some feature engineering, providing the model with considerably better grid representations than the naive approach of just providing images. (See below for details on what a "grid" in ARC-AGI is.) I used specialized few-shot prompts for the two main buckets of ARC-AGI problems (cases where the grid size changes vs doesn't). The prior state of the art on this dataset was 34% accuracy, so this is a significant improvement.[3] On a held-out subset of the train set, where humans get 85% accuracy, my solution gets 72% accuracy.[4] (The train set is significantly easier than the test set as noted here.) Additional increases of runtime compute would further improve performance (and there are clear scaling laws), but this is left as an exercise to the reader. In this post: I describe my method; I analyze what limits its performance and make predictions about what is needed to reach human performance; I comment on what it means for claims that François Chollet makes about LLMs. Given that current LLMs can perform decently well on ARC-AGI, do claims like "LLMs like Gemini or ChatGPT [don't work] because they're basically frozen at inference time. They're not actually learning anything." make sense? (This quote is from here.) Thanks to Fabien Roger and Buck Shlegeris for a bit of help with this project and with writing this post. What is ARC-AGI? ARC-AGI is a dataset built to evaluate the general reasoning abilities of AIs. It consists of visual problems like the below, where there are input-output examples which are grids of colored cells. The task is to guess the transformation from input to output and then fill out the missing grid. Here is an example from the tutorial: This one is easy, and it's easy to get GPT-4o to solve it. But the tasks from the public test set are much harder; they're often non-trivial for (typical) humans. There is a reported MTurk human baseline for the train distribution of 85%, but no human baseline for the public test set which is known to be significantly more difficult. Here are representative problems from the test set[5], and whether my GPT-4o-based solution gets them correct or not. Problem 1: Problem 2: Problem 3: My method The main idea behind my solution is very simple: get GPT-4o to generate around 8,000 python programs which attempt to implement the transformation, select a program which is right on all the examples (usually there are 3 examples), and then submit the output this function produces when applied to the additional test input(s). I show GPT-4o the problem as images and in various ascii representations. My approach is similar in spirit to the approach applied in AlphaCode in which a model generates millions of completions attempting to solve a programming problem and then aggregates over them to determine what to submit. Actually getting to 50% with this main idea took me about 6 days of work. This work includes construct...

Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Getting 50% (SoTA) on ARC-AGI with GPT-4o, published by ryan greenblatt on June 17, 2024 on LessWrong. I recently got to 50%[1] accuracy on the public test set for ARC-AGI by having GPT-4o generate a huge number of Python implementations of the transformation rule (around 8,000 per problem) and then selecting among these implementations based on correctness of the Python programs on the examples (if this is confusing, go here)[2]. I use a variety of additional approaches and tweaks which overall substantially improve the performance of my method relative to just sampling 8,000 programs. [This post is on a pretty different topic than the usual posts I make about AI safety.] The additional approaches and tweaks are: I use few-shot prompts which perform meticulous step-by-step reasoning. I have GPT-4o try to revise some of the implementations after seeing what they actually output on the provided examples. I do some feature engineering, providing the model with considerably better grid representations than the naive approach of just providing images. (See below for details on what a "grid" in ARC-AGI is.) I used specialized few-shot prompts for the two main buckets of ARC-AGI problems (cases where the grid size changes vs doesn't). The prior state of the art on this dataset was 34% accuracy, so this is a significant improvement.[3] On a held-out subset of the train set, where humans get 85% accuracy, my solution gets 72% accuracy.[4] (The train set is significantly easier than the test set as noted here.) Additional increases of runtime compute would further improve performance (and there are clear scaling laws), but this is left as an exercise to the reader. In this post: I describe my method; I analyze what limits its performance and make predictions about what is needed to reach human performance; I comment on what it means for claims that François Chollet makes about LLMs. Given that current LLMs can perform decently well on ARC-AGI, do claims like "LLMs like Gemini or ChatGPT [don't work] because they're basically frozen at inference time. They're not actually learning anything." make sense? (This quote is from here.) Thanks to Fabien Roger and Buck Shlegeris for a bit of help with this project and with writing this post. What is ARC-AGI? ARC-AGI is a dataset built to evaluate the general reasoning abilities of AIs. It consists of visual problems like the below, where there are input-output examples which are grids of colored cells. The task is to guess the transformation from input to output and then fill out the missing grid. Here is an example from the tutorial: This one is easy, and it's easy to get GPT-4o to solve it. But the tasks from the public test set are much harder; they're often non-trivial for (typical) humans. There is a reported MTurk human baseline for the train distribution of 85%, but no human baseline for the public test set which is known to be significantly more difficult. Here are representative problems from the test set[5], and whether my GPT-4o-based solution gets them correct or not. Problem 1: Problem 2: Problem 3: My method The main idea behind my solution is very simple: get GPT-4o to generate around 8,000 python programs which attempt to implement the transformation, select a program which is right on all the examples (usually there are 3 examples), and then submit the output this function produces when applied to the additional test input(s). I show GPT-4o the problem as images and in various ascii representations. My approach is similar in spirit to the approach applied in AlphaCode in which a model generates millions of completions attempting to solve a programming problem and then aggregates over them to determine what to submit. Actually getting to 50% with this main idea took me about 6 days of work. This work includes construct...

This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.   NetSuite is offering a one-of-a-kind flexible financing program. Head to  https://netsuite.com/EYEONAI to know more.  In this episode of the Eye on AI podcast, join host Craig Smith as he sits down with Itamar Friedman, co-founder and CEO of CodiumAI, a pioneering company in the realm of intelligent coding systems.   Itamar shares the ambitious vision of CodiumAI, where developers can aim for zero bugs and issues in their code. Dive into the innovative solutions CodiumAI offers, including Codiumate and PR Agent, tools designed to assist developers in planning, writing, analyzing, and reviewing code with high integrity.    Explore the concept of flow engineering and how CodiumAI's research project, AlphaCodium, outperforms DeepMind's AlphaCode by using fewer LLM calls and no fine-tuning.    Itamar delves into the future of coding, where AI not only generates code but ensures its quality through robust verification systems.Itamar offers valuable advice for both developers and enterprises on navigating the evolving landscape of AI in software development.   Tune in to gain insights into how CodiumAI is leading the way in creating a future where coding is more efficient, reliable, and free from bugs.   Don't forget to like, subscribe, and hit the notification bell for more on groundbreaking AI technologies. Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI  

Our 153rd episode with a summary and discussion of last week's big AI news! Check out our sponsor, the SuperDataScience podcast. You can listen to SDS across all major podcasting platforms (e.g., Spotify, Apple Podcasts, Google Podcasts) plus there's a video version on YouTube. Read out our text newsletter and comment on the podcast at https://lastweekin.ai/ Email us your questions and feedback at contact@lastweekin.ai and/or hello@gladstone.ai Timestamps + links: (00:00:00)  Intro / Banter Synthetic Media & Art (00:03:15) Trolls have flooded X with graphic Taylor Swift AI fakes (00:08:30) YouTube Deletes 1,000 Videos of Celebrity AI Scam Ads (00:10:20) Iceland Has Its Own AI George Carlin Moment, Considers Law Against Deepfaking the Dead (00:12:20) Guns N' Roses share AI-generated video for ‘The General' Tools & Apps (00:13:30) Microsoft Makes Swift Changes to AI Tool (00:16:38) OpenAI drops prices and fixes ‘lazy' GPT-4 that refused to work (00:20:40) ChatGPT's new "@GPT" feature paves the way for OpenAI's vision of a universal assistant (00:23:47)  ChatGPT finally has competition — Google Bard with Gemini just matched it with a huge upgrade (00:26:37) Browser alternatives Brave, Arc, add new AI integrations (00:28:37) Baidu's Ernie AI chatbot to power Samsung's new Galaxy S24 smartphones Applications & Business (00:30:40) AI companies lose $190 billion in market cap after Alphabet and Microsoft report (00:34:25) Cruise wasn't hiding the pedestrian-dragging video from regulators — it just had bad internet (00:40:32) Hugging Face teams up with Google to accelerate open AI development (00:43:33) Elon Musk's xAI eyes $6 billion funding to challenge ChatGPT maker OpenAI (00:47:22)  AI Chip Startup Rebellions Snags Funding to Challenge Nvidia Projects & Open Source (00:50:07) New open source AI coding tool surpasses its inspiration: Google DeepMind's AlphaCode (00:53:00) Meta's free Code Llama AI programming tool closes the gap with GPT-4 (00:54:30) DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence Lighting round Research & Advancements (00:55:50) Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding (01:05:15) EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty (01:09:20) Are Vision Transformers More Data Hungry Than Newborn Visual Systems? (01:15:52) Circuit Component Reuse Across Tasks in Transformer Language Models (01:20:30) A ‘Shocking' Amount of the Web Is Already AI-Translated Trash, Scientists Determine Policy & Safety (01:22:45) Taylor Swift AI images prompt US bill to tackle nonconsensual, sexual deepfakes (01:27:50) OpenAI and Google will be required to notify the government about AI models (01:32:12) The campaign to take down the Biden AI executive order (01:33:06) Rep. Jeff Jackson Introduces Bipartisan CLOUD AI Act to Stop China from Remotely Using American Technology to Build AI Tools (01:39:00) AI Startup ElevenLabs Bans Account Blamed for Biden Audio Deepfake (01:40:06) How the West Can Match Russia in Drone Innovation (01:45:15) Outro

Dans cet épisode, Katia, Arnaud et Emmanuel discutent les nouvelles de cette fin 2023. Le gatherer dans les stream Java, les exceptions, JavaScript dans la JVM, recherche vectorielle, coût du cloud, Gemini, Llama et autres animaux fantastiques et pleins d'outils sympathiques pour fêter la fin de l'année. Enregistré le 15 décembre 2023 Téléchargement de l'épisode LesCastCodeurs-Episode-304.mp3 News Aide Les Cast Codeurs et remplis un petit formulaire pour nous guider l'année prochaine https://lescastcodeurs.com/sondage Langages Avec JEP 461, arrivée dans en preview dans Java 22 de la notion de “gatherer” pour les streams https://groovy.apache.org/blog/groovy-gatherers dans cet article de Paul King, de l'équipe Groovy, il montre et contraste ce que l'on pouvait faire en Groovy depuis des années, comme des sliding windows, par exemple explique l'approche des gatherers avec ses opérations intermédiaires gatherer sont des operations intermediaires custom qui prennent un etat et le prochain element pour decided quoi faire, et meme changer le stream d'elements suivants (en publier) (via la fonction integrate certains peuvent permettre de combiner les resultats intermediaires (pour paralleliser) Examples : fenetres de taille fixe, fenettres glissantes Joe Duffy, qui est CEO de Pulumi, mais qui avait travaillé chez Microsoft sur le project Midori (un futur OS repensé) parle du design des exceptions, des erreurs, des codes de retour https://joeduffyblog.com/2016/02/07/the-error-model/ Il compare les codes d'erreurs, les exceptions, checked et non-checked il separe les bugs des erreurs attendues (bugs doivent arreter le process) il raconte l'histoire des unchecked exception et leurs problemes et des checked exceptopns et poourquoi les developeurs java les detestent (selon lui) long article maisn interessant dans ses retours mais lon je ne suis pas allé au bout :smile: Après la disparition de Nashorn dans le JDK, on peut se tourner vers le projet Javet https://www.caoccao.com/Javet/index.html Javet permet d'intégrer JavaScript avec le moteur V8 Mais aussi carrément Node.js c'est super comme capacité car on a les deux mielleurs moteurs, par contre le support hors x86 est plus limité (genre arm sous windows c'est non) Librairies Une partie de l'équipe Spring se fait lourder après le rachat effectif de Broadcom https://x.com/odrotbohm/status/1729231722498425092?s=20 peu d'info en vrai à part ce tweet mais l'acquisition Broadcome n'a pas l'air de se faire dans le monde des bisounours Marc Wrobel annonce la sortie de JBanking 4.2.0 https://www.marcwrobel.fr/sortie-de-jbanking-4-2-0 support de Java 21 possibilité de générer aléatoirement des BIC amélioration de la génération d'IBAN jbanking est une bibliotheque pour manipuler des structures typiques des banques comme les IBAN les BIC, les monnaies, les SEPA etc. Hibernate Search 7 est sorti https://in.relation.to/2023/12/05/hibernate-search-7-0-0-Final/ Support ElasticSearch 8.10-11 et openSearch 2.10-11 Rebasé sur Lucerne 9.8 support sur Amazon OpenSearch Serverless (experimental) attention sous ensemble de fonctionnalités sur Serverless, c'est un API first search cluster vendu a la lambda En lien aussi sur la version 7.1 alpha1 Hibernate ORM 6.4 est sorti https://in.relation.to/2023/11/23/orm-640-final/ support pour SoftDelete (colonne marquant la suppression) support pour les operations vectorielles (support postgreSQL initialement) les fonctions vectorielles sont particulièrement utilisées par l'IA/ML événement spécifiques JFR Intégration de citrus et Quarkus pour les tests d'intégrations de pleins de protocoles et formats de message https://quarkus.io/blog/testing-quarkus-with-citrus/ permet de tester les entrees / sorties attendues de systèmes de messages (HTTP, Kafka, serveur mail etc) top pour tester les application Event Driven pas de rapport mais Quarkus 3.7 ciblera Java 17 (~8% des gens utilisaient Java 11 dans les builds qui ont activé les notifications) Hibernate Search 7.1 (dev 7.1.0.Alpha1) avec dernière version de Lucene (9.8), Infinispan rajoute le support pour la recherche vectorielle. https://hibernate.org/search/releases/7.1/ https://infinispan.org/blog/2023/12/13/infinispan-vector-search Hibernate Search permet maintenant la recherche vectorielle La dernière version est intégrée en Infinispan 15 (dev) qui sortira La recherche vectoriolle et stockage de vecteurs, permettent convertir Infinispan en Embedding Store (langchain) Cloud Comment choisir sa region cloud https://blog.scottlogic.com/2023/11/23/conscientious-cloud-pick-your-cloud-region-deliberately.html pas si simple le coût la securité légale de vos données la consommation carbone de la région choisie (la France est top, la Pologne moins) la latence vs où sont vos clients les services supportés Web Vers une standardisation des Webhooks ? https://www.standardwebhooks.com/ Des gens de Zapier, Twilio, Ngrok, Kong, Supabase et autres, se rejoignent pour essayer de standardiser l'approche des Webhooks La spec est open source (Apache) sur Github https://github.com/standard-webhooks/standard-webhooks/blob/main/spec/standard-webhooks.md Les objectifs sont la sécurité, la reliabilité, l'interopérabilité, la simplicité et la compatibilité (ascendante / descendante) sans la spec, chaque webhook est different dans son comportement et donc les clients doivent s'adapter dans la sematique et les erreurs etc la (meta-) structure de la payload, la taille, la securisation via signature (e.g. hmac), les erreurs (via erreurs HTTP), etc Data et Intelligence Artificielle Google annonce Gemini, son nouveau Large Language Model https://blog.google/technology/ai/google-gemini-ai/#sundar-note modèle multimodal qui peut prendre du texte, en entrée, mais aussi des images, du son, des vidéos d'après les benchmarks, il est largement aussi bon que GPT4 plusieurs tailles de modèles disponible : Nano pour être intégré aux mobiles, Pro qui va être utilisé dans la majeure partie des cas, et Ultra pour les besoins de réflexion les plus avancés Android va rajouter aussi des librairies AICore pour utiliser Gemini Nano dans les téléphones Pixel https://android-developers.googleblog.com/2023/12/a-new-foundation-for-ai-on-android.html Gemini Pro va être disponible dans Bard (en anglais et dans 170 pays, mais l'Europe va devoir attendre un petit peu pour que ce soit dispo) Gemini Ultra devrait aussi rejoindre Bard, dans une version étendue https://blog.google/products/bard/google-bard-try-gemini-ai/ Gemini va être intégré progressivement dans plein de produits Google DeepMind parlant de Gemini https://deepmind.google/technologies/gemini/#introduction Un rapport de 60 pages sur Gemini https://storage.googleapis.com/deepmind-media/gemini/gemini_1_report.pdf Gemini a permis aussi de pouvoir développer une nouvelle version du modèle AlphaCode qui excelle dans les compétitions de coding https://storage.googleapis.com/deepmind-media/AlphaCode2/AlphaCode2_Tech_Report.pdf Liste de petites vidéos sur YouTube avec des interviews et démonstrations des capacités de Gemini https://www.youtube.com/playlist?list=PL590L5WQmH8cSyqzo1PwQVUrZYgLcGZcG malheureusement certaines des annonces sont un peu fausse ce qui a amené un discrédit (non du) sur Gemini par exemple la video “aspirationelle” était vendue comme du réel mais ce n'est pas le cas. et ultra n'est pas disponible encore ausso la comparaison de ChatGPT sur la page (initialement au moins) comparait des choux et des carottes, meme si le papier de recherche était correct Avec la sortie de Gemini, Guillaume a écrit sur comment appeler Gemini en Java https://glaforge.dev/posts/2023/12/13/get-started-with-gemini-in-java/ Gemini est multimodèle, donc on peut passer aussi bien du texte que des images, ou même de la vidéo Il y a un SDK en Java pour interagir avec l'API de Gemini Facebook, Purple Llama https://ai.meta.com/blog/purple-llama-open-trust-safety-generative-ai/ Opensource https://ai.meta.com/llama/ dans l'optique des modeles GenAI ouverts, Facebook fournit des outils pour faire des IA responsables (mais pas coupables :wink: ) notament des benchmarks pour evaluler la sureté et un classifier de sureté, par exemple pour ne pas generer du code malicieux (ou le rendre plus dur) llama purple sera un projet parapluie D'ailleurs Meta IBM, Red Hat et pleins d'autres ont annoncé l'AI Alliance pour une AI ouverte et collaborative entre académique et industriels. Sont notammenrt absent Google, OpenAI (pas ouvert) et Microsoft Juste une annouce pour l'instant mais on va voir ce que ces acteurs de l'AI Alliance feront de concret il y a aussi un guide d'utilisateur l'usage IA responsable (pas lu) Apple aussi se met aux librairies de Machine Learning https://ml-explore.github.io/mlx/build/html/index.html MLX est une librairie Python qui s'inspire fortement de NumPy, PyTorch, Jax et ArrayFire Surtout, c'est développé spécifiquement pour les Macs, pour tirer au maximum parti des processeurs Apple Silicon Dans un des repos Github, on trouve également des exemples qui font tourner nativement sur macOS les modèles de Llama, de Mistral et d'auters https://github.com/ml-explore/mlx-examples non seulement les Apple Silicon amis aussi la memoire unifiee CPU/GPU qui est une des raisons clés de la rapidité des macs Faire tourner Java dans un notebook Jupyter https://www.javaadvent.com/2023/12/jupyter-notebooks-and-java.html Max Andersen explore l'utilisation de Java dans les notebooks Jupyter, au lieu du classique Python il y a des kernels java selon vos besoins mais il faut les installer dans la distro jupyter qu'on utilise et c'est la que jbang installable via pip vient a la rescousse il installe automatiquement ces kernels en quelques lignes Outillage Sfeir liste des jeux orientés développeurs https://www.sfeir.dev/tendances/notre-selection-de-jeux-de-programmation/ parfait pour Noël mais c'est pour ceux qui veulent continuer a challenger leur cerveau après le boulot jeu de logique, jeu de puzzle avec le code comme forme, jeu autour du machine learning, jeu de programmation assembleur Les calendriers de l'Avent sont populaires pour les développeurs ! En particulier avec Advent of Code https://adventofcode.com/ Mais il y a aussi l'Advent of Java https://www.javaadvent.com/ Ou un calendrier pour apprendre les bases de SVG https://svg-tutorial.com/ Le calendrier HTML “hell” https://www.htmhell.dev/adventcalendar/ qui parle d'accessibilité, de web components, de balises meta, de toutes les choses qu'on peut très bien faire en HTML/CSS sans avoir besoin de JavaScript Pour les développeurs TypeScript, il y a aussi un calendrier de l'Avent pour vous ! https://typehero.dev/aot-2023 Un super thread de Clara Dealberto sur le thème de la “dataviz” (data visualization) https://twitter.com/claradealberto/status/1729447130228457514 Beaucoup d'outil librement accessibles sont mentionnés pour faire toutes sortes de visualisations (ex. treemap, dendros, sankey…) mais aussi pour la cartographie Quelques ressources de site qui conseillent sur l'utilisation du bon type de visualisation en fonction du problème et des données que l'on a notemment celui du financial time qui tiens dans une page de PDF Bref c'est cool mais c'est long a lire Une petite liste d'outils sympas - jc pour convertir la sortie de commandes unix en JSON https://github.com/kellyjonbrazil/jc - AltTab pour macOS pour avoir le même comportement de basculement de fenêtre que sous Windows https://alt-tab-macos.netlify.app/ - gron pour rendre le JSON grep-able, en transformant chaque valeur en ligne ressemblant à du JSONPath https://github.com/tomnomnom/gron - Marker, en Python, pour transformer des PDF en beau Markdown https://github.com/VikParuchuri/marker - n8n un outil de workflow open source https://n8n.io/ gron en fait montre des lignes avec des assignments genre jsonpath = value et tu peux ungroner apres pour revenir a du json Marker utilise du machine learning mais il halklucine moins que nougat (nous voilà rassuré) Docker acquiert Testcontainers https://techcrunch.com/2023/12/11/docker-acquires-atomicjar-a-testing-startup-that-raised-25m-in-january/ Annonce par AtomicJar https://www.atomicjar.com/2023/12/atomicjar-is-now-part-of-docker/ Annonce par Docker https://www.docker.com/blog/docker-whale-comes-atomicjar-maker-of-testcontainers/ Architecture Comment implémenter la reconnaissance de chanson, comme Shazam https://www.cameronmacleod.com/blog/how-does-shazam-work il faut d'abord passer en mode fréquence avec des transformées de Fourrier pour obtenir des spectrogrammes puis créer une sorte d'empreinte qui rassemble des pics de fréquences notables à divers endroits de la chanson d'associer ces pics pour retrouver un enchainement de tels pics de fréquence dans le temps l'auteur a partagé son implémentation sur Github https://github.com/notexactlyawe/abracadabra/blob/e0eb59a944d7c9999ff8a4bc53f5cfdeb07b39aa/abracadabra/recognise.py#L80 Il y avait également une très bonne présentation sur ce thème par Moustapha Agack à DevFest Toulouse https://www.youtube.com/watch?v=2i4nstFJRXU les pics associés sont des hash qui peut etre comparés et le plus de hash veut dire que les chansons sont plus similaires Méthodologies Un mémo de chez ThoughtWorks à propos du coding assisté par IA https://martinfowler.com/articles/exploring-gen-ai.html#memo-08 Avec toute une liste de questions à se poser dans l'utilisation d'un outil tel que Copilot Il faut bien réaliser que malheureusement, une IA n'a pas raison à 100% dans ses réponses, et même plutôt que la moitié du temps, donc il faut bien mettre à jour ses attentes par rapport à cela, car ce n'est pas magique La conclusion est intéressante aussi, en suggérant que grosso modo dans 40 à 60% des situations, tu peux arriver à 40 à 80% de la solution. Est-ce que c'est à partir de ce niveau là qu'on peut vraiment gagner du temps et faire confiance à l'IA ? Ne perdez pas trop de temps non plus à essayer de convaincre l'IA de faire ce que vous voulez qu'elle fasse. Si vous n'y arrivez pas, c'est sans doute parce que l'IA n'y arrivera même pas elle même ! Donc au-delà de 10 minutes, allez lire la doc, chercher sur Google, etc. notamment, faire genrer les tests par l'IA dans al foulée augmente les risques surtout si on n'est pas capable de bien relire le code si on introduit un choix de pattern genre flexbox en CSS, si c'est sur une question de sécuriter, vérifier (ceinture et bretelle) est-ce le framework de la semaine dernière? L'info ne sera pas dans le LLM (sans RAG) Quelles capacités sont nécessaires pour déployer un projet AI/ML https://blog.scottlogic.com/2023/11/22/capabilities-to-deploy-ai-in-your-organisation.html C'est le MLOps et il y a quelques modèles end to end Google, IBM mais vu la diversité des organisations, c'est difficile a embrasser ces versions completes ML Ops est une métier, data science est un metier, donc intégrer ces competences sachez gérer votre catalogue de données Construire un process pour tester vos modèles et continuellement La notion de culture de la recherche et sa gestion (comme un portefeuille financier, accepter d'arrêter des experience etc) la culture de la recherche est peu présente en engineering qui est de construire des choses qui foncitonnent c'est un monde pre LLM Vous connaissez les 10 dark patterns de l'UX ? Pour vous inciter à cliquer ici ou là, pour vous faire rester sur le site, et plus encore https://dodonut.com/blog/10-dark-patterns-in-ux-design/ Parmi les dark patterns couverts Confirmshaming Fake Urgency and the Fear of Missing Out Nagging Sneaking Disguised Ads Intentional Misdirection The Roach Motel Pattern Preselection Friend Spam Negative Option Billing or Forced Continuity L'article conclut avec quelques pistes sur comment éviter ces dark patterns en regardant les bons patterns de la concurrence, en testant les interactions UX, et en applicant beaucoup de bon sens ! les dark patterns ne sont pas des accidents, ils s'appuient sur la psychologie et sont mis en place specifiquement Comment choisir de belles couleurs pour la visualisation de données ? https://blog.datawrapper.de/beautifulcolors/ Plutôt que de penser en RGB, il vaut mieux se positionner dans le mode Hue Saturation Brightness Plein d'exemples montrant comment améliorer certains choix de couleurs Mieux vaut éviter des couleurs trop pures ou des couleurs trop brillantes et saturées Avoir un bon contraste Penser aussi aux daltoniens ! j'ai personnellement eu toujours du mal avec saturationm vs brightness faire que les cloueirs en noir et blanc soient separees evant de le remettre (en changeant la brightness de chaque couleur) ca aide les daltoniens eviter les couleurs aux 4 coins amis plutot des couleurs complementaires (proches) rouge orange et jaune (non saturé) et variations de bleu sont pas mal les couleurs saturées sont aggressives et stressent les gens Pourquoi vous devriez devenir Engineering Manager? https://charity.wtf/2023/12/15/why-should-you-or-anyone-become-an-engineering-manager/ L'article parle de l'évolution de la perception de l'engineering management qui n'est plus désormais le choix de carrière par défaut pour les ingénieurs ambitieux. Il met en évidence les défis auxquels les engineering managers sont confrontés, y compris les attentes croissantes en matière d'empathie, de soutien et de compétences techniques, ainsi que l'impact de la pandémie de COVID-19 sur l'attrait des postes de management. L'importance des bons engineering mnanagers est soulignée, car ils sont considérés comme des multiplicateurs de force pour les équipes, contribuant de manière significative à la productivité, à la qualité et au succès global dans les environnements organisationnels complexes. L'article fournit des raisons pour lesquelles quelqu'un pourrait envisager de devenir Engineering Manager, y compris acquérir une meilleure compréhension de la façon dont les entreprises fonctionnent, contribuer au mentorat et influencer les changements positifs dans la dynamique des équipes et les pratiques de l'industrie. Une perspective est présentée, suggérant que devenir Engineering manager peut conduire à la croissance personnelle et à l'amélioration des compétences de vie, telles que l'autorégulation, la conscience de soi, la compréhension des autres, l'établissement de limites, la sensibilité à la dynamique du pouvoir et la maîtrise des conversations difficiles. L'article encourage à considérer la gestion comme une occasion de développer et de porter ces compétences pour la vie. Sécurité LogoFAIL une faille du bootloader de beaucoup de machines https://arstechnica.com/security/2023/12/just-about-every-windows-and-linux-device-vulnerable-to-new-logofail-firmware-attack/ en gros en changeant les eimages qu'on voit au boot permet d'executer du code arbitraire au tout debuit de la securisation du UEFI (le boot le plus utilisé) donc c'est game over parce que ca demarre avant l'OS c'est pas une exploitation a distance, il faut etre sur la machine avec des droits assez elevés deja mais ca peut etre la fin de la chaine d'attaque et comme d'hab un interpreteur d'image est la cause de ces vulnerabilités Conférences L'IA au secours de conférences tech: rajoute des profile tech femme comme speaker au programme pour passer le test diversité online via des profiles fake. https://twitter.com/GergelyOrosz/status/1728177708608450705 https://www.theregister.com/2023/11/28/devternity_conference_fake_speakers/ https://www.developpez.com/actu/351260/La-conference-DevTernity-sur-la-technologie-s-e[…]s-avoir-cree-de-fausses-oratrices-generees-automatiquement/ j'avais lu le tweet du createur de cette conf qui expliquait que c'etait des comptes de tests et que pris dans le rush ils avaient oublié de les enlever mais en fait les comptes de tests ont des profils “Actifs” sur le reseaux sociaux apparemment donc c'était savamment orchestré Au final beaucoup de speakers et des sponsors se desengagent La liste des conférences provenant de Developers Conferences Agenda/List par Aurélie Vache et contributeurs : 31 janvier 2024-3 février 2024 : SnowCamp - Grenoble (France) 1 février 2024 : AgiLeMans - Le Mans (France) 6 février 2024 : DevFest Paris - Paris (France) 8-9 février 2024 : Touraine Tech - Tours (France) 15-16 février 2024 : Scala.IO - Nantes (France) 6-7 mars 2024 : FlowCon 2024 - Paris (France) 14-15 mars 2024 : pgDayParis - Paris (France) 19 mars 2024 : AppDeveloperCon - Paris (France) 19 mars 2024 : ArgoCon - Paris (France) 19 mars 2024 : BackstageCon - Paris (France) 19 mars 2024 : Cilium + eBPF Day - Paris (France) 19 mars 2024 : Cloud Native AI Day Europe - Paris (France) 19 mars 2024 : Cloud Native Wasm Day Europe - Paris (France) 19 mars 2024 : Data on Kubernetes Day - Paris (France) 19 mars 2024 : Istio Day Europe - Paris (France) 19 mars 2024 : Kubeflow Summit Europe - Paris (France) 19 mars 2024 : Kubernetes on Edge Day Europe - Paris (France) 19 mars 2024 : Multi-Tenancy Con - Paris (France) 19 mars 2024 : Observabiity Day Europe - Paris (France) 19 mars 2024 : OpenTofu Day Europe - Paris (France) 19 mars 2024 : Platform Engineering Day - Paris (France) 19 mars 2024 : ThanosCon Europe - Paris (France) 19-21 mars 2024 : IT & Cybersecurity Meetings - Paris (France) 19-22 mars 2024 : KubeCon + CloudNativeCon Europe 2024 - Paris (France) 26-28 mars 2024 : Forum INCYBER Europe - Lille (France) 28-29 mars 2024 : SymfonyLive Paris 2024 - Paris (France) 4-6 avril 2024 : Toulouse Hacking Convention - Toulouse (France) 17-19 avril 2024 : Devoxx France - Paris (France) 18-20 avril 2024 : Devoxx Greece - Athens (Greece) 25-26 avril 2024 : MiXiT - Lyon (France) 25-26 avril 2024 : Android Makers - Paris (France) 8-10 mai 2024 : Devoxx UK - London (UK) 16-17 mai 2024 : Newcrafts Paris - Paris (France) 24 mai 2024 : AFUP Day Nancy - Nancy (France) 24 mai 2024 : AFUP Day Poitiers - Poitiers (France) 24 mai 2024 : AFUP Day Lille - Lille (France) 24 mai 2024 : AFUP Day Lyon - Lyon (France) 2 juin 2024 : PolyCloud - Montpellier (France) 6-7 juin 2024 : DevFest Lille - Lille (France) 6-7 juin 2024 : Alpes Craft - Grenoble (France) 27-28 juin 2024 : Agi Lille - Lille (France) 4-5 juillet 2024 : Sunny Tech - Montpellier (France) 19-20 septembre 2024 : API Platform Conference - Lille (France) & Online 7-11 octobre 2024 : Devoxx Belgium - Antwerp (Belgium) 10-11 octobre 2024 : Volcamp - Clermont-Ferrand (France) 10-11 octobre 2024 : Forum PHP - Marne-la-Vallée (France) 17-18 octobre 2024 : DevFest Nantes - Nantes (France) Nous contacter Pour réagir à cet épisode, venez discuter sur le groupe Google https://groups.google.com/group/lescastcodeurs Contactez-nous via twitter https://twitter.com/lescastcodeurs Faire un crowdcast ou une crowdquestion Soutenez Les Cast Codeurs sur Patreon https://www.patreon.com/LesCastCodeurs Tous les épisodes et toutes les infos sur https://lescastcodeurs.com/

Our 146th episode with a summary and discussion of last week's big AI news! Correction: Gemini also supports audio Also check out our sponsor, the SuperDataScience podcast. You can listen to SDS across all major podcasting platforms (e.g., Spotify, Apple Podcasts, Google Podcasts) plus there's a video version on YouTube. Read out our text newsletter and comment on the podcast at https://lastweekin.ai/ Email us your questions and feedback at contact@lastweekin.ai Timestamps + links: (00:00:00) Intro/Sponsor Read Tools & Apps(00:03:00) Google Just Launched Gemini, Its Long-Awaited Answer to ChatGPT (00:14:15) Google's best Gemini demo was faked  (00:19:33) Early impressions of Google's Gemini aren't great (00:22:30) Google unveils AlphaCode 2, powered by Gemini (00:24:50) Pixel 8 Pro — the first smartphone with AI built in — is now running Gemini Nano (00:25:55) Meta unveils Audiobox, an AI that clones voices and generates ambient sounds (00:29:55) Oops! Elon Musk's Grok AI Caught Plagiarizing OpenAI's ChatGPT (00:33:21) Elon Musk Fans Horrified When His Grok AI Immediately "Goes Woke" (00:34:51) Gmail's AI-powered spam detection is its biggest security upgrade in years (00:35:55) Augmenting Local AI with Browser Data: Introducing MemoryCache Applications & Business(00:37:23) Meta and Microsoft say they will buy AMD's new AI chip as an alternative to Nvidia's (00:42:02) China poised to break 5nm barrier — Huawei lists 5nm processor presumably built with SMIC tech, defying U.S. sanctions (00:46:44) OpenAI's Altman Ouster Was Result of Drawn-Out Tensions (00:50:20) The OpenAI Board Member Who Clashed With Sam Altman Shares Her Side (00:51:46)  Google announces the Cloud TPU v5p, its most powerful AI accelerator yet (00:54:08) Tesla's Dojo Supercomputer Head Exits in Blow to Efforts (00:56:45) AssemblyAI lands $50M to build and serve AI speech models (00:57:41) Sydney-based generative AI art platform Leonardo.Ai raises $31M Projects & Open Source(00:59:20) Mixtral of experts (01:05:50) Meta AI unveils ‘Seamless' translator for real-time communication across languages (01:07:07) Paving the way to efficient architectures: StripedHyena-7B, open source models offering a glimpse into a world beyond Transformers (01:10:15) Introducing Purple Llama for Safe and Responsible AI Development Research & Advancements(01:13:21) WALT is a new AI video tool that creates photorealistic clips from a single image — you have to see it to believe it (01:14:20) Long context prompting for Claude 2.1 (01:17:40) Real-World Humanoid Locomotion with Reinforcement Learning (01:19:04) Defending ChatGPT against jailbreak attack via self-reminders (01:21:20) Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models (01:23:40) Who is leading in AI? An analysis of industry AI research Policy & Safety(01:26:41) E.U. Agrees on Landmark Artificial Intelligence Rules (01:33:58) More Trouble Brews For Microsoft As FTC Allegedly Starts Inquiring Into OpenAI Investment (01:39:12) Asking ChatGPT to Repeat Words ‘Forever' Is Now a Terms of Service Violation (01:41:22)  US in talks with Nvidia about AI chip sales to China (01:44:12) MIT group releases white papers on governance of AI (01:47:25) G7 agrees on first comprehensive guidelines for generative AI Synthetic Media & Art(01:49:03) High Court rules that Getty v Stability AI case can proceed (01:52:55) Top Execs at Sports Illustrated's Publisher Fired After AI Debacle (01:55:57) Outro

We don't delve too deep into the already covered demo-gate scandal, don't worry! This episode features insights from Senior ML Research Scientist Alex Pap and AI Startup Founder and CTO Nitish Mutha. We discuss: Google vs OpenAI for the long-term. GPT4 Vision, GPT5, Multimodal AI, Gemini Ultra, Gemini Pro, Gemini Nano, OpenAI Whisper, DALL·E 3, Chain of thought, Google, OpenAI, Bard, AI technology, Machine Learning Welcome to Episode 17: and the 3rd episode in our AI Market Leaders mini-series - focusing on Google vs OpenAI. This episode dives into all the details of the release in Gemini's Ultra, Pro, and Nano (and how that affects Alphacode2, and Bard). We also delve into multi-modal technology and its promise for the future. Watch This Episode of Using AI on youtube⁠⁠https://www.youtube.com/channel/UCHsQu4IipA7Ri2AqKcQZ1Yw⁠⁠ Topics Discussed: GPT4 Vision, GPT5, Multimodal AI Gemini's announcements and releases Google's catch up play with OpenAI (and a little bit about what they did wrong!) Additional Resources: Gemini Technical Report in full (PDF): https://storage.googleapis.com/deepmind-media/gemini/gemini_1_report.pdf Reddit post: Testing the Gemini demo video screenshots with GPT-4: https://www.reddit.com/r/ChatGPT/comments/18d9wgn/asked_gpt4_some_logical_questions_from_the_gemini/ GPT4 + Gemini Pro for coding: https://www.reddit.com/r/ChatGPT/comments/18d773r/gpt4_and_gemini_cocreated_code_better_than_gpt4/ AI Explained's breakdown on Youtube: https://www.youtube.com/watch?v=toShbNUGAyo&ab_channel=AIExplained GPT4 comparison controversy https://twitter.com/kenshin9000_/status/1734238211088506967?s=46 Alex D's Midjourney background (Godzilla walking through a town in the style of 'The Starry Night Painting by Vincent van Gogh: https://www.reddit.com/r/midjourney/comments/18gt00b/exactly_what_i_expected_and_more_amazing/ Running an LLM on your Pixel 8 Pro: https://store.google.com/intl/en/ideas/articles/pixel-feature-drop-december-2023/ Deep dive into AlphaCode 2 on TechCrunch: ⁠https://tcrn.ch/46G5u8w⁠ --- Send in a voice message: https://podcasters.spotify.com/pod/show/using-ai/message

Infomaniak partage les valeurs de Tech Café : éthique, écologie et respect de la vie privée. Découvrez les services de notre partenaire sur Infomaniak.comL'actualité de la tech se rapproche de la fin de l'année comme elle a commencé et nous sommes habitués désormais à parler d'intelligence artificielle parce qu'il se passe des choses chaque semaine, parce que c'est intéressant et parce qu'en vrai, ce serait irresponsable de ne pas vous en parler au fur et à mesure. Et cette semaine, l'actualité marquante c'est le nouveau modèle d'intelligence artificielle de Google : Gemini. ❤️ Patreon

Google unveils AlphaCode 2, powered by Gemini

In this episode, we delve into the latest technological advancements as Google unveils AlphaCode 2 and its new component, Gemini. We explore the features, potential impacts, and what this means for the world of coding and AI development.

In this episode, we explore Google's latest release, AlphaCode 2, and its integration with the advanced Gemini technology. We delve into how these innovative tools are set to revolutionize the coding landscape, examining their features, potential impacts, and how they differ from their predecessors. Invest in AI Box: https://republic.com/ai-box AI Box Waitlist: https://aibox.ai/

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Possible OpenAI's Q* breakthrough and DeepMind's AlphaGo-type systems plus LLMs, published by Burny on November 23, 2023 on LessWrong. tl;dr: OpenAI leaked AI breakthrough called Q*, acing grade-school math. It is hypothesized combination of Q-learning and A*. It was then refuted. DeepMind is working on something similar with Gemini, AlphaGo-style Monte Carlo Tree Search. Scaling these might be crux of planning for increasingly abstract goals and agentic behavior. Academic community has been circling around these ideas for a while. https://www.reuters.com/technology/sam-altmans-ouster-openai-was-precipitated-by-letter-board-about-ai-breakthrough-2023-11-22/ https://twitter.com/MichaelTrazzi/status/1727473723597353386 "Ahead of OpenAI CEO Sam Altman's four days in exile, several staff researchers sent the board of directors a letter warning of a powerful artificial intelligence discovery that they said could threaten humanity Mira Murati told employees on Wednesday that a letter about the AI breakthrough called Q* (pronounced Q-Star), precipitated the board's actions. Given vast computing resources, the new model was able to solve certain mathematical problems. Though only performing math on the level of grade-school students, acing such tests made researchers very optimistic about Q*'s future success." https://twitter.com/SilasAlberti/status/1727486985336660347 "What could OpenAI's breakthrough Q* be about? It sounds like it's related to Q-learning. (For example, Q* denotes the optimal solution of the Bellman equation.) Alternatively, referring to a combination of the A* algorithm and Q learning. One natural guess is that it is AlphaGo-style Monte Carlo Tree Search of the token trajectory. It seems like a natural next step: Previously, papers like AlphaCode showed that even very naive brute force sampling in an LLM can get you huge improvements in competitive programming. The next logical step is to search the token tree in a more principled way. This particularly makes sense in settings like coding and math where there is an easy way to determine correctness. https://twitter.com/mark_riedl/status/1727476666329411975 "Anyone want to speculate on OpenAI's secret Q* project? Something similar to tree-of-thought with intermediate evaluation (like A*)? Monte-Carlo Tree Search like forward roll-outs with LLM decoder and q-learning (like AlphaGo)? Maybe they meant Q-Bert, which combines LLMs and deep Q-learning Before we get too excited, the academic community has been circling around these ideas for a while. There are a ton of papers in the last 6 months that could be said to combine some sort of tree-of-thought and graph search. Also some work on state-space RL and LLMs." https://www.theverge.com/2023/11/22/23973354/a-recent-openai-breakthrough-on-the-path-to-agi-has-caused-a-stir OpenAI spokesperson Lindsey Held Bolton refuted it: "refuted that notion in a statement shared with The Verge: "Mira told employees what the media reports were about but she did not comment on the accuracy of the information."" https://www.wired.com/story/google-deepmind-demis-hassabis-chatgpt/ Google DeepMind's Gemini, that is currently the biggest rival with GPT4, which was delayed to the start of 2024, is also trying similar things: AlphaZero-based MCTS through chains of thought, according to Hassabis. Demis Hassabis: "At a high level you can think of Gemini as combining some of the strengths of AlphaGo-type systems with the amazing language capabilities of the large models. We also have some new innovations that are going to be pretty interesting." https://twitter.com/abacaj/status/1727494917356703829 Aligns with DeepMind Chief AGI scientist Shane Legg saying: "To do really creative problem solving you need to start searching." https://twitter.com/iamgingertrash/status/1727482695356494132 "...

Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Possible OpenAI's Q* breakthrough and DeepMind's AlphaGo-type systems plus LLMs, published by Burny on November 23, 2023 on LessWrong. tl;dr: OpenAI leaked AI breakthrough called Q*, acing grade-school math. It is hypothesized combination of Q-learning and A*. It was then refuted. DeepMind is working on something similar with Gemini, AlphaGo-style Monte Carlo Tree Search. Scaling these might be crux of planning for increasingly abstract goals and agentic behavior. Academic community has been circling around these ideas for a while. https://www.reuters.com/technology/sam-altmans-ouster-openai-was-precipitated-by-letter-board-about-ai-breakthrough-2023-11-22/ https://twitter.com/MichaelTrazzi/status/1727473723597353386 "Ahead of OpenAI CEO Sam Altman's four days in exile, several staff researchers sent the board of directors a letter warning of a powerful artificial intelligence discovery that they said could threaten humanity Mira Murati told employees on Wednesday that a letter about the AI breakthrough called Q* (pronounced Q-Star), precipitated the board's actions. Given vast computing resources, the new model was able to solve certain mathematical problems. Though only performing math on the level of grade-school students, acing such tests made researchers very optimistic about Q*'s future success." https://twitter.com/SilasAlberti/status/1727486985336660347 "What could OpenAI's breakthrough Q* be about? It sounds like it's related to Q-learning. (For example, Q* denotes the optimal solution of the Bellman equation.) Alternatively, referring to a combination of the A* algorithm and Q learning. One natural guess is that it is AlphaGo-style Monte Carlo Tree Search of the token trajectory. It seems like a natural next step: Previously, papers like AlphaCode showed that even very naive brute force sampling in an LLM can get you huge improvements in competitive programming. The next logical step is to search the token tree in a more principled way. This particularly makes sense in settings like coding and math where there is an easy way to determine correctness. https://twitter.com/mark_riedl/status/1727476666329411975 "Anyone want to speculate on OpenAI's secret Q* project? Something similar to tree-of-thought with intermediate evaluation (like A*)? Monte-Carlo Tree Search like forward roll-outs with LLM decoder and q-learning (like AlphaGo)? Maybe they meant Q-Bert, which combines LLMs and deep Q-learning Before we get too excited, the academic community has been circling around these ideas for a while. There are a ton of papers in the last 6 months that could be said to combine some sort of tree-of-thought and graph search. Also some work on state-space RL and LLMs." https://www.theverge.com/2023/11/22/23973354/a-recent-openai-breakthrough-on-the-path-to-agi-has-caused-a-stir OpenAI spokesperson Lindsey Held Bolton refuted it: "refuted that notion in a statement shared with The Verge: "Mira told employees what the media reports were about but she did not comment on the accuracy of the information."" https://www.wired.com/story/google-deepmind-demis-hassabis-chatgpt/ Google DeepMind's Gemini, that is currently the biggest rival with GPT4, which was delayed to the start of 2024, is also trying similar things: AlphaZero-based MCTS through chains of thought, according to Hassabis. Demis Hassabis: "At a high level you can think of Gemini as combining some of the strengths of AlphaGo-type systems with the amazing language capabilities of the large models. We also have some new innovations that are going to be pretty interesting." https://twitter.com/abacaj/status/1727494917356703829 Aligns with DeepMind Chief AGI scientist Shane Legg saying: "To do really creative problem solving you need to start searching." https://twitter.com/iamgingertrash/status/1727482695356494132 "...

Algunas reflexiones sobre GitHub Copilot y AlphaCode y su posible impacto en la manera que tenemos de concebir la programación.Artículos mencionados: Do Users Write More Insecure Code with AI Assistants?https://arxiv.org/abs/2211.03622The End of Programming. https://cacm.acm.org/magazines/2023/1/267976-the-end-of-programming/fulltextSupport the show

Andy and Dave discuss the latest in AI news and research, including the release of the US National Defense Authorization Act for FY2023, which includes over 200 mentions of “AI” and many more requirements for the Department of Defense. DoD has also awarded its cloud-computing contracts, not to one company, but four – Amazon, Google, Microsoft, and Oracle. At the end of November, the San Francisco Board voted to allow the police force to use robots to administer deadly force, however, after a nearly immediate response from a “No Killer Robots” campaign, in early December the board passed a revised version of the policy that prohibits police from using robots to kill people. Israeli company Elbit unveils its LANIUS drone, a “drone-based loitering munition” that can carry lethal or non-lethal payloads, and appears to have many functions similar to the ‘slaughter bots,' except for autonomous targeting. Neuralink shows the latest updates on its research for putting a brain chip interface into humans, with demonstrations of a monkey manipulating a mouse cursor with its thoughts; the company also faces a federal investigation into possible animal-welfare violations. DeepMind publishes AlphaCode in Science, a story that we covered back in February. DeepMind also introduces DeepNash, an autonomous agent that can play Stratego. OpenAI unleashes ChatGPT, a spin-off of GPT-3 optimized for answering questions through back-and-forth dialogue. Meanwhile, Stack Overflow, a website for programmers, temporarily banned users from sharing responses generated by ChatGPT, because the output of the algorithm might look good, but it has “a high rate of being incorrect.” Researchers at the Weizmann Institute of Science demonstrate that, with a simple neural network, it is possible to reconstruct a “large portion” of the actual training samples. NOMIC provides an interactive map to explore over 6M images from Stable Diffusion.  Steve Coulson creates “AI-assisted comics” using Midjourney. Stay tuned for AI Debate 3 on 23 December 2022. And the video of the week from Ricard Sole at the Santa Fe Institute explores mapping the cognition space of liquid and solid brains. https://www.cna.org/our-media/podcasts/ai-with-ai  

What is ChatGPT and why does it matter? | ZDNET (00:57) ChatGPT was created by OpenAI, an AI and research company. Launched on November 30, 2022.  ChatGPT is a natural language processing tool driven by AI technology that allows you to have human-like conversations and much more with a chatbot.It answers questions and can assist you with tasks Open to the public “ChatGPT is scary good. We are not far from dangerously strong AI," said nonother than Elon Musk Sam Altman, CEO of OpenAI, stated on twitter the success of their chatbot:“ChatGPT launched on wednesday. Today it crossed 1 million users!” Altman tweeted that just 5 days after ChatGPT went online One twitter thread that I've seen that shows the power of this sophisticated chatbot was posted by Ben Tossell (@bentossell)One tweet in the thread was a quote tweeting @jdjkelly post stating: “Google is done. Compare the quality of these responses (ChatGPT)” The tweet has pictures comparing the question asked in Google Search and ChatGPT. GPT was straightforward, explained thoroughly, and had examples. It should be noted when comparing GPT to a search engineChatGPT does not have the ability to search the internet for information and rather, uses the information it learned from training data to generate a response, which leaves room for error.  One issue I have encountered with GPT is that the responses it generates are not always of high quality. Responses may sound plausible, but they lack practical sense or are overly verbose.   NASA's TBIRD Mission Demonstrates 1.4TB Optical Downlink | Via Satellite (06:18) NASA's TBIRD mission recently achieved a record for optical communications in spaceThe satellite downlinked 1.4 terabytes of data over laser communications links in a single pass that lasted about five minutes. TBIRD = TeraByte InfraRed Delivery According to NASA, the goal of the TBIRD program was to “establish a communication link from a nanosatellite in low-Earth orbit to a ground station at burst rates up to 200 Gbps.”Built by the MIT Lincoln Laboratory  Integrated into NASA's Pathfinder Technology Demonstrator 3 Satellite (PTD-3) NASA confirmed this amazing data transfer milestone on Twitter:“Our tiny TBIRD payload just achieved a major milestone! The @NASA_Technology mission downlinked a record-setting data volume of 1.4 terabytes over laser comm links in a single, ~5-minute pass. TBIRD is showing the benefits laser comm can have for missions.”   Paper-thin solar cell can turn any surface into a power source | TechXplore (09:34) MIT engineers have developed ultralight fabric solar cells that can quickly and easily turn any surface into a power source.These durable, flexible solar cells are much thinner than a human hair. Are glued to a strong, lightweight fabric, making them easy to install on a fixed surface. Because they are so thin and lightweight, these solar cells can be laminated onto many different surfaces.Could be integrated onto the sails of a boat to provide power while at sea, Adhered onto tents and tarps that are deployed in disaster recovery operations Applied onto the wings of drones to extend their flying range.  They are one-hundredth the weight of conventional solar panels, generate 18 times more power-per-kilogram, and are made from semiconducting inks.Uses printing processes that can be scaled in the future to large-area manufacturing. When they tested the device, the MIT researchers found it could generate 730 watts of power per kilogram when freestanding and about 370 watts-per-kilogram if deployed on the high-strength fabric. 18 times more power-per-kilogram than conventional solar cells. After rolling and unrolling a fabric solar panel more than 500 times, the researchers saw that the cells still retained more than 90 percent of their initial power generation. Jeremiah Mwaura, a co-author on the study, explains why the team is looking at the encasing method next:“Encasing these solar cells in heavy glass, as is standard with the traditional silicon solar cells, would minimize the value of the present advancement, so the team is currently developing ultrathin packaging solutions that would only fractionally increase the weight of the present ultralight devices."    Cheap sodium-sulfur battery boasts 4x the capacity of lithium-ion | New Atlas (16:21) An international team of scientists eyeing next-generation energy storage solutions have demonstrated an eco-friendly and low-cost battery with some exciting potential.Sodium-sulfur battery design offers a fourfold increase on energy capacity compared to a typical lithium-ion battery The creation falls into a category of batteries known as molten-salt batteries.Energy storage system that uses a molten salt electrolyte to store electrical energy. Molten salt: Is solid at standard temperature and pressure but enters the liquid phase due to elevated temperature. Regular table salt has a melting point of 801 °C (1474°F). These batteries are theoretically attractive for use in grid-scale energy storage systems. Capable of storing large amounts of energy for long periods of time Also be discharged very quickly to meet sudden increases in demand.  The research team set out to address a couple of shortcomings with current sodium-sulfur batteries:Short life cycles and limited capacities The team's design makes use of carbon-based electrodes and a thermal degradation process known as pyrolysis to alter the reactions between the sulfur and sodium.Pyrolysis: The thermal decomposition of materials at elevated temperatures in an inert atmosphere. Result: a sodium-sulfur battery with a high capacity of 1,017 mAh/g  at room temperatureThe unit mAh/g stands for milliampere-hours per gram, and it is used to express the amount of electrical charge that a battery can store per unit of mass.  Importantly, the battery demonstrated good stability and retained around half of this capacity after 1,000 cycles, described in the team's paper as “unprecedented.” End on a quote from lead researcher Dr Shenlong Zhao: “Our sodium battery has the potential to dramatically reduce costs while providing four times as much storage capacity … This is a significant breakthrough for renewable energy development which, although reduces costs in the long term, has had several financial barriers to entry.” AlphaCode can solve complex problems and create code using AI | Interesting Engineering (22:33) A novel system called AlphaCode, created by DeepMind,uses artificial intelligence (AI) to create computer code.Recently participated in programming competitions, using critical thinking, algorithms, and natural language comprehension. The software generates code in Python or C++, while filtering out any bad coding.  Generates code at an exceptional rate The system was trained to solve problems and generate code solutions. It filters out bad code through a process that involves keeping only 1% of the programs that pass the test cases. There are a few AI coding systems, with another well-known system for coders called Codex. Codex was created by OpenAI, the makers of DALL-E and ChatGPT. Proficient in a dozen programming languages and powers GitHub copilot  AlphaCode was created to assist programmers by generating code, while also solving more complicated problems.Trying to solve issues that arose in other AI coding systems, such as solving difficult problems that require analysis and logic on a deeper level.  DeepMind discovered three key points that needed to be incorporated:An extensive and clean competitive programming dataset for training and evaluation,  Large and efficient-to-sample transformer-based architectures, and large-scale model sampling to explore the search space,  Followed by filtering based on program behavior to a small set of submissions AlphaCode in the study, solved about 34.2% of the problems:“With up to a million samples per problem, we can solve 34.2% of problems in our validation set; and with one hundred thousand samples, we solve 31.8% of problems in our validation set” DeepMind entered AlphaCode into online coding competitions. In competitions with 5000 programmers or more, AlphaCode ranked in the top 54.3%. Yujia Li, a computer scientist at DeepMind and paper co-author stated:“AI coding might have applications beyond winning competitions … It could do software grunt work, freeing up developers to work at a higher, or more abstract level, or it could help noncoders create simple programs.”   

The FTC filed a lawsuit to block Microsoft’s acquisition of Activision Blizzard, Amazon launches a customized scrollable shopping feed called Inspire, and DeepMind’s AlphaCode can solve coding challenges. MP3 Please SUBSCRIBE HERE. You can get an ad-free feed of Daily Tech Headlines for $3 a month here. A special thanks to all our supporters–without you,Continue reading "FTC Blocks Microsoft’s Activision Blizzard Acquisition – DTH"

AlphaCode te ayuda a programar, problemas para Microsoft en sus compras y Twitter te avisará si limita tus publicaciones.Puedes apoyar la realización de este programa con una suscripción. Más información por acáNoticias:-La Comisión Federal de Comercio de los Estados Unidos presentó una demanda para evitar la adquisición de Activision Blizzard.-Investigadores de DeepMind dentro de Alphabet publicaron un artículo en la revista Science, describiendo un sistema llamado AlphaCode, el cual es capaz de resolver desafíos generales de programación. -El fundador de FTX, Sam Bankman-Fried, dijo que testificará ante el Comité de Servicios Financieros de la Cámara este 13 de diciembre-De acuerdo con la nueva guía de la comisión de Bolsa y Valores de los Estados Unidos, las empresas que emiten valores deberán incluir el registro de posesión de activos de criptomonedas y la exposición al riesgo de quiebra de la bolsa de criptomonedas FTX en sus presentaciones públicas. -El CEO de Twitter, Elon Musk dijo que la compañía comenzará a notificar a los usuarios si el alcance de sus publicaciones ha sido limitadoAnálisis: ¿Qué alcance tienen mis publicaciones?¿Prefieres leer las noticias? ¡Suscríbete a mi newsletter y te llegarán todos los días!   Become a member at https://plus.acast.com/s/noticias-de-tecnologia-express. Hosted on Acast. See acast.com/privacy for more information.

Die Themen in den Wissensnachrichten:+++AlphaCode ist die erste Künstliche Intelligenz, die so gut programmiert wie Menschen +++ Vegane Fleischersatzprodukte enthalten oft nicht genug Nährstoffe +++ Wasserhanf ist durch die moderne Landwirtschaft zum Unkraut geworden +++ **********Weiterführende Quellen zu dieser Folge:Competition-level code generation with AlphaCode, Science, 9.12.2022Nutritional Composition and Estimated Iron and Zinc Bioavailability of Meat Substitutes Available on the Swedish Market, Nutrients 2022, 21.09.2022Rapid weed adaptation and range expansion in response to agriculture over the past two centuries, Science, 8.12.2022The Lancet Series on racism, xenophobia, discrimination, and health, Lancet, 8.12.2022Nutritional needs and mortality risk combine to shape foraging decisions in ants, Current Zoology, 12.11. 2022Discriminatory Attitudes Against the Unvaccinated During a Global Pandemic, Nature, 8.12.2022**********Ihr könnt uns auch auf diesen Kanälen folgen: Tiktok und Instagram.**********Weitere Wissensnachrichten zum Nachlesen: https://www.deutschlandfunknova.de/nachrichten

DeepMind developed AlphaCode which can write computer programs --- Send in a voice message: https://anchor.fm/tonyphoang/message

WAAIT Part 3: What individuals, humanity, and players in the game can ask themselves. Subscribe at: https://paid.retraice.com Details: AlphaCode; individuals — How much do I matter?; humanity — What are we doing again? Where are we headed?; players — How to win? Complete notes and video at: https://www.retraice.com/segments/re52 Air date: Wednesday, 16th Nov. 2022, 11 : 00 PM Eastern/US. 0:00:00 AlphaCode; 0:04:09 individuals — How much do I matter?; 0:12:31 humanity — What are we doing again? Where are we headed?; 0:14:29 players — How to win? Copyright: 2022 Retraice, Inc. https://retraice.com

Oriol Vinyals, who leads DeepMind's deep learning team, talks about AlphaCode, his group's code-writing language model, and DeepMind's winding road toward artificial general intelligence.

Ethan is known on Twitter as the edgiest person at MILA. We discuss all the gossips around scaling large language models in what will be later known as the Edward Snowden moment of Deep Learning. On his free time, Ethan is a Master's degree student at MILA in Montreal, and has published papers on out of distribution generalization and robustness generalization, accepted both as oral presentations and spotlight presentations at ICML and NeurIPS. Ethan has recently been thinking about scaling laws, both as an organizer and speaker for the 1st Neural Scaling Laws Workshop. Transcript: https://theinsideview.github.io/ethan Youtube: https://youtu.be/UPlv-lFWITI Michaël: https://twitter.com/MichaelTrazzi Ethan: https://twitter.com/ethancaballero Outline (00:00) highlights (00:50) who is Ethan, scaling laws T-shirts (02:30) scaling, upstream, downstream, alignment and AGI (05:58) AI timelines, AlphaCode, Math scaling, PaLM (07:56) Chinchilla scaling laws (11:22) limits of scaling, Copilot, generative coding, code data (15:50) Youtube scaling laws, constrative type thing (20:55) AGI race, funding, supercomputers (24:00) Scaling at Google (25:10) gossips, private research, GPT-4 (27:40) why Ethan was did not update on PaLM, hardware bottleneck (29:56) the fastest path, the best funding model for supercomputers (31:14) EA, OpenAI, Anthropics, publishing research, GPT-4 (33:45) a zillion language model startups from ex-Googlers (38:07) Ethan's journey in scaling, early days (40:08) making progress on an academic budget, scaling laws research (41:22) all alignment is inverse scaling problems (45:16) predicting scaling laws, useful ai alignment research (47:16) nitpicks aobut Ajeya Cotra's report, compute trends (50:45) optimism, conclusion on alignment

Patrocínio: Alphacode Aprenda a programar com a Alphacode com 10% de desconto! Utilize o cupom LOOPMATINAL no site https://www.ferasdatecnologia.com.br. -------------------------------- Sobre o Podcast O Loop Matinal é um podcast do Loop Infinito que traz as notícias mais importantes do mundo da tecnologia para quem não tem tempo de ler sites e blogs de tecnologia. Marcus Mendes apresenta um resumo rápido e conciso das notícias mais importantes, sempre com bom-humor e um toque de acidez. Confira as notícias das últimas 24h, e até amanhã! -------------------------------- Apoie o Loop Matinal! O Loop Matinal está no apoia.se/loopmatinal e no picpay.me/loopmatinal! Se você quiser ajudar a manter o podcast no ar, é só escolher a categoria que você preferir e definir seu apoio mensal. Obrigado em especial aos ouvintes Advogado Junio Araujo, Alexsandra Romio, Alisson Rocha, Anderson Barbosa, Anderson Cazarotti, Angelo Almiento, Arthur Givigir, Breno Farber, Caio Santos, Carolina Vieira, Christophe Trevisani, Claudio Souza, Dan Fujita, Daniel Ivasse, Daniel Cardoso, Diogo Silva, Edgard Contente, Edson  Pieczarka Jr, Fabian Umpierre, Fabio Brasileiro, Felipe, Francisco Neto, Frederico Souza, Gabriel Souza, Guilherme Santos, Henrique Orçati, Horacio Monteiro, Igor Antonio, Igor Silva, Ismael Cunha, Jeadilson Bezerra, Jorge Fleming, Jose Junior, Juliana Majikina, Juliano Cezar, Juliano Marcon, Leandro Bodo, Luis Carvalho, Luiz Mota, Marcus Coufal, Mauricio Junior, Messias Oliveira, Nilton Vivacqua, Otavio Tognolo, Paulo Sousa, Ricardo Mello, Ricardo Berjeaut, Ricardo Soares, Rickybell, Roberto Chiaratti, Rodrigo Rosa, Rodrigo Rezende, Samir da Converta Mais, Teresa Borges, Tiago Soares, Victor Souza, Vinícius Lima, Vinícius Ghise e Wilson Pimentel pelo apoio! -------------------------------- Xbox bate recorde de vendas: 
https://www.theverge.com/2022/4/25/23040875/xbox-series-x-s-sales-nintendo-switch-ps5-npd-march-2022 PS Plus reformulado deve ser lançado em 13 de junho: https://www.theverge.com/2022/4/22/23037384/sony-playstation-plus-new-tiers-launch-date Diablo Immortal chega ao iOS em junho: https://9to5mac.com/2022/04/25/diablo-immortal-arriving-on-ios-devices-in-june-features-cross-play-and-cross-progression/ Samsung lança o Galaxy M53 5G: https://tecnoblog.net/noticias/2022/04/25/galaxy-m53-5g-chega-com-camera-quadrupla-de-108-mp-e-tela-de-120-hz/ Anatel homologa o Galaxy S20 FE 5G: https://tecnoblog.net/noticias/2022/04/22/galaxy-s20-fe-5g-com-snapdragon-865-e-homologado-para-venda-no-brasil/ Vaza o Pixel Watch: https://www.androidcentral.com/wearables/google-pixel-watch-live-images-exclusive Asus lança monitor portátil: https://www.theverge.com/2022/4/25/23040654/asus-proart-display-pa147cdv-14-inch-secondary-monitor-duo-laptop Europa quer que big tech expliquem seus algoritmos: https://www.theverge.com/2022/4/23/23036976/eu-digital-services-act-finalized-deatils Amazon compra a GlowRoad: https://economictimes.indiatimes.com/tech/technology/amazon-acquires-reseller-platform-glowroad-to-bolster-social-commerce-ambitions/articleshow/90987418.cms Elon Musk compra o Twitter: 
https://www.prnewswire.com/news-releases/elon-musk-to-acquire-twitter-301532245.html Twitter testa mudanças na legendagem de vídeos: https://9to5mac.com/2022/04/22/twitter-cc-button-video-captions/ Twitter bane anúncios enganosos sobre mudança climática: https://www.theverge.com/2022/4/22/23037677/twitter-bans-climate-change-misinformation-ads Apple anuncia programa de trocas do Apple Watch Series 6: https://macmagazine.com.br/post/2022/04/22/apple-watch-series-6-tem-recall-por-tela-apagada/ Apple Watch pode ter conectividade via satélite: https://9to5mac.com/2022/04/24/gurman-apple-watch-could-feature-satellite-connectivity-in-a-future-model/ Apple já trabalha em iMac com chip M3: https://9to5mac.com/2022/04/24/gurman-imac-with-m3-chip-already-in-the-works-could-be-released-later-next-year/ Apple removerá apps abandonados da App Store: https://www.theverge.com/2022/4/23/23038870/apple-app-store-widely-remove-outdated-apps-developers?scrolla=5eb6d68b7fedc32c19ef33b4 -------------------------------- Site do Loop Matinal: http://www.loopmatinal.com Anuncie no Loop Matinal: comercial@loopinfinito.net Marcus Mendes: https://www.twitter.com/mvcmendes Loop Infinito: https://www.youtube.com/oloopinfinito

En este episodio contamos con un invitado especial Carlos Santana (DotCSV) que entiende bastante más que nosotros son inteligencia artificial. Para hablar del futuro de la programación con las revoluciones que ha traido este campo en el ultimo año o año y medio. Hablarémos de Github Copilot, de AlphaCode y de otras técnologias similares como Dall-E 2. --- Send in a voice message: https://podcasters.spotify.com/pod/show/thebigbranchtheory/message

Patrocínio: Alphacode Aprenda a programar com a Alphacode com 10% de desconto! Utilize o cupom LOOPMATINAL no site https://www.ferasdatecnologia.com.br. -------------------------------- Sobre o Podcast O Loop Matinal é um podcast do Loop Infinito que traz as notícias mais importantes do mundo da tecnologia para quem não tem tempo de ler sites e blogs de tecnologia. Marcus Mendes apresenta um resumo rápido e conciso das notícias mais importantes, sempre com bom-humor e um toque de acidez. Confira as notícias das últimas 24h, e até amanhã! -------------------------------- Apoie o Loop Matinal! O Loop Matinal está no apoia.se/loopmatinal e no picpay.me/loopmatinal! Se você quiser ajudar a manter o podcast no ar, é só escolher a categoria que você preferir e definir seu apoio mensal. Obrigado em especial aos ouvintes Advogado Junio Araujo, Alexsandra Romio, Alisson Rocha, Anderson Barbosa, Anderson Cazarotti, Angelo Almiento, Arthur Givigir, Breno Farber, Caio Santos, Carolina Vieira, Christophe Trevisani, Claudio Souza, Dan Fujita, Daniel Ivasse, Daniel Cardoso, Diogo Silva, Edgard Contente, Edson  Pieczarka Jr, Fabian Umpierre, Fabio Brasileiro, Felipe, Francisco Neto, Frederico Souza, Gabriel Souza, Guilherme Santos, Henrique Orçati, Horacio Monteiro, Igor Antonio, Igor Silva, Ismael Cunha, Jeadilson Bezerra, Jorge Fleming, Jose Junior, Juliana Majikina, Juliano Cezar, Juliano Marcon, Leandro Bodo, Luis Carvalho, Luiz Mota, Marcus Coufal, Mauricio Junior, Messias Oliveira, Nilton Vivacqua, Otavio Tognolo, Paulo Sousa, Ricardo Mello, Ricardo Berjeaut, Ricardo Soares, Rickybell, Roberto Chiaratti, Rodrigo Rosa, Rodrigo Rezende, Samir da Converta Mais, Teresa Borges, Tiago Soares, Victor Souza, Vinícius Lima, Vinícius Ghise e Wilson Pimentel pelo apoio! -------------------------------- CODA liderou ranking de steramings nos EUA: https://macmagazine.com.br/post/2022/04/18/coda-foi-o-titulo-de-streaming-mais-assistido-do-1o-trimestre-nos-eua/ Netflix terá série e jogo de Exploding Kittens: https://www.theverge.com/2022/4/18/23030345/netflix-exploding-kittens-mobile-game-tv-animated-series Procon-RJ não gostou de indicação de destino a motoristas da Uber: https://tecnoblog.net/noticias/2022/04/18/procon-carioca-notifica-uber-por-adiantar-destino-de-corridas-a-motoristas/ Bolsonaro quer obrigar WhatsApp a lançar Comunidades no Brasil: 
https://tecnoblog.net/noticias/2022/04/18/bolsonaro-promete-buscar-ceo-do-whatsapp-para-ter-comunidades-antes-das-eleicoes/ Whatsapp deixa mais pessoas ocultarem o “Visto por último” seletivamente: https://tecnoblog.net/noticias/2022/04/18/whatsapp-expande-recurso-que-oculta-visto-por-ultimo-para-certas-pessoas/ Elon Musk diz que painel do Twitter não será pago se ele comprar a empresa: https://www.cnbc.com/2022/04/18/musk-twitter-board-will-be-paid-nothing-if-he-acquires-the-company.html Tesla não permite mais a compra de carros após o fim do leasing: https://fortune.com/2022/04/18/tesla-rule-change-leases-car-purchases/ Microsoft comenta ausência de segundos no relógio do Windows 11: https://tecnoblog.net/noticias/2022/04/18/microsoft-explica-por-que-windows-11-nao-mostra-segundos-no-relogio/ Telegram ganha customização de sons de notificação: https://telegram.org/blog/notifications-bots#custom-notification-sounds Vazam moldes dos novos iPhones: https://macmagazine.com.br/post/2022/04/18/moldes-dos-iphones-14-mostram-novos-pares-de-modelos/ -------------------------------- Site do Loop Matinal: http://www.loopmatinal.com Anuncie no Loop Matinal: comercial@loopinfinito.net Marcus Mendes: https://www.twitter.com/mvcmendes Loop Infinito: https://www.youtube.com/oloopinfinito

Patrocínio: Alphacode Aprenda a programar com a Alphacode com 10% de desconto! Utilize o cupom LOOPMATINAL no site https://www.ferasdatecnologia.com.br. -------------------------------- Sobre o Podcast O Loop Matinal é um podcast do Loop Infinito que traz as notícias mais importantes do mundo da tecnologia para quem não tem tempo de ler sites e blogs de tecnologia. Marcus Mendes apresenta um resumo rápido e conciso das notícias mais importantes, sempre com bom-humor e um toque de acidez. Confira as notícias das últimas 24h, e até amanhã! -------------------------------- Apoie o Loop Matinal! O Loop Matinal está no apoia.se/loopmatinal e no picpay.me/loopmatinal! Se você quiser ajudar a manter o podcast no ar, é só escolher a categoria que você preferir e definir seu apoio mensal. Obrigado em especial aos ouvintes Advogado Junio Araujo, Alexsandra Romio, Alisson Rocha, Anderson Barbosa, Anderson Cazarotti, Angelo Almiento, Arthur Givigir, Breno Farber, Caio Santos, Carolina Vieira, Christophe Trevisani, Claudio Souza, Dan Fujita, Daniel Ivasse, Daniel Cardoso, Diogo Silva, Edgard Contente, Edson  Pieczarka Jr, Fabian Umpierre, Fabio Brasileiro, Felipe, Francisco Neto, Frederico Souza, Gabriel Souza, Guilherme Santos, Henrique Orçati, Horacio Monteiro, Igor Antonio, Igor Silva, Ismael Cunha, Jeadilson Bezerra, Jorge Fleming, Jose Junior, Juliana Majikina, Juliano Cezar, Juliano Marcon, Leandro Bodo, Luis Carvalho, Luiz Mota, Marcus Coufal, Mauricio Junior, Messias Oliveira, Nilton Vivacqua, Otavio Tognolo, Paulo Sousa, Ricardo Mello, Ricardo Berjeaut, Ricardo Soares, Rickybell, Roberto Chiaratti, Rodrigo Rosa, Rodrigo Rezende, Samir da Converta Mais, Teresa Borges, Tiago Soares, Victor Souza, Vinícius Lima, Vinícius Ghise e Wilson Pimentel pelo apoio! -------------------------------- Spotify testa feed no estilo TikTok: 
https://9to5mac.com/2022/04/08/spotify-testing-gif-like-videos/ Fãs de Anitta enganaram o algoritmo do Spotify: https://restofworld.org/2022/anitta-fans-spotify-brazil-global-chart/ Uber ganha botão para chamar a polícia no RJ: https://macmagazine.com.br/post/2022/04/08/rio-de-janeiro-uber-tera-botao-no-app-para-acionar-a-policia/ Amazon Prime ficará mais caro no Canadá: https://www.theverge.com/2022/4/8/23017323/amazon-prime-canada-price-hike-subscription-shopping-deals-shipping ProtonMail compra a SimpleLogin: https://9to5mac.com/2022/04/08/protonmail-acquires-simplelogin/ Facebook não permitirá mais compartilhamento abusivo de endereços pessoais: https://www.theverge.com/2022/4/10/23019046/meta-no-longer-allow-private-residential-address-doxxing-facebook-instagram-oversight-board Qualcomm fará chip dos Ray-Ban Stories 2: https://www.theinformation.com/articles/meta-platforms-is-struggling-to-develop-its-own-device-chips Elon Musk não fará parte do conselho do Twitter: https://twitter.com/paraga/status/1513354622466867201 Elon Musk pergunta se o Twitter está morrendo: https://www.bloomberg.com/news/articles/2022-04-09/musk-asks-is-twitter-dying-as-he-cites-bieber-s-quiet-account Elon Musk diz que assinantes do Twitter deveriam ganhar conta verificada: https://www.axios.com/elon-musk-suggests-twitter-blue-overhaul-a84c5035-7629-4b15-a137-e09aed3f085b.html Google confirma PiP no YouTube TV para iPhone: https://www.macrumors.com/2022/04/11/youtube-picture-in-picture-coming-soon/ iOS 16 mudará notificações: https://macmagazine.com.br/post/2022/04/11/ios-16-tera-melhorias-em-notificacoes-e-design-nao-mudara-diz-gurman/ -------------------------------- Site do Loop Matinal: http://www.loopmatinal.com Anuncie no Loop Matinal: comercial@loopinfinito.net Marcus Mendes: https://www.twitter.com/mvcmendes Loop Infinito: https://www.youtube.com/oloopinfinito

Patrocínio: Alphacode Aprenda a programar com a Alphacode com 10% de desconto! Utilize o cupom LOOPMATINAL no site https://www.ferasdatecnologia.com.br. -------------------------------- Sobre o Podcast O Loop Matinal é um podcast do Loop Infinito que traz as notícias mais importantes do mundo da tecnologia para quem não tem tempo de ler sites e blogs de tecnologia. Marcus Mendes apresenta um resumo rápido e conciso das notícias mais importantes, sempre com bom-humor e um toque de acidez. Confira as notícias das últimas 24h, e até amanhã! -------------------------------- Apoie o Loop Matinal! O Loop Matinal está no apoia.se/loopmatinal e no picpay.me/loopmatinal! Se você quiser ajudar a manter o podcast no ar, é só escolher a categoria que você preferir e definir seu apoio mensal. Obrigado em especial aos ouvintes Advogado Junio Araujo, Alexsandra Romio, Alisson Rocha, Anderson Barbosa, Anderson Cazarotti, Angelo Almiento, Arthur Givigir, Breno Farber, Caio Santos, Carolina Vieira, Christophe Trevisani, Claudio Souza, Dan Fujita, Daniel Ivasse, Daniel Cardoso, Diogo Silva, Edgard Contente, Edson  Pieczarka Jr, Fabian Umpierre, Fabio Brasileiro, Felipe, Francisco Neto, Frederico Souza, Gabriel Souza, Guilherme Santos, Henrique Orçati, Horacio Monteiro, Igor Antonio, Igor Silva, Ismael Cunha, Jeadilson Bezerra, Jorge Fleming, Jose Junior, Juliana Majikina, Juliano Cezar, Juliano Marcon, Leandro Bodo, Luis Carvalho, Luiz Mota, Marcus Coufal, Mauricio Junior, Messias Oliveira, Nilton Vivacqua, Otavio Tognolo, Paulo Sousa, Ricardo Mello, Ricardo Berjeaut, Ricardo Soares, Rickybell, Roberto Chiaratti, Rodrigo Rosa, Rodrigo Rezende, Samir da Converta Mais, Teresa Borges, Tiago Soares, Victor Souza, Vinícius Lima, Vinícius Ghise e Wilson Pimentel pelo apoio! -------------------------------- Amazon dá desconto em produtos Echo: https://amzn.to/3jllSoR YouTube da Samsung é hackeado: https://tecnoblog.net/noticias/2022/04/04/canal-da-samsung-brasil-no-youtube-e-hackeado-para-promover-criptomoedas/ Samsung mostra tv QD-OLED: https://www.theverge.com/2022/4/4/23009841/samsung-qd-oled-tv-s95b-preview Samsung anuncia TV fosca de parede: 
https://www.theverge.com/2022/4/4/23009799/samsung-the-frame-2022-preview-matte-display-artwork Samsung anuncia o Galaxy M33 5G: https://tecnoblog.net/noticias/2022/04/04/galaxy-m33-5g-traz-bateria-enorme-de-6-000-mah-e-camera-quadrupla-de-50-mp/ Fortnite levantou US$144M para a Ucrânia: 
https://www.theverge.com/2022/4/4/23009838/fortnite-ukraine-relief-fundraising-total Como ajudar as vítimas da guerra na Ucrânia: https://www.uol.com.br/ecoa/ultimas-noticias/2022/03/03/guerra-na-ucrania-onu-faz-apelo-para-ajuda-humanitaria-as-vitimas.htm Google oferece patinetes elétricos para atrair funcionários ao escritório: https://www.theverge.com/2022/4/4/23004667/google-unagi-electric-scooter-subscription-return-office Google terá delivery com drones em Dallas: https://www.engadget.com/alphabets-wing-drone-delivery-service-comes-to-texas-on-april-7th-120059178.html Elon Musk compra 9,2% do Twitter: https://www.theverge.com/2022/4/4/23009622/elon-musk-twitter-shares-free-speech Rede de Trump pede líder de tecnologia: https://www.reuters.com/technology/exclusive-two-key-tech-execs-quit-truth-social-after-troubled-app-launch-2022-04-04/ Apple segue cortando a fabricação de iPhones: https://9to5mac.com/2022/04/04/analysts-apple-to-keep-cutting-iphone-orders-services-now-key-differentiator/ Ming Chi Kuo diz que iPhones de 2024 terão Face ID sob a tela: https://macmagazine.com.br/post/2022/04/04/ming-chi-kuo-concorda-que-face-id-sob-a-tela-chegara-em-2024/ -------------------------------- Site do Loop Matinal: http://www.loopmatinal.com Anuncie no Loop Matinal: comercial@loopinfinito.net Marcus Mendes: https://www.twitter.com/mvcmendes Loop Infinito: https://www.youtube.com/oloopinfinito

Patrocínio: Alphacode Aprenda a programar com a Alphacode com 10% de desconto! Utilize o cupom LOOPMATINAL no site https://www.ferasdatecnologia.com.br. -------------------------------- Sobre o Podcast O Loop Matinal é um podcast do Loop Infinito que traz as notícias mais importantes do mundo da tecnologia para quem não tem tempo de ler sites e blogs de tecnologia. Marcus Mendes apresenta um resumo rápido e conciso das notícias mais importantes, sempre com bom-humor e um toque de acidez. Confira as notícias das últimas 24h, e até amanhã! -------------------------------- Apoie o Loop Matinal! O Loop Matinal está no apoia.se/loopmatinal e no picpay.me/loopmatinal! Se você quiser ajudar a manter o podcast no ar, é só escolher a categoria que você preferir e definir seu apoio mensal. Obrigado em especial aos ouvintes Advogado Junio Araujo, Alexsandra Romio, Alisson Rocha, Anderson Barbosa, Anderson Cazarotti, Angelo Almiento, Arthur Givigir, Breno Farber, Caio Santos, Carolina Vieira, Christophe Trevisani, Claudio Souza, Dan Fujita, Daniel Ivasse, Daniel Cardoso, Diogo Silva, Edgard Contente, Edson  Pieczarka Jr, Fabian Umpierre, Fabio Brasileiro, Felipe, Francisco Neto, Frederico Souza, Gabriel Souza, Guilherme Santos, Henrique Orçati, Horacio Monteiro, Igor Antonio, Igor Silva, Ismael Cunha, Jeadilson Bezerra, Jorge Fleming, Jose Junior, Juliana Majikina, Juliano Cezar, Juliano Marcon, Leandro Bodo, Luis Carvalho, Luiz Mota, Marcus Coufal, Mauricio Junior, Messias Oliveira, Nilton Vivacqua, Otavio Tognolo, Paulo Sousa, Ricardo Mello, Ricardo Berjeaut, Ricardo Soares, Rickybell, Roberto Chiaratti, Rodrigo Rosa, Rodrigo Rezende, Samir da Converta Mais, Teresa Borges, Tiago Soares, Victor Souza, Vinícius Lima, Vinícius Ghise e Wilson Pimentel pelo apoio! -------------------------------- Uber garante licença para operar em Londres: https://www.theverge.com/2022/3/26/22997671/uber-granted-30-month-license-operate-london-uk RJ lança app de entrega de comida: https://tecnoblog.net/noticias/2022/03/28/rival-do-ifood-app-de-entrega-sem-taxas-e-lancado-pela-prefeitura-do-rio/ Samsung lança o Galaxy A13 e A23 no Brasil: https://tecnoblog.net/noticias/2022/03/28/galaxy-a13-e-a23-chegam-ao-brasil-com-tela-grande-e-camera-de-50-mp/ Samsung lança o Smart Monitor M8: 
https://www.theverge.com/2022/3/28/22999709/samsung-m8-4k-32-inch-smart-monitor-features-price-airplay-tv-apple-studio-display-comparison Faturamento da Huawei caiu em 2021: https://www.cnbc.com/2022/03/28/huawei-annual-results-2022-revenue-declines-but-profit-surges.html Google aceitou não usar o termo guerra e posts sobre a guerra da Rússia: https://theintercept.com/2022/03/28/google-russia-ukraine-war-censorship/ Google Chrome corrige bugs de segurança: https://www.bleepingcomputer.com/news/security/emergency-google-chrome-update-fixes-zero-day-used-in-attacks/ WhatsApp para iOS aumentará limite de transferência de arquivos: https://9to5mac.com/2022/03/27/whatsapp-for-ios-could-soon-let-users-send-files-with-up-to-2gb/ Anatel homologa o novo iPhone SE: https://tecnoblog.net/noticias/2022/03/28/iphone-se-2022-e-homologado-pela-anatel-e-ja-pode-ser-vendido-no-brasil/ Apple corta produção do novo iPhone SE: 
https://asia.nikkei.com/Spotlight/Supply-Chain/Apple-to-cut-iPhone-AirPods-output-amid-Ukraine-war-uncertainty CODA ganha 3 Oscars: 
https://www.apple.com/newsroom/2022/03/apples-coda-wins-historic-oscar-for-best-picture-at-the-academy-awards/ iPad Pro pode ganhar MagSafe: https://macmagazine.com.br/post/2022/03/28/ipad-pro-com-magsafe-e-chip-m2-podera-chegar-no-fim-do-ano/ Câmera saltada do novo iPhone deve ser maior: https://www.macrumors.com/2022/03/27/iphone-14-pro-larger-camera-bump-48mp-system/?scrolla=5eb6d68b7fedc32c19ef33b4 Apple aumenta capacidade de fabricação de miniLED: https://9to5mac.com/2022/03/26/apple-boosting-supply-chain-capacity-for-macbook-pro-miniled-panels/ -------------------------------- Site do Loop Matinal: http://www.loopmatinal.com Anuncie no Loop Matinal: comercial@loopinfinito.net Marcus Mendes: https://www.twitter.com/mvcmendes Loop Infinito: https://www.youtube.com/oloopinfinito

Patrocínio: Alphacode Aprenda a programar com a Alphacode com 10% de desconto! Utilize o cupom LOOPMATINAL no site https://www.ferasdatecnologia.com.br. -------------------------------- Sobre o Podcast O Loop Matinal é um podcast do Loop Infinito que traz as notícias mais importantes do mundo da tecnologia para quem não tem tempo de ler sites e blogs de tecnologia. Marcus Mendes apresenta um resumo rápido e conciso das notícias mais importantes, sempre com bom-humor e um toque de acidez. Confira as notícias das últimas 24h, e até amanhã! -------------------------------- Apoie o Loop Matinal! O Loop Matinal está no apoia.se/loopmatinal e no picpay.me/loopmatinal! Se você quiser ajudar a manter o podcast no ar, é só escolher a categoria que você preferir e definir seu apoio mensal. Obrigado em especial aos ouvintes Advogado Junio Araujo, Alexsandra Romio, Alisson Rocha, Anderson Barbosa, Anderson Cazarotti, Angelo Almiento, Arthur Givigir, Breno Farber, Caio Santos, Carolina Vieira, Christophe Trevisani, Claudio Souza, Dan Fujita, Daniel Ivasse, Daniel Cardoso, Diogo Silva, Edgard Contente, Edson  Pieczarka Jr, Fabian Umpierre, Fabio Brasileiro, Felipe, Francisco Neto, Frederico Souza, Gabriel Souza, Guilherme Santos, Henrique Orçati, Horacio Monteiro, Igor Antonio, Igor Silva, Ismael Cunha, Jeadilson Bezerra, Jorge Fleming, Jose Junior, Juliana Majikina, Juliano Cezar, Juliano Marcon, Leandro Bodo, Luis Carvalho, Luiz Mota, Marcus Coufal, Mauricio Junior, Messias Oliveira, Nilton Vivacqua, Otavio Tognolo, Paulo Sousa, Ricardo Mello, Ricardo Berjeaut, Ricardo Soares, Rickybell, Roberto Chiaratti, Rodrigo Rosa, Rodrigo Rezende, Samir da Converta Mais, Teresa Borges, Tiago Soares, Victor Souza, Vinícius Lima, Vinícius Ghise e Wilson Pimentel pelo apoio! -------------------------------- Fortnite ganha ação de Doctor Strange: https://www.theverge.com/2022/3/20/22987308/fortnite-chapter-3-season-2-battle-pass-doctor-strange Epic doará lucro do Fortnite à Ucrânia: https://www.theverge.com/2022/3/21/22988901/fortnite-ukraine-relief Netflix publica teaser de Tekken: 
https://www.theverge.com/2022/3/19/22986995/tekken-bloodlines-anime-netflix-teaser-trailer-streaming Apple Music não consome dados da TIM: 
https://tecnoblog.net/noticias/2022/03/21/tim-oferece-apple-music-sem-descontar-da-franquia-e-de-graca-por-seis-meses/ Multilaser venderá drones da DJI no Brasil: https://tecnoblog.net/noticias/2022/03/18/multilaser-faz-acordo-com-dji-para-vender-drones-mini-e-mavic-no-brasil/ GM compra participação da SoftBank na Cruse: 
https://www.bloomberg.com/news/articles/2022-03-18/gm-buys-2-1-billion-softbank-stake-in-cruise-self-driving-unit Vimeo explica melhor mudanças na anuidade: https://vimeo.com/blog/post/improving-policy-on-video-bandwidth/ Google libera limpeza de histórico recente no Android: 
https://www.theverge.com/2022/3/18/22985668/google-android-app-delete-last-15-minutes-search-history?scrolla=5eb6d68b7fedc32c19ef33b4 WhatsApp Desktop ficará melhor: 
https://macmagazine.com.br/post/2022/03/21/whatsapp-desktop-tera-previas-de-links-listas-de-transmissao-e-mais/ Windows 11 ganha novo alerta de incompatibilidade: https://www.theverge.com/22988775/microsoft-windows-11-desktop-watermark-unsupported-hardware Novo iPad Air é meio mequetrefe: https://macmagazine.com.br/post/2022/03/21/usuarios-reclamam-da-qualidade-de-construcao-do-novo-ipad-air/ Apple Studio Display tem 64GB de espaço: https://macmagazine.com.br/post/2022/03/21/apple-studio-display-possui-64gb-de-armazenamento-interno/ Apple atualiza o Boot Camp com suporte ao Studio Display: https://9to5mac.com/2022/03/19/apple-updates-boot-camp-with-studio-display-drivers-for-windows-users/ Mac Studio pode oferecer upgrade de SSD: https://www.theverge.com/2022/3/19/22986705/mac-studio-teardown-potentially-upgradeable-ssd-storage-apple -------------------------------- Site do Loop Matinal: http://www.loopmatinal.com Anuncie no Loop Matinal: comercial@loopinfinito.net Marcus Mendes: https://www.twitter.com/mvcmendes Loop Infinito: https://www.youtube.com/oloopinfinito

ブカとオカでエルデンリング、磁石などについて話しました。以下の Show Notes は簡易版です。完全版はこちら。0:00 イントロ0:28 磁石トーク磁石ニュース「東芝がサマリウム系ボンド磁石、レアアース半減でもネオジム同等（日本クロステック、22/03/01）」対象のpaperコバルト先物価格推移　> 80 $/kg（22/03/01）14:23 C-S-H系高圧超伝導arXiv:2201.07686Ep. 9, Ep. 3024:10 脳オルガノイド卓球と自由エネルギー原理実験室内で培養した人の「ミニ脳」にゲームをプレイさせることに成功人工培養された脳細胞によるゲームプレイの仕組み 〜自由エネルギー原理について〜｜masa_kazama｜note幸せには｢推しが大事｣予防医学研究者が言う訳 via まにーさん脳の大統一理論 自由エネルギー原理とはなにか上記の本の詳細版→ 自由エネルギー原理入門: 知覚・行動・コミュニケーションの計算理論28:55 OpenAI と DeepMindA Neural Network Solves and Generates Mathematics ProblemsTransformer (OpenAI Codex)で数式を解く論文Competitive programming with AlphaCode嘘解法のススメ - てきとーな日記DeepMindのAlphaシリーズまとめ｜npaka｜noteディープマインドが天気予報で成果43:32 Jxiv機構報 第1551号：ＪＳＴのプレプリントサーバー「Ｊｘｉｖ（ジェイカイブ）」の運用開始46:20 宇宙飛行士候補者選抜試験の進捗石原式色覚異常検査表中川翔子、黒田有彩も応募した　13年ぶり宇宙飛行士公募に最多1563人、女性の割合20％52:39 ELDEN RING とオープンワールドゲームELDEN RING公式webpage>祝福なく、死にきれぬ死者たちよ　導きに従い、霧の海の先、狭間の地に向かいエルデンリングに見えよ　そして、エルデの王となるがよいタイでの広告 (YouTube)『ELDEN RING』Steamでやはり同時接続プレイヤー数1位獲得！75万人突破―『Fallout 4』『ウィッチャー3』超え現在（3/11は約70万人で2位）『エルデンリング』がついに40分以内にクリアされる。NPC イベント（未解決）ネフェリ・ルー、ケネス・ハイト、ゴストーク（情報サイト）「スカイリムおばあちゃん」が“脳卒中により『スカイリム』の遊び方を忘れた”と明かす。キリストとなるオープンワールド『I Am Jesus Christ』ベータテスト参加者募集開始。ジャパニーズRPG『昭和米国物語』発表、日本語対応。高い城の男※収録後、霜踏みが弱体化、ネフェリ・ルーらのイベント修正2022.03.17 - アップデートファイル配信のお知らせ - ELDEN RING1:40:12 Nier シリーズ、なろう、カルチャーラジオ大人気アクションRPGゲーム『NieR:Automata』（ニーア オートマタ）TVアニメ化決定NieR AutomataNieR ReplicantSINoALICENieR Re[in]carnationニーアシリーズについては Ep. 21 でも話してます。Nishika 小説家になろう ブクマ数予測コンペ振り返り｜baukmilzeカルチャーラジオ 芸術その魅力 - NHKお知らせ出演して頂ける方、感想などお待ちしております。 #interaxion

Patrocínio: Alphacode Aprenda a programar com a Alphacode com 10% de desconto! Utilize o cupom LOOPMATINAL no site https://www.ferasdatecnologia.com.br. -------------------------------- Sobre o Podcast O Loop Matinal é um podcast do Loop Infinito que traz as notícias mais importantes do mundo da tecnologia para quem não tem tempo de ler sites e blogs de tecnologia. Marcus Mendes apresenta um resumo rápido e conciso das notícias mais importantes, sempre com bom-humor e um toque de acidez. Confira as notícias das últimas 24h, e até amanhã! -------------------------------- Apoie o Loop Matinal! O Loop Matinal está no apoia.se/loopmatinal e no picpay.me/loopmatinal! Se você quiser ajudar a manter o podcast no ar, é só escolher a categoria que você preferir e definir seu apoio mensal. Obrigado em especial aos ouvintes Advogado Junio Araujo, Alexsandra Romio, Alisson Rocha, Anderson Barbosa, Anderson Cazarotti, Angelo Almiento, Arthur Givigir, Breno Farber, Caio Santos, Carolina Vieira, Christophe Trevisani, Claudio Souza, Dan Fujita, Daniel Ivasse, Daniel Cardoso, Diogo Silva, Edgard Contente, Edson  Pieczarka Jr, Fabian Umpierre, Fabio Brasileiro, Felipe, Francisco Neto, Frederico Souza, Gabriel Souza, Guilherme Santos, Henrique Orçati, Horacio Monteiro, Igor Antonio, Igor Silva, Ismael Cunha, Jeadilson Bezerra, Jorge Fleming, Jose Junior, Juliana Majikina, Juliano Cezar, Juliano Marcon, Leandro Bodo, Luis Carvalho, Luiz Mota, Marcus Coufal, Mauricio Junior, Messias Oliveira, Nilton Vivacqua, Otavio Tognolo, Paulo Sousa, Ricardo Mello, Ricardo Berjeaut, Ricardo Soares, Rickybell, Roberto Chiaratti, Rodrigo Rosa, Rodrigo Rezende, Samir da Converta Mais, Teresa Borges, Tiago Soares, Victor Souza, Vinícius Lima, Vinícius Ghise e Wilson Pimentel pelo apoio! -------------------------------- HBO Max e Discovery+ serão um app só: 
https://www.hollywoodreporter.com/business/business-news/discovery-plus-hbo-max-bundled-warnermedia-merger-streaming-1235107837/ Ubisoft sofre ataque hacker: https://www.theverge.com/2022/3/11/22972768/ubisoft-cyber-security-incident-hack Nintendo Switch lidera vendas de consoles: https://www.theverge.com/2022/3/12/22974056/nintendo-switch-top-selling-console-february-2022 Positivo prestará assistência para laptops da HP, Dell e mais: https://tecnoblog.net/noticias/2022/03/11/positivo-vai-consertar-pcs-da-lenovo-dell-hp-e-outras-marcas-em-todo-o-brasil/ Brasil pode taxar streaming: https://tecnoblog.net/noticias/2022/03/11/projeto-de-lei-quer-taxa-para-netflix-disney-hbo-max-e-mais-streamings/ Google combate a PL das Fake News: https://blog.google/intl/pt-br/novidades/iniciativas/PL2630/ Anatel homologa o Poco M3 Pro: https://tecnoblog.net/noticias/2022/03/11/poco-m4-pro-4g-com-camera-tripla-de-64-mp-e-aprovado-pela-anatel/ Anatel homolog o Galaxy A73 5G: https://tecnoblog.net/noticias/2022/03/11/galaxy-a73-5g-e-aprovado-pela-anatel-e-pode-ter-camera-de-108-mp/ Samsung marca evento para 17/3: https://www.theverge.com/2022/3/13/22975452/samsung-galaxy-awesome-unpacked-a-series-event-march-17 Uber aumenta preços nos EUA: 
https://www.cnbc.com/2022/03/11/uber-adds-fuel-surcharge-because-of-high-gas-prices.html Russia bane o Instagram: https://www.theverge.com/2022/3/14/22976603/russia-bans-instagram-facebook-meta-call-to-violence Facebook não permitirá pedir pelo assassinato de Putin: https://www.bloomberg.com/news/articles/2022-03-14/facebook-parent-says-users-can-t-post-calls-to-assassinate-putin Facebook só permitira promover violência contra russos na Ucrânia: http://www.techmeme.com/220311/p27#a220311p27 Twitter muda comportamento da timeline outra vez: https://twitter.com/TwitterSupport/status/1503443926258180106 Lives do Instagram ganham moderação: https://macmagazine.com.br/post/2022/03/11/instagram-ganha-moderacao-de-comentarios-em-lives/ Relógios inteligentes estão vendendo mais: https://www.counterpointresearch.com/global-smartwatch-market-2021/ Apple libera o iOS 15.4: https://www.theverge.com/2022/3/14/22976606/ios-15-4-mask-compatible-face-id-emoji-tap-to-pay-airtags-stalking-update-release-date-features iPhone 14 pode manter chip da linha 13: 
https://9to5mac.com/2022/03/13/kuo-a16-iphone-14-pro-models/ -------------------------------- Site do Loop Matinal: http://www.loopmatinal.com Anuncie no Loop Matinal: comercial@loopinfinito.net Marcus Mendes: https://www.twitter.com/mvcmendes Loop Infinito: https://www.youtube.com/oloopinfinito

Patrocínio: Alphacode Ganhe um desconto exclusivo para fazer seu aplicativo Android ou iOS com a Alphacode! Acesse https://www.alphacode.com.br. -------------------------------- Sobre o Podcast O Loop Matinal é um podcast do Loop Infinito que traz as notícias mais importantes do mundo da tecnologia para quem não tem tempo de ler sites e blogs de tecnologia. Marcus Mendes apresenta um resumo rápido e conciso das notícias mais importantes, sempre com bom-humor e um toque de acidez. Confira as notícias das últimas 24h, e até amanhã! -------------------------------- Apoie o Loop Matinal! O Loop Matinal está no apoia.se/loopmatinal e no picpay.me/loopmatinal! Se você quiser ajudar a manter o podcast no ar, é só escolher a categoria que você preferir e definir seu apoio mensal. Obrigado em especial aos ouvintes Advogado Junio Araujo, Alexsandra Romio, Alisson Rocha, Anderson Barbosa, Anderson Cazarotti, Angelo Almiento, Arthur Givigir, Breno Farber, Caio Santos, Carolina Vieira, Christophe Trevisani, Claudio Souza, Dan Fujita, Daniel Ivasse, Daniel Cardoso, Diogo Silva, Edgard Contente, Edson  Pieczarka Jr, Fabian Umpierre, Fabio Brasileiro, Felipe, Francisco Neto, Frederico Souza, Gabriel Souza, Guilherme Santos, Henrique Orçati, Horacio Monteiro, Igor Antonio, Igor Silva, Ismael Cunha, Jeadilson Bezerra, Jorge Fleming, Jose Junior, Juliana Majikina, Juliano Cezar, Juliano Marcon, Leandro Bodo, Luis Carvalho, Luiz Mota, Marcus Coufal, Mauricio Junior, Messias Oliveira, Nilton Vivacqua, Otavio Tognolo, Paulo Sousa, Ricardo Mello, Ricardo Berjeaut, Ricardo Soares, Rickybell, Roberto Chiaratti, Rodrigo Rosa, Rodrigo Rezende, Samir da Converta Mais, Teresa Borges, Tiago Soares, Victor Souza, Vinícius Lima, Vinícius Ghise e Wilson Pimentel pelo apoio! -------------------------------- Receita libera software do IR 2022: https://macmagazine.com.br/post/2022/03/07/receita-federal-libera-software-do-imposto-de-renda-2022-veja-como-baixar/ Amazon dá até 70% de descontos em produtos no Brasil: https://amzn.to/3HLhxot Anatel homologa o Moto G22: https://tecnoblog.net/noticias/2022/03/07/moto-g22-com-android-12-e-tela-de-90-hz-e-homologado-pela-anatel/ Samsung confirma roubo de código do Galaxy: https://www.bleepingcomputer.com/news/security/hackers-leak-190gb-of-alleged-samsung-data-source-code/ Hackers da Nvidia querem fim de trava de mineração em GPUs: https://arstechnica.com/information-technology/2022/03/cybercriminals-who-breached-nvidia-issue-one-of-the-most-unusual-demands-ever Roubo de dados Nvidia está sendo usado em novos golpes: https://www.bleepingcomputer.com/news/security/malware-now-using-nvidias-stolen-code-signing-certificates/ Netflix suspende operação na Rússia: https://variety.com/2022/digital/news/netflix-suspends-service-russia-ukraine-invasion-1235197390/ Visa e MasterCard suspendem operações na Rússia: https://www.bloomberg.com/news/articles/2022-03-05/visa-suspends-all-russia-operations-l0eegccn Blizzard e Epic suspendem vendas na Rússia: https://www.engadget.com/activision-blizzard-epic-games-pause-game-sales-russia-201856440.html Russia perde parte de acesso à internet: https://www.theverge.com/2022/3/5/22962822/internet-backbone-provider-cogent-shuts-off-service-russia TikTok suspende uploads na Rússia https://www.bloomberg.com/news/articles/2022-03-06/tiktok-says-it-is-suspending-livestreaming-in-russia WhatsApp terá enquetes: https://9to5mac.com/2022/03/06/whatsapp-for-ios-polls-group-chat/ Nintendo Switch Online para iOS ganha redesenho: https://9to5mac.com/2022/03/07/nintendo-switch-online-app-ios/ Nike publica teaser de uniforme do AFC Richmond: https://twitter.com/Nike/status/1500864007800037382 Loop Infinito: Peek Performance: https://www.youtube.com/watch?v=dmGXIW9_oEk -------------------------------- Site do Loop Matinal: http://www.loopmatinal.com Anuncie no Loop Matinal: comercial@loopinfinito.net Marcus Mendes: https://www.twitter.com/mvcmendes Loop Infinito: https://www.youtube.com/oloopinfinito

An interview with the creators of AlphaCode! Paper review video here: https://youtu.be/s9UAOmyah1A OUTLINE: 0:00 - Intro 1:10 - Media Reception 5:10 - How did the project go from start to finish? 9:15 - Does the model understand its own code? 14:45 - Are there plans to reduce the number of samples? 16:15 - Could one do smarter filtering of samples? 18:55 - How crucial are the public test cases? 21:55 - Could we imagine an adversarial method? 24:45 - How are coding problems even made? 27:40 - Does AlphaCode evaluate a solution's asymptotic complexity? 33:15 - Are our sampling procedures inappropriate for diversity? 36:30 - Are all generated solutions as instructive as the example? 41:30 - How are synthetic examples created during training? 42:30 - What were high and low points during this research? 45:25 - What was the most valid criticism after publication? 47:40 - What are applications in the real world? 51:00 - Where do we go from here? Paper: https://storage.googleapis.com/deepmi... Code: https://github.com/deepmind/code_cont... Abstract: Programming is a powerful and ubiquitous problem-solving tool. Developing systems that can assist programmers or even generate programs independently could make programming more productive and accessible, yet so far incorporating innovations in AI has proven challenging. Recent large-scale language models have demonstrated an impressive ability to generate code, and are now able to complete simple programming tasks. However, these models still perform poorly when evaluated on more complex, unseen problems that require problem-solving skills beyond simply translating instructions into code. For example, competitive programming problems which require an understanding of algorithms and complex natural language remain extremely challenging. To address this gap, we introduce AlphaCode, a system for code generation that can create novel solutions to these problems that require deeper reasoning. Evaluated on recent programming competitions on the Codeforces platform, AlphaCode achieved on average a ranking of top 54.3% in programming competitions with more than 5,000 participants. We found that three key components were critical to achieve good and reliable performance: (1) an extensive and clean competitive programming dataset for training and evaluation, (2) large and efficient-to-sample transformer-based architectures, and (3) large-scale model sampling to explore the search space, followed by filtering based on program behavior to a small set of submissions. Authors: Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d'Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J. Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu and Oriol Vinyals Links: Merch: store.ykilcher.com TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://discord.gg/4H8xxDF BitChute: https://www.bitchute.com/channel/yann... LinkedIn: https://www.linkedin.com/in/ykilcher BiliBili: https://space.bilibili.com/2017636191 If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://www.subscribestar.com/yannick... Patreon: https://www.patreon.com/yannickilcher

AI-oppfinnelsene har kommet som perler på en snor de seneste årene, men en yrkesgruppe har derimot ikke fått mange oppgaver automatisert av kunstig intelligens: Programmerere. Det endrer seg nå. I starten av februar lanserte DeepMind algoritmen AlphaCode. AlphaCode kan sammenlignes med Google Translate for programkode, men isteden for å oversette mellom to naturlig språk, som norsk og engelsk, kan AlphaCode «oversette» fra en problembeskrivelse til en programkode. I simulerte programmeringskonkurranser AlphaCode det bedre enn 41% av alle deltagerne. Selv om dette var langt unna å vinne, som betyr programmerere har trygge jobber enn så lenge, visere det mulighetene. Støtten programmerere og utviklere får med kunstig intelligens vil endre seg drastisk de neste årene.

#ai #alphacode #deepmind AlphaCode is an automated system that can solve competitive programing exercises. The authors found an interesting combination of language models, large-scale sampling, and clever techniques to filter and subsequently cluster the resulting programs, which lets the system perform on the level of an average competitor in real competitions. In this video, we take a deep dive into AlphaCode's design, architecture, and experimental evaluation. The paper is very well structured and the empirical results are super interesting! OUTLINE: 0:00 - Intro 2:10 - Paper Overview 3:30 - An example problem from competitive programming 8:00 - AlphaCode system overview 14:00 - Filtering out wrong solutions 17:15 - Clustering equivalent generated programs 21:50 - Model configurations & engineering choices 24:30 - Adding privileged information to the input & more tricks 28:15 - Experimental Results (very interesting!) Paper: https://storage.googleapis.com/deepmi... Code: https://github.com/deepmind/code_cont... Abstract: Programming is a powerful and ubiquitous problem-solving tool. Developing systems that can assist programmers or even generate programs independently could make programming more productive and accessible, yet so far incorporating innovations in AI has proven challenging. Recent large-scale language models have demonstrated an impressive ability to generate code, and are now able to complete simple programming tasks. However, these models still perform poorly when evaluated on more complex, unseen problems that require problem-solving skills beyond simply translating instructions into code. For example, competitive programming problems which require an understanding of algorithms and complex natural language remain extremely challenging. To address this gap, we introduce AlphaCode, a system for code generation that can create novel solutions to these problems that require deeper reasoning. Evaluated on recent programming competitions on the Codeforces platform, AlphaCode achieved on average a ranking of top 54.3% in programming competitions with more than 5,000 participants. We found that three key components were critical to achieve good and reliable performance: (1) an extensive and clean competitive programming dataset for training and evaluation, (2) large and efficient-to-sample transformer-based architectures, and (3) large-scale model sampling to explore the search space, followed by filtering based on program behavior to a small set of submissions. Authors: Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d'Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J. Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu and Oriol Vinyals Links: Merch: store.ykilcher.com TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://discord.gg/4H8xxDF BitChute: https://www.bitchute.com/channel/yann... LinkedIn: https://www.linkedin.com/in/ykilcher BiliBili: https://space.bilibili.com/2017636191 If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://www.subscribestar.com/yannick... Patreon: https://www.patreon.com/yannickilcher Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq

Patrocínio: Alphacode Ganhe um desconto exclusivo para fazer seu aplicativo Android ou iOS com a Alphacode! Acesse https://www.alphacode.com.br. -------------------------------- Sobre o Podcast O Loop Matinal é um podcast do Loop Infinito que traz as notícias mais importantes do mundo da tecnologia para quem não tem tempo de ler sites e blogs de tecnologia. Marcus Mendes apresenta um resumo rápido e conciso das notícias mais importantes, sempre com bom-humor e um toque de acidez. Confira as notícias das últimas 24h, e até amanhã! -------------------------------- Apoie o Loop Matinal! O Loop Matinal está no apoia.se/loopmatinal e no picpay.me/loopmatinal! Se você quiser ajudar a manter o podcast no ar, é só escolher a categoria que você preferir e definir seu apoio mensal. Obrigado em especial aos ouvintes Advogado Junio Araujo, Alexsandra Romio, Alisson Rocha, Anderson Barbosa, Anderson Cazarotti, Angelo Almiento, Arthur Givigir, Breno Farber, Caio Santos, Carolina Vieira, Christophe Trevisani, Claudio Souza, Dan Fujita, Daniel Ivasse, Daniel Cardoso, Diogo Silva, Edgard Contente, Edson  Pieczarka Jr, Fabian Umpierre, Fabio Brasileiro, Felipe, Francisco Neto, Frederico Souza, Gabriel Souza, Guilherme Santos, Henrique Orçati, Horacio Monteiro, Igor Antonio, Igor Silva, Ismael Cunha, Jeadilson Bezerra, Jorge Fleming, Jose Junior, Juliana Majikina, Juliano Cezar, Juliano Marcon, Leandro Bodo, Luis Carvalho, Luiz Mota, Marcus Coufal, Mauricio Junior, Messias Oliveira, Nilton Vivacqua, Otavio Tognolo, Paulo Sousa, Ricardo Mello, Ricardo Berjeaut, Ricardo Soares, Rickybell, Roberto Chiaratti, Rodrigo Rosa, Rodrigo Rezende, Samir da Converta Mais, Teresa Borges, Tiago Soares, Victor Souza, Vinícius Lima, Vinícius Ghise e Wilson Pimentel pelo apoio! -------------------------------- Discord muda termos de uso: 
https://www.theverge.com/2022/2/25/22950432/discord-new-privacy-policy-community-guidelines Telegram remove canais a mando do STF: https://tecnoblog.net/noticias/2022/02/28/telegram-obedece-stf-e-apaga-canais-bolsonaristas-para-evitar-bloqueio-no-brasil/ EUA anunciam sanções de chips à Rússia: https://tecnoblog.net/noticias/2022/02/25/eua-anunciam-sancoes-em-chips-pcs-e-lasers-para-limitar-poder-da-russia/ EUA e Europa bloqueiam alguns bancos russos: https://www.theverge.com/2022/2/26/22949156/russia-expelled-swift-ukraine-sanctions Russos perdem Apple Pay e Google Pay: https://www.theverge.com/2022/2/26/22952191/russian-bank-customers-apple-pay-google-pay-financial-sanctions-ukraine Facebook remove rede russa de desinformação: https://www.theverge.com/2022/2/28/22954451/facebook-twitter-remove-misinformation-network-russian-propaganda-ukraine-invasion Facebook limita uso de plataformas a mídias estatais russas: https://www.theverge.com/2022/2/27/22953790/facebook-restricts-access-russian-state-controlled-media-ukraine Facebook se recusou a parar de checar fatos na Rússia: https://www.theverge.com/2022/2/25/22950874/russia-facebook-blocked-roskomnadzor-media-censorship?scrolla=5eb6d68b7fedc32c19ef33b4 Facebook barra anúncios de mídias estatais russas: https://www.reuters.com/technology/meta-bar-russian-state-media-running-ads-monetizing-platform-2022-02-26/ Google barra anúncios de mídias estatais russas: https://www.reuters.com/technology/youtube-blocks-rt-other-russian-channels-generating-revenue-2022-02-26/ YouTube desativa monetização de canais russos: https://www.theverge.com/2022/2/26/22952439/youtube-bans-ads-rt-russia-channels-google-ukraine Rússia ordena reverter restrições no YouTube: https://www.reuters.com/world/europe/russia-demands-google-restore-access-its-media-youtube-channels-ukraine-2022-02-27/ Google Maps perde trânsito em tempo real na Ucrânia: https://www.theverge.com/2022/2/28/22954426/google-disables-maps-traffic-data-in-ukraine-to-protect-citizens Google Maps permitiu confirmar invasão da Ucrânia antes da imprensa: 
https://www.washingtonpost.com/technology/2022/02/25/google-maps-ukraine-invasion/ Twitter pausa anúncios na Ucrânia: https://www.theverge.com/2022/2/26/22952128/twitter-pauses-ads-ukraine-russia-conflict Twitter pausa recomendações na Ucrânia: https://www.engadget.com/twitter-is-pausing-ads-and-recommendations-in-ukraine-and-russia-004617413.html Russia bloqueia o Twitter: https://www.theverge.com/2022/2/26/22952006/russia-block-twitter-ukraine-invasion-censorship-putin Twitter ganha customização de alerta de conteúdo: https://www.theverge.com/2022/2/25/22951334/twitter-sensitive-content-warning-individual-tweet-update-ios-android-web Meta desiste de fazer o próprio sistema operacional imersivo: 
https://9to5mac.com/2022/02/25/meta-disbands-ar-vr-headset-os-team-after-denying-it-would/ Samsung anuncia o Galaxy Book 2 Pro e 360: https://tecnoblog.net/noticias/2022/02/27/galaxy-book-2-pro-e-pro-360-sao-lancados-com-i7-de-12a-geracao-e-tela-amoled/ Lenovo lança muitos notebooks, híbridos e tablets: https://www.xda-developers.com/lenovo-ideapad-mwc-2022/ Nvidia confirma incidente de segurança: 
https://www.bloomberg.com/news/articles/2022-02-25/nvidia-is-investigating-cyber-attack-but-business-uninterrupted Mineradores de criptomoeda sofrem ataque: https://www.theverge.com/2022/2/24/22949480/nvidia-lhr-crypto-ethereum-mining-graphics-cards-tool-malware Apple patenteia teclado com Mac integrado: https://9to5mac.com/2022/02/25/apple-patents-magic-keyboard-with-integrated-mac-inside/ Apple Watch Series 8 deve ter acompanhamento mais preciso de exercícios: https://9to5mac.com/2022/02/27/apple-watch-series-8-features-activity-tracking-report/ -------------------------------- Site do Loop Matinal: http://www.loopmatinal.com Anuncie no Loop Matinal: comercial@loopinfinito.net Marcus Mendes: https://www.twitter.com/mvcmendes Loop Infinito: https://www.youtube.com/oloopinfinito

Sejam bem-vindos ao milésimo quingentésimo sexagésimo oitavo Spin de Notícias, o seu giro diário de informações científicas... em escala sub-atômica. E nesse Spin de Notícias falaremos sobre...Inteligência Artificial! *Este episódio, assim como tantos outros projetos vindouros, só foi possível por conta do Patronato do SciCast. Se você quiser mais episódios assim, contribua conosco!*

Andy and Dave discuss the latest in AI news and research, starting with the Aircrew Labor In-Cockpit Automation System (ALIAS) program from DARPA, which flew a UH-60A Black Hawk autonomously and without pilots on board, to include autonomous (simulated) obstacle avoidance [1:05]. Another DARPA program, Robotic Autonomy in Complex Environments with Resiliency (RACER) entered its first phase, focused on high-speed autonomous driving in unstructured environments, such as off-road terrain [2:39]. The National Science Board releases its State of U.S. Science and Engineering 2022 report, which shows the U.S. continues to lose its leadership position in global science and engineering [4:30]. The Undersecretary of Defense for Research and Engineering, Heidi Shyu, formally releases its technology priorities, 14 areas grouped into three categories: seed areas, effective adoption areas, and defense-specific areas [6:31]. In research, OpenAI creates InstructGPT in an attempt to align language models to follow human instructions better, resulting in a model with 100x fewer parameters than GPT-3 and provided a user-favored output 70% of the time, though still suffering from toxic output [9:37]. DeepMind releases AlphaCode, which has succeeded in programming competitions with an average ranking in the top 54% across 10 contests with more than 5,000 participants each though it approaches the problem through more of a brute-force approach [14:42]. DeepMind and the EPFL's Swiss Plasma Center also announce they have used reinforcement learning algorithms to control nuclear fusion (commanding the full set of control coils of a tokamak magnetic controller). Venture City publishes Timelapse of AI (2028 – 3000+), imagining how the next 1,000 years will play out for AI and the human race [18:25]. And finally, with the Russia-Ukraine conflict continuing to evolve, CNA's Russia Program experts Sam Bendett and Jeff Edmonds return to discuss what Russia has in its inventory when it comes to autonomy and how they might use it in this conflict, wrapping up insights from their recent paper on Russian Military Autonomy in a Ukraine Conflict [22:52]. Listener Note: The interview with Sam Bendett and Jeff Edmonds was recorded on Tuesday, February 22 at 1 pm. At the time of recording, Russia had not yet launched a full-scale invasion of Ukraine. https://www.cna.org/news/AI-Podcast  

Sejam bem-vindos ao milésimo quingentésimo sexagésimo oitavo Spin de Notícias, o seu giro diário de informações científicas... em escala sub-atômica. E nesse Spin de Notícias falaremos sobre...Inteligência Artificial! *Este episódio, assim como tantos outros projetos vindouros, só foi possível por conta do Patronato do SciCast. Se você quiser mais episódios assim, contribua conosco!*

L'affaire « Bitfinex » ou l'histoire de la plus grande saisie financière jamais réalisée.. On vous en parle dans l'épisode #16 de Digital Room ! Cette semaine, on parle aussi de : AlphaCode : l'IA qui rivalise avec les meilleurs programmeurs Brand loyalty : quand la crise rebat les cartes de la fidélité AssangeDAO : un NFT pour libérer Julian Assange ! Drop Servicing : Quand les influenceurs flirtent avec l'arnaque Retrouvez tous les épisodes sur : https://ladigitalroom.com Et comme toujours, si vous aimez ce que vous entendez, surtout n'hésitez pas à vous abonner et à le partager autour de vous :) --------- Powered by : http://agencepush.com --- Send in a voice message: https://anchor.fm/digitalroom/message

Patrocínio: Alphacode Ganhe um desconto exclusivo para fazer seu aplicativo Android ou iOS com a Alphacode! Acesse https://www.alphacode.com.br. -------------------------------- Sobre o Podcast O Loop Matinal é um podcast do Loop Infinito que traz as notícias mais importantes do mundo da tecnologia para quem não tem tempo de ler sites e blogs de tecnologia. Marcus Mendes apresenta um resumo rápido e conciso das notícias mais importantes, sempre com bom-humor e um toque de acidez. Confira as notícias das últimas 24h, e até amanhã! -------------------------------- Apoie o Loop Matinal! O Loop Matinal está no apoia.se/loopmatinal e no picpay.me/loopmatinal! Se você quiser ajudar a manter o podcast no ar, é só escolher a categoria que você preferir e definir seu apoio mensal. Obrigado em especial aos ouvintes Advogado Junio Araujo, Alexsandra Romio, Alisson Rocha, Anderson Barbosa, Anderson Cazarotti, Angelo Almiento, Arthur Givigir, Breno Farber, Caio Santos, Carolina Vieira, Christophe Trevisani, Claudio Souza, Dan Fujita, Daniel Ivasse, Daniel Cardoso, Diogo Silva, Edgard Contente, Edson  Pieczarka Jr, Fabian Umpierre, Fabio Brasileiro, Felipe, Francisco Neto, Frederico Souza, Gabriel Souza, Guilherme Santos, Henrique Orçati, Horacio Monteiro, Igor Antonio, Igor Silva, Ismael Cunha, Jeadilson Bezerra, Jorge Fleming, Jose Junior, Juliana Majikina, Juliano Cezar, Juliano Marcon, Leandro Bodo, Luis Carvalho, Luiz Mota, Marcus Coufal, Mauricio Junior, Messias Oliveira, Nilton Vivacqua, Otavio Tognolo, Paulo Sousa, Ricardo Mello, Ricardo Berjeaut, Ricardo Soares, Rickybell, Roberto Chiaratti, Rodrigo Rosa, Rodrigo Rezende, Samir da Converta Mais, Teresa Borges, Tiago Soares, Victor Souza, Vinícius Lima, Vinícius Ghise e Wilson Pimentel pelo apoio! -------------------------------- Capcom confirma Street Fighter 6: https://www.youtube.com/watch?v=SwPzuBj01AM B2W sofre suposto ataque hacker: https://tecnoblog.net/noticias/2022/02/21/americanas-e-submarino-sairam-do-ar-ha-3-dias-suspeita-e-de-ataque-hacker/ OpenSea sofre ataque hacker: https://www.coindesk.com/business/2022/02/20/opensea-investigating-exploit-rumors-as-users-complain-of-missing-nfts/ Funcionários da Salesforce se opõem a projeto com NFTs: 
https://www.theverge.com/2022/2/18/22941223/salesforce-nft-cloud-employee-protest-open-letter Samsung tira carregador da caixa do Galaxy Tab S8: https://tecnoblog.net/noticias/2022/02/21/samsung-vende-galaxy-tab-s8-sem-carregador-nos-eua-ipad-vem-com-acessorio/ Vaza o Motorola Frontier: https://tecnoblog.net/noticias/2022/02/18/motorola-frontier-tera-camera-com-duas-protuberancias-para-sensor-de-194-mp/ YouTube ganha sinalização de live igual ao TikTok: https://www.theverge.com/2022/2/21/22944111/youtube-live-rings-tiktok-instagram Truth Social é lançada na App Store americana: https://www.theverge.com/2022/2/21/22944179/truth-social-launch-ios-donald-trump-twitter-platform Snapchat terá compartilhamento de localização em tempo real: https://www.theverge.com/2022/2/18/22937338/snapchat-live-location-sharing Facebook segue perdendo anunciantes: 
https://www.wsj.com/articles/facebook-apple-google-advertising-privacy-changes-11645199877?mod=djemalertNEWS Mark Gurman fala sobre o Mac mini high-end: https://macmagazine.com.br/post/2022/02/21/mac-pro-mini-tera-desempenho-de-quatro-chips-m1-max-diz-gurman/ Mark Gurman diz que Apple fará mais de um evento para anunciar Macs: 
https://www.bloomberg.com/news/newsletters/2022-02-20/when-will-apple-aapl-launch-a-new-macbook-air-macbook-pro-imac-pro-in-2022-kzvdtgri -------------------------------- Site do Loop Matinal: http://www.loopmatinal.com Anuncie no Loop Matinal: comercial@loopinfinito.net Marcus Mendes: https://www.twitter.com/mvcmendes Loop Infinito: https://www.youtube.com/oloopinfinito

Learn more about AlphaCode here.Check out an amazing video essay critiquing the NFT market, The Line Goes Up.Read up on Josh Wardle, the developer who built Wordle for his partner to help pass the time during the pandemic, then sold it to the NY Times for a sweet seven figures.

Learn more about AlphaCode here.Check out an amazing video essay critiquing the NFT market, The Line Goes Up.Read up on Josh Wardle, the developer who built Wordle for his partner to help pass the time during the pandemic, then sold it to the NY Times for a sweet seven figures.

Sind Machine Learning und Artificial Intelligence nur Hypes oder sollte ich meine Karriere dahingehend ausrichten? Und welche Hypes gibt es im Infrastruktur-Bereich? Und überhaupt: Wie steht das alles im Zusammenhang mit Job-Titels, meiner Beförderung zum Senior Engineer und meinem Gehalt?All diese Themen klären Wolfgang und Andy in dieser wilden Folge. Weiterhin: Warum das Leben kein Ponyhof ist, was Agrar-Tech und autonom-fahrende Trecker, die Inflation und Krösus damit zu tun haben, sowie warum Software Engineers zu den Top 5% der Gesellschaft gehören.Bonus: Warum Wolfgang kein Eiskunstlauf macht und wie er seinen Dr.-Titel bekommen hat.Feedback an stehtisch@engineeringkiosk.dev oder via Twitter an https://twitter.com/EngKioskLinksDeepMind AlphaCode: https://www.deepmind.com/blog/article/Competitive-programming-with-AlphaCodeGitHub Co-Pilot: https://copilot.github.com/GPT-3 Model: https://en.wikipedia.org/wiki/GPT-3Engineering levels / levels.fyi: https://www.levels.fyi/?compare=Google,Facebook,Microsoft&track=Software%20EngineerDown-Leveling = The Senioritz Rollercoaster: https://newsletter.pragmaticengineer.com/p/the-seniority-rollercoasterKrösus: https://de.wiktionary.org/wiki/Kr%C3%B6susCareer ladders bei Firmen / progression.fyi: https://www.progression.fyi/CircleCI Engineering Competency Matrix: https://docs.google.com/spreadsheets/d/131XZCEb8LoXqy79WWrhCX4sBnGhCM1nAIz4feFZJsEo/edit#gid=0Erwähnte PersonenRuss Cox: https://swtch.com/~rsc/Sprungmarken(00:00) Intro(01:06) Deepmind News "AlphaCode" - Ein neuer Machine Learning Hype?(06:40) Wie kann Alpha Code in der Praxis genutzt werden?(08:04) Coding Challenges im Recruiting-Prozess(11:09) Hypes im Infrastruktur-Bereich(16:45) Frischer Wind von neuen Leuten in der Firma(19:22) Mono-Repos als Hype-Beispiel(20:55) Industrie-Definition von Job-Titles(26:03) Braucht man Job-Titles (Senior, etc.)?(31:43) Festgefahrene Strukturen in Konzernen(37:38) Geld ist bei weitem nicht alles bei einem Job(41:50) Mach das was dir Spaß machst und Generalisten vs. Spezialisten(45:36) 5-Jahres-Pläne(49:56) OutroHostsWolfgang Gassler (https://twitter.com/schafele)Andy Grunwald (https://twitter.com/andygrunwald)Engineering Kiosk Podcast: Anfragen an stehtisch@engineeringkiosk.dev oder via Twitter an https://twitter.com/EngKiosk 

Côté intelligence artificielle, l'entreprise Deepmind, filiale de Google, est clairement l'un des leaders dans le monde. Après AlphaGo qui a été capable de battre le meilleur joueur de Go du monde et AlphaStar sur le jeu vidéo StarCraft II, voilà que l'IA investit le champ du développement informatique. AlphaCode, c'est le nom de cette nouvelle intelligence artificielle vise je cite à « écrire des programmes informatiques à un niveau compétitif » fin de citation. De quoi s'agit-il ? Est-ce une révolution on plutôt une menace sur la communauté des développeurs ? C'est ce que je vous propose de voir dans cet épisode. Dans le détail, AlphaCode a été entraîné grâce à des codes disponibles au grand public sur la plateforme opensource GitHub. Mais ces derniers temps, c'est sur la plateforme Codeforces, qui organise régulièrement des compétitions pour développeurs avec un classement à la clé que l'IA s'est illustré. Pour résumer, au terme de sa participation, AlphaCode se classait dans les je cite dans les 54 % des meilleures réponses humaines. Et si l'on élargit un peu plus, AlphaCode se positionnerait même parmi les 28 % des meilleurs compétiteurs des six derniers mois. Des résultats qui je cite « dépassent les attentes » pour Mike Mirzayanov, fondateur de Codeforces. « J'étais sceptique parce que même pour les problèmes simples, il est souvent nécessaire non seulement d'implémenter l'algorithme, mais aussi (et c'est la partie la plus difficile) de l'inventer […] AlphaCode a réussi à atteindre un niveau de performances du niveau d'un nouveau compétiteur prometteur » fin de citation. Pour l'instant, AlphaCode ne peut exercer ses talents que dans le cadre de compétition de code, avec une consigne stricte. En clair, voire cette IA coder un programme à partir de rien n'est pas pour tout de suite. De plus, il existe un vrai risque à confier la rédaction d'un code à une intelligence artificielle, car si les données qui servent à son entraînement contiennent des failles de sécurité, il n'est pas impossible que l'IA les reproduise ensuite. Quoi qu'il en soit, DeepMind n'est pas le seul sur les rangs puisque Microsoft et OpenAI sont également très actif dans ce domaine. Ceci, dit, on est encore assez loin de voir débarquer des programmes entièrement conçus par des robots. Voir Acast.com/privacy pour les informations sur la vie privée et l'opt-out. Learn more about your ad choices. Visit megaphone.fm/adchoices

AlphaCode Incubate is inviting start-ups with game-changing business ideas in financial services to become part of AlphaCode. Eight businesses will each qualify for a R2 million package. It's like a real life Shark Tank for small businesses, with BIG ideas! Andile Maseko joins Brent Lindeque to chat about last year's competition and how the businesses have grown in the past few months (adding jobs to our economy as well as new innovative ideas to the business space). 2019 applications were meant to close on the 18 June but AlphaCode decided to move this to the 24 June after appearing on the show. The packages consist of: - R1 million in grant funding - A R500 000 12-month customised financial services programme with access to experienced mentors, RMI capital and an extensive network of thought leaders - R250 000 worth of comprehensive business support services - R250 000 worth of premium office space at AlphaCode's exclusive Sandton co-working space and the opportunity to immerse in an unrivaled community of experts, potential clients and like-minded entrepreneurs. Ntandoyenkosi Shezi is the co-founder of iSpani Group which provides sales channels for insurance distribution in informal markets and collects data for financial inclusion and is currently part of the programme. He explains that Incubate has accelerated his exposure in financial services and to the RMI companies. Apply here