Podcasts about geolocation

J-Dog is the former maintainer of Bitcoin's Counterparty protocol – a role which he fulfilled for about 8 years. Under his stewardship, XCP witnessed the creation of legendary collections such as Spells of Genesis, Rare Pepes, and Fake Rares – even my Bitcoin Heads and Leftist Tears were created when he was the lead developer and he provided some useful advice. Today, J-Dog builds the FreeWallet.io Counterparty wallet and the TokenScan.io blockchain explorer (formerly Xchain.io). He maintains opinions which diverge from those of current maintainer Adam Krellenstein (who joined the show in S16 E14) and even claims that the Counterparty protocol was forked at block 866000. Time stamps: Introducing J-Dog (00:00:53) Counterparty's Founders (00:02:13) What is Counterparty? (00:03:19) History of Token Platforms (00:04:24) Creation of Dispensers (00:07:57) The Fork Controversy (00:09:50) User Reactions to Changes (00:12:42) Counterparty Classic (00:13:16) Current State of Dispensers (00:13:52) Ongoing FUD in the Community (00:14:41) Recent Developments (00:15:02) Control and Development (00:16:05) Token Scan and Exchange (00:17:25) Counterparty's Early Challenges (00:20:55) The use case for Bitcoin (00:23:16) Counterparty's missed opportunity (00:23:39) Community decision-making challenges (00:24:11) Smart contracts and security (00:25:27) Counterparty's innovative features (00:26:42) Evolution of Counterparty's focus (00:27:40) Concerns about asset transactions (00:28:19) The evolution of meme culture (00:29:26) Collecting Rare Pepes (00:31:03) Geolocation-based token distribution (00:32:04) Comparison to Pokémon Go (00:33:14) Current projects and developments (00:35:50) Citrea's zero-knowledge rollup (00:36:50) Counterparty's future on Layer Two (00:37:53) Current work and future vision (00:38:25) Community-driven development concerns (00:43:07) Consensus measurement in development (00:45:59) Consensus Gathering in Counterparty (00:46:39) Atomic Swaps Explained (00:49:42) Adoption of New Features (00:51:33) Counterparty vs Horizon Market (00:55:05) Impact of Ordinals on Counterparty (00:58:16) Integration of Ordinals with Counterparty (01:00:09) Fallout Among Developers (01:03:21) STAMPs vs Ordinals (01:04:34) Concerns About UTXO Set Bloat (01:07:45) Introduction to the UTXO Set Concerns (01:09:58) Turning Point on Stamps (01:10:48) Pixel Art and Compression Challenges (01:11:07) Nihilistic Moments in Bitcoin History (01:11:47) Innovations in Small Data Graphics (01:12:08) Future of Interoperability Among Protocols (01:13:38) Challenges in Ecosystem Integration (01:14:02) Islands of Unconnected Communities (01:15:35) Historical Significance of Bitcoin Artifacts (01:16:03) Hope for NFT Market Revival (01:17:38) Mixed Feelings on NFT Participation (01:18:37) Sponsor Plug for SideShift.ai (01:20:22) Counterparty Classic and Current Focus (01:22:55) Counterparty's Resilience (01:23:58) Future of Counterparty Protocol (01:24:59) Cultural Acceptance of On-Chain Data (01:27:42) Difference Between Counterparty Assets and Runes (01:28:18) Valuation of Vlad Head Cards (01:29:04) Scams in Low Liquidity Tokens (01:30:39) Concerns Over Domain Squatting (01:31:52) Counterparty Improvement Proposals (01:32:43) Creating an Asset Escrow Service (01:33:44) Resetting Asset Supply (01:34:42) Counterparty Wallet Quirks (01:35:21) Protocol Functionality Improvements (01:36:44) Funding Development through Donations (01:37:31) Betting System Revival (01:41:03) User Feedback on FreeWallet (01:44:24) Creating Exchange Markets (01:47:05) Transaction Fee Issues (01:48:19) Token Description Formatting (01:50:11) Multi-Send Transaction Challenges (01:51:14) User Interface Updates Needed (01:52:58) Mobile Wallet Development (01:53:34) Mobile Free Wallet Update (01:54:51) Free Wallet Confusion (01:55:01) Counterparty's Future (01:56:02) Investment Needs for Counterparty (01:57:18) Competing Visions for Counterparty (01:58:56) Message to Counterparty Team (01:59:46) Community Engagement (02:01:14) Running a Counterparty Node (02:03:37) Hardware Requirements (02:05:06) Importance of Running a Node (02:06:18) Closing Remarks (02:07:39)

In this Risky Bulletin sponsor interview Ed Currie from Kroll Cyber talks to Tom Uren about the recent hack of the Gravy Analytics geolocation data provider. He explains the hack and how geolocation data can be used by malicious actors. Show notes Kroll's report on the risks of geolocation hacks

In this episode of iGaming Daily, we explore the rapidly evolving landscape of Brazil's iGaming market, unpacking recent regulatory changes, challenges with municipal lotteries, and the ongoing Loterge conflict. Joining Fernando Noodt, Senior Journalist at SBC Noticias, is Ana Maria Menezes and Elisa Marcante of SBC Noticias Brasil and Lucia Gando, Editor of SBC Noticias, dives into the legislative efforts to combat match-fixing in sports betting and the crucial role of structured regulations in fostering a sustainable gaming industry.We also examine the industry's marketing strategies, the impact of new advertising regulations, and the push for responsible gaming practices. With a focus on collaboration between lawmakers and industry stakeholders, we discuss the importance of training affiliates and influencers to promote ethical gaming. To read more on the topic's discussed in today's podcast, click on the following links:Propane Ft https://sbcnoticias.com/br/propane-training-center-entrevista-benites/Municipal lotteries https://sbcnoticias.com/br/stf-solidariedade-loterias-municipais/Match fixing CPI https://sbcnoticias.com/br/cpi-da-manipulacao-sugere-3-projetos-de-lei/Host: Fernando NoodtGuests: Lucia Gando, Elisa Marcante & Ana Maria MenezesProducer: Anaya McDonaldEditor: James RossiGaming Daily is also now on TikTok. Make sure to follow us at iGaming Daily Podcast (@igaming_daily_podcast) | TikTok for bite-size clips from your favourite podcast. Finally, remember to check out Optimove at https://hubs.la/Q02gLC5L0 or go to Optimove.com/sbc to get your first month free when buying the industry's leading customer-loyalty service. 

Beyond IP, the role of geolocation data in combating AML and fraud. John Byrne sits down with David Briggs, CEO and Co-Founder of GeoGuard and GeoComply, to discuss the limitations of IP addresses and the role that advanced geolocation data can play in AML and in fighting other types of financial fraud, FinCEN's recent guidance on encouraging innovative responses to COVID-19 fraud, and how to improve the BSA/AML data analysis infrastructure.

Today's episode is with Paul Klein, founder of Browserbase. We talked about building browser infrastructure for AI agents, the future of agent authentication, and their open source framework Stagehand.* [00:00:00] Introductions* [00:04:46] AI-specific challenges in browser infrastructure* [00:07:05] Multimodality in AI-Powered Browsing* [00:12:26] Running headless browsers at scale* [00:18:46] Geolocation when proxying* [00:21:25] CAPTCHAs and Agent Auth* [00:28:21] Building “User take over” functionality* [00:33:43] Stagehand: AI web browsing framework* [00:38:58] OpenAI's Operator and computer use agents* [00:44:44] Surprising use cases of Browserbase* [00:47:18] Future of browser automation and market competition* [00:53:11] Being a solo founderTranscriptAlessio [00:00:04]: 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 are very blessed to have our friends, Paul Klein, for the fourth, the fourth, CEO of Browserbase. Welcome.Paul [00:00:21]: Thanks guys. Yeah, I'm happy to be here. I've been lucky to know both of you for like a couple of years now, I think. So it's just like we're hanging out, you know, with three ginormous microphones in front of our face. It's totally normal hangout.swyx [00:00:34]: Yeah. We've actually mentioned you on the podcast, I think, more often than any other Solaris tenant. Just because like you're one of the, you know, best performing, I think, LLM tool companies that have started up in the last couple of years.Paul [00:00:50]: Yeah, I mean, it's been a whirlwind of a year, like Browserbase is actually pretty close to our first birthday. So we are one years old. And going from, you know, starting a company as a solo founder to... To, you know, having a team of 20 people, you know, a series A, but also being able to support hundreds of AI companies that are building AI applications that go out and automate the web. It's just been like, really cool. It's been happening a little too fast. I think like collectively as an AI industry, let's just take a week off together. I took my first vacation actually two weeks ago, and Operator came out on the first day, and then a week later, DeepSeat came out. And I'm like on vacation trying to chill. I'm like, we got to build with this stuff, right? So it's been a breakneck year. But I'm super happy to be here and like talk more about all the stuff we're seeing. And I'd love to hear kind of what you guys are excited about too, and share with it, you know?swyx [00:01:39]: Where to start? So people, you've done a bunch of podcasts. I think I strongly recommend Jack Bridger's Scaling DevTools, as well as Turner Novak's The Peel. And, you know, I'm sure there's others. So you covered your Twilio story in the past, talked about StreamClub, you got acquired to Mux, and then you left to start Browserbase. So maybe we just start with what is Browserbase? Yeah.Paul [00:02:02]: Browserbase is the web browser for your AI. We're building headless browser infrastructure, which are browsers that run in a server environment that's accessible to developers via APIs and SDKs. It's really hard to run a web browser in the cloud. You guys are probably running Chrome on your computers, and that's using a lot of resources, right? So if you want to run a web browser or thousands of web browsers, you can't just spin up a bunch of lambdas. You actually need to use a secure containerized environment. You have to scale it up and down. It's a stateful system. And that infrastructure is, like, super painful. And I know that firsthand, because at my last company, StreamClub, I was CTO, and I was building our own internal headless browser infrastructure. That's actually why we sold the company, is because Mux really wanted to buy our headless browser infrastructure that we'd built. And it's just a super hard problem. And I actually told my co-founders, I would never start another company unless it was a browser infrastructure company. And it turns out that's really necessary in the age of AI, when AI can actually go out and interact with websites, click on buttons, fill in forms. You need AI to do all of that work in an actual browser running somewhere on a server. And BrowserBase powers that.swyx [00:03:08]: While you're talking about it, it occurred to me, not that you're going to be acquired or anything, but it occurred to me that it would be really funny if you became the Nikita Beer of headless browser companies. You just have one trick, and you make browser companies that get acquired.Paul [00:03:23]: I truly do only have one trick. I'm screwed if it's not for headless browsers. I'm not a Go programmer. You know, I'm in AI grant. You know, browsers is an AI grant. But we were the only company in that AI grant batch that used zero dollars on AI spend. You know, we're purely an infrastructure company. So as much as people want to ask me about reinforcement learning, I might not be the best guy to talk about that. But if you want to ask about headless browser infrastructure at scale, I can talk your ear off. So that's really my area of expertise. And it's a pretty niche thing. Like, nobody has done what we're doing at scale before. So we're happy to be the experts.swyx [00:03:59]: You do have an AI thing, stagehand. We can talk about the sort of core of browser-based first, and then maybe stagehand. Yeah, stagehand is kind of the web browsing framework. Yeah.What is Browserbase? Headless Browser Infrastructure ExplainedAlessio [00:04:10]: Yeah. Yeah. And maybe how you got to browser-based and what problems you saw. So one of the first things I worked on as a software engineer was integration testing. Sauce Labs was kind of like the main thing at the time. And then we had Selenium, we had Playbrite, we had all these different browser things. But it's always been super hard to do. So obviously you've worked on this before. When you started browser-based, what were the challenges? What were the AI-specific challenges that you saw versus, there's kind of like all the usual running browser at scale in the cloud, which has been a problem for years. What are like the AI unique things that you saw that like traditional purchase just didn't cover? Yeah.AI-specific challenges in browser infrastructurePaul [00:04:46]: First and foremost, I think back to like the first thing I did as a developer, like as a kid when I was writing code, I wanted to write code that did stuff for me. You know, I wanted to write code to automate my life. And I do that probably by using curl or beautiful soup to fetch data from a web browser. And I think I still do that now that I'm in the cloud. And the other thing that I think is a huge challenge for me is that you can't just create a web site and parse that data. And we all know that now like, you know, taking HTML and plugging that into an LLM, you can extract insights, you can summarize. So it was very clear that now like dynamic web scraping became very possible with the rise of large language models or a lot easier. And that was like a clear reason why there's been more usage of headless browsers, which are necessary because a lot of modern websites don't expose all of their page content via a simple HTTP request. You know, they actually do require you to run this type of code for a specific time. JavaScript on the page to hydrate this. Airbnb is a great example. You go to airbnb.com. A lot of that content on the page isn't there until after they run the initial hydration. So you can't just scrape it with a curl. You need to have some JavaScript run. And a browser is that JavaScript engine that's going to actually run all those requests on the page. So web data retrieval was definitely one driver of starting BrowserBase and the rise of being able to summarize that within LLM. Also, I was familiar with if I wanted to automate a website, I could write one script and that would work for one website. It was very static and deterministic. But the web is non-deterministic. The web is always changing. And until we had LLMs, there was no way to write scripts that you could write once that would run on any website. That would change with the structure of the website. Click the login button. It could mean something different on many different websites. And LLMs allow us to generate code on the fly to actually control that. So I think that rise of writing the generic automation scripts that can work on many different websites, to me, made it clear that browsers are going to be a lot more useful because now you can automate a lot more things without writing. If you wanted to write a script to book a demo call on 100 websites, previously, you had to write 100 scripts. Now you write one script that uses LLMs to generate that script. That's why we built our web browsing framework, StageHand, which does a lot of that work for you. But those two things, web data collection and then enhanced automation of many different websites, it just felt like big drivers for more browser infrastructure that would be required to power these kinds of features.Alessio [00:07:05]: And was multimodality also a big thing?Paul [00:07:08]: Now you can use the LLMs to look, even though the text in the dome might not be as friendly. Maybe my hot take is I was always kind of like, I didn't think vision would be as big of a driver. For UI automation, I felt like, you know, HTML is structured text and large language models are good with structured text. But it's clear that these computer use models are often vision driven, and they've been really pushing things forward. So definitely being multimodal, like rendering the page is required to take a screenshot to give that to a computer use model to take actions on a website. And it's just another win for browser. But I'll be honest, that wasn't what I was thinking early on. I didn't even think that we'd get here so fast with multimodality. I think we're going to have to get back to multimodal and vision models.swyx [00:07:50]: This is one of those things where I forgot to mention in my intro that I'm an investor in Browserbase. And I remember that when you pitched to me, like a lot of the stuff that we have today, we like wasn't on the original conversation. But I did have my original thesis was something that we've talked about on the podcast before, which is take the GPT store, the custom GPT store, all the every single checkbox and plugin is effectively a startup. And this was the browser one. I think the main hesitation, I think I actually took a while to get back to you. The main hesitation was that there were others. Like you're not the first hit list browser startup. It's not even your first hit list browser startup. There's always a question of like, will you be the category winner in a place where there's a bunch of incumbents, to be honest, that are bigger than you? They're just not targeted at the AI space. They don't have the backing of Nat Friedman. And there's a bunch of like, you're here in Silicon Valley. They're not. I don't know.Paul [00:08:47]: I don't know if that's, that was it, but like, there was a, yeah, I mean, like, I think I tried all the other ones and I was like, really disappointed. Like my background is from working at great developer tools, companies, and nothing had like the Vercel like experience. Um, like our biggest competitor actually is partly owned by private equity and they just jacked up their prices quite a bit. And the dashboard hasn't changed in five years. And I actually used them at my last company and tried them and I was like, oh man, like there really just needs to be something that's like the experience of these great infrastructure companies, like Stripe, like clerk, like Vercel that I use in love, but oriented towards this kind of like more specific category, which is browser infrastructure, which is really technically complex. Like a lot of stuff can go wrong on the internet when you're running a browser. The internet is very vast. There's a lot of different configurations. Like there's still websites that only work with internet explorer out there. How do you handle that when you're running your own browser infrastructure? These are the problems that we have to think about and solve at BrowserBase. And it's, it's certainly a labor of love, but I built this for me, first and foremost, I know it's super cheesy and everyone says that for like their startups, but it really, truly was for me. If you look at like the talks I've done even before BrowserBase, and I'm just like really excited to try and build a category defining infrastructure company. And it's, it's rare to have a new category of infrastructure exists. We're here in the Chroma offices and like, you know, vector databases is a new category of infrastructure. Is it, is it, I mean, we can, we're in their office, so, you know, we can, we can debate that one later. That is one.Multimodality in AI-Powered Browsingswyx [00:10:16]: That's one of the industry debates.Paul [00:10:17]: I guess we go back to the LLMOS talk that Karpathy gave way long ago. And like the browser box was very clearly there and it seemed like the people who were building in this space also agreed that browsers are a core primitive of infrastructure for the LLMOS that's going to exist in the future. And nobody was building something there that I wanted to use. So I had to go build it myself.swyx [00:10:38]: Yeah. I mean, exactly that talk that, that honestly, that diagram, every box is a startup and there's the code box and then there's the. The browser box. I think at some point they will start clashing there. There's always the question of the, are you a point solution or are you the sort of all in one? And I think the point solutions tend to win quickly, but then the only ones have a very tight cohesive experience. Yeah. Let's talk about just the hard problems of browser base you have on your website, which is beautiful. Thank you. Was there an agency that you used for that? Yeah. Herb.paris.Paul [00:11:11]: They're amazing. Herb.paris. Yeah. It's H-E-R-V-E. I highly recommend for developers. Developer tools, founders to work with consumer agencies because they end up building beautiful things and the Parisians know how to build beautiful interfaces. So I got to give prep.swyx [00:11:24]: And chat apps, apparently are, they are very fast. Oh yeah. The Mistral chat. Yeah. Mistral. Yeah.Paul [00:11:31]: Late chat.swyx [00:11:31]: Late chat. And then your videos as well, it was professionally shot, right? The series A video. Yeah.Alessio [00:11:36]: Nico did the videos. He's amazing. Not the initial video that you shot at the new one. First one was Austin.Paul [00:11:41]: Another, another video pretty surprised. But yeah, I mean, like, I think when you think about how you talk about your company. You have to think about the way you present yourself. It's, you know, as a developer, you think you evaluate a company based on like the API reliability and the P 95, but a lot of developers say, is the website good? Is the message clear? Do I like trust this founder? I'm building my whole feature on. So I've tried to nail that as well as like the reliability of the infrastructure. You're right. It's very hard. And there's a lot of kind of foot guns that you run into when running headless browsers at scale. Right.Competing with Existing Headless Browser Solutionsswyx [00:12:10]: So let's pick one. You have eight features here. Seamless integration. Scalability. Fast or speed. Secure. Observable. Stealth. That's interesting. Extensible and developer first. What comes to your mind as like the top two, three hardest ones? Yeah.Running headless browsers at scalePaul [00:12:26]: I think just running headless browsers at scale is like the hardest one. And maybe can I nerd out for a second? Is that okay? I heard this is a technical audience, so I'll talk to the other nerds. Whoa. They were listening. Yeah. They're upset. They're ready. The AGI is angry. Okay. So. So how do you run a browser in the cloud? Let's start with that, right? So let's say you're using a popular browser automation framework like Puppeteer, Playwright, and Selenium. Maybe you've written a code, some code locally on your computer that opens up Google. It finds the search bar and then types in, you know, search for Latent Space and hits the search button. That script works great locally. You can see the little browser open up. You want to take that to production. You want to run the script in a cloud environment. So when your laptop is closed, your browser is doing something. The browser is doing something. Well, I, we use Amazon. You can see the little browser open up. You know, the first thing I'd reach for is probably like some sort of serverless infrastructure. I would probably try and deploy on a Lambda. But Chrome itself is too big to run on a Lambda. It's over 250 megabytes. So you can't easily start it on a Lambda. So you maybe have to use something like Lambda layers to squeeze it in there. Maybe use a different Chromium build that's lighter. And you get it on the Lambda. Great. It works. But it runs super slowly. It's because Lambdas are very like resource limited. They only run like with one vCPU. You can run one process at a time. Remember, Chromium is super beefy. It's barely running on my MacBook Air. I'm still downloading it from a pre-run. Yeah, from the test earlier, right? I'm joking. But it's big, you know? So like Lambda, it just won't work really well. Maybe it'll work, but you need something faster. Your users want something faster. Okay. Well, let's put it on a beefier instance. Let's get an EC2 server running. Let's throw Chromium on there. Great. Okay. I can, that works well with one user. But what if I want to run like 10 Chromium instances, one for each of my users? Okay. Well, I might need two EC2 instances. Maybe 10. All of a sudden, you have multiple EC2 instances. This sounds like a problem for Kubernetes and Docker, right? Now, all of a sudden, you're using ECS or EKS, the Kubernetes or container solutions by Amazon. You're spending up and down containers, and you're spending a whole engineer's time on kind of maintaining this stateful distributed system. Those are some of the worst systems to run because when it's a stateful distributed system, it means that you are bound by the connections to that thing. You have to keep the browser open while someone is working with it, right? That's just a painful architecture to run. And there's all this other little gotchas with Chromium, like Chromium, which is the open source version of Chrome, by the way. You have to install all these fonts. You want emojis working in your browsers because your vision model is looking for the emoji. You need to make sure you have the emoji fonts. You need to make sure you have all the right extensions configured, like, oh, do you want ad blocking? How do you configure that? How do you actually record all these browser sessions? Like it's a headless browser. You can't look at it. So you need to have some sort of observability. Maybe you're recording videos and storing those somewhere. It all kind of adds up to be this just giant monster piece of your project when all you wanted to do was run a lot of browsers in production for this little script to go to google.com and search. And when I see a complex distributed system, I see an opportunity to build a great infrastructure company. And we really abstract that away with Browserbase where our customers can use these existing frameworks, Playwright, Publisher, Selenium, or our own stagehand and connect to our browsers in a serverless-like way. And control them, and then just disconnect when they're done. And they don't have to think about the complex distributed system behind all of that. They just get a browser running anywhere, anytime. Really easy to connect to.swyx [00:15:55]: I'm sure you have questions. My standard question with anything, so essentially you're a serverless browser company, and there's been other serverless things that I'm familiar with in the past, serverless GPUs, serverless website hosting. That's where I come from with Netlify. One question is just like, you promised to spin up thousands of servers. You promised to spin up thousands of browsers in milliseconds. I feel like there's no real solution that does that yet. And I'm just kind of curious how. The only solution I know, which is to kind of keep a kind of warm pool of servers around, which is expensive, but maybe not so expensive because it's just CPUs. So I'm just like, you know. Yeah.Browsers as a Core Primitive in AI InfrastructurePaul [00:16:36]: You nailed it, right? I mean, how do you offer a serverless-like experience with something that is clearly not serverless, right? And the answer is, you need to be able to run... We run many browsers on single nodes. We use Kubernetes at browser base. So we have many pods that are being scheduled. We have to predictably schedule them up or down. Yes, thousands of browsers in milliseconds is the best case scenario. If you hit us with 10,000 requests, you may hit a slower cold start, right? So we've done a lot of work on predictive scaling and being able to kind of route stuff to different regions where we have multiple regions of browser base where we have different pools available. You can also pick the region you want to go to based on like lower latency, round trip, time latency. It's very important with these types of things. There's a lot of requests going over the wire. So for us, like having a VM like Firecracker powering everything under the hood allows us to be super nimble and spin things up or down really quickly with strong multi-tenancy. But in the end, this is like the complex infrastructural challenges that we have to kind of deal with at browser base. And we have a lot more stuff on our roadmap to allow customers to have more levers to pull to exchange, do you want really fast browser startup times or do you want really low costs? And if you're willing to be more flexible on that, we may be able to kind of like work better for your use cases.swyx [00:17:44]: Since you used Firecracker, shouldn't Fargate do that for you or did you have to go lower level than that? We had to go lower level than that.Paul [00:17:51]: I find this a lot with Fargate customers, which is alarming for Fargate. We used to be a giant Fargate customer. Actually, the first version of browser base was ECS and Fargate. And unfortunately, it's a great product. I think we were actually the largest Fargate customer in our region for a little while. No, what? Yeah, seriously. And unfortunately, it's a great product, but I think if you're an infrastructure company, you actually have to have a deeper level of control over these primitives. I think it's the same thing is true with databases. We've used other database providers and I think-swyx [00:18:21]: Yeah, serverless Postgres.Paul [00:18:23]: Shocker. When you're an infrastructure company, you're on the hook if any provider has an outage. And I can't tell my customers like, hey, we went down because so-and-so went down. That's not acceptable. So for us, we've really moved to bringing things internally. It's kind of opposite of what we preach. We tell our customers, don't build this in-house, but then we're like, we build a lot of stuff in-house. But I think it just really depends on what is in the critical path. We try and have deep ownership of that.Alessio [00:18:46]: On the distributed location side, how does that work for the web where you might get sort of different content in different locations, but the customer is expecting, you know, if you're in the US, I'm expecting the US version. But if you're spinning up my browser in France, I might get the French version. Yeah.Paul [00:19:02]: Yeah. That's a good question. Well, generally, like on the localization, there is a thing called locale in the browser. You can set like what your locale is. If you're like in the ENUS browser or not, but some things do IP, IP based routing. And in that case, you may want to have a proxy. Like let's say you're running something in the, in Europe, but you want to make sure you're showing up from the US. You may want to use one of our proxy features so you can turn on proxies to say like, make sure these connections always come from the United States, which is necessary too, because when you're browsing the web, you're coming from like a, you know, data center IP, and that can make things a lot harder to browse web. So we do have kind of like this proxy super network. Yeah. We have a proxy for you based on where you're going, so you can reliably automate the web. But if you get scheduled in Europe, that doesn't happen as much. We try and schedule you as close to, you know, your origin that you're trying to go to. But generally you have control over the regions you can put your browsers in. So you can specify West one or East one or Europe. We only have one region of Europe right now, actually. Yeah.Alessio [00:19:55]: What's harder, the browser or the proxy? I feel like to me, it feels like actually proxying reliably at scale. It's much harder than spending up browsers at scale. I'm curious. It's all hard.Paul [00:20:06]: It's layers of hard, right? Yeah. I think it's different levels of hard. I think the thing with the proxy infrastructure is that we work with many different web proxy providers and some are better than others. Some have good days, some have bad days. And our customers who've built browser infrastructure on their own, they have to go and deal with sketchy actors. Like first they figure out their own browser infrastructure and then they got to go buy a proxy. And it's like you can pay in Bitcoin and it just kind of feels a little sus, right? It's like you're buying drugs when you're trying to get a proxy online. We have like deep relationships with these counterparties. We're able to audit them and say, is this proxy being sourced ethically? Like it's not running on someone's TV somewhere. Is it free range? Yeah. Free range organic proxies, right? Right. We do a level of diligence. We're SOC 2. So we have to understand what is going on here. But then we're able to make sure that like we route around proxy providers not working. There's proxy providers who will just, the proxy will stop working all of a sudden. And then if you don't have redundant proxying on your own browsers, that's hard down for you or you may get some serious impacts there. With us, like we intelligently know, hey, this proxy is not working. Let's go to this one. And you can kind of build a network of multiple providers to really guarantee the best uptime for our customers. Yeah. So you don't own any proxies? We don't own any proxies. You're right. The team has been saying who wants to like take home a little proxy server, but not yet. We're not there yet. You know?swyx [00:21:25]: It's a very mature market. I don't think you should build that yourself. Like you should just be a super customer of them. Yeah. Scraping, I think, is the main use case for that. I guess. Well, that leads us into CAPTCHAs and also off, but let's talk about CAPTCHAs. You had a little spiel that you wanted to talk about CAPTCHA stuff.Challenges of Scaling Browser InfrastructurePaul [00:21:43]: Oh, yeah. I was just, I think a lot of people ask, if you're thinking about proxies, you're thinking about CAPTCHAs too. I think it's the same thing. You can go buy CAPTCHA solvers online, but it's the same buying experience. It's some sketchy website, you have to integrate it. It's not fun to buy these things and you can't really trust that the docs are bad. What Browserbase does is we integrate a bunch of different CAPTCHAs. We do some stuff in-house, but generally we just integrate with a bunch of known vendors and continually monitor and maintain these things and say, is this working or not? Can we route around it or not? These are CAPTCHA solvers. CAPTCHA solvers, yeah. Not CAPTCHA providers, CAPTCHA solvers. Yeah, sorry. CAPTCHA solvers. We really try and make sure all of that works for you. I think as a dev, if I'm buying infrastructure, I want it all to work all the time and it's important for us to provide that experience by making sure everything does work and monitoring it on our own. Yeah. Right now, the world of CAPTCHAs is tricky. I think AI agents in particular are very much ahead of the internet infrastructure. CAPTCHAs are designed to block all types of bots, but there are now good bots and bad bots. I think in the future, CAPTCHAs will be able to identify who a good bot is, hopefully via some sort of KYC. For us, we've been very lucky. We have very little to no known abuse of Browserbase because we really look into who we work with. And for certain types of CAPTCHA solving, we only allow them on certain types of plans because we want to make sure that we can know what people are doing, what their use cases are. And that's really allowed us to try and be an arbiter of good bots, which is our long term goal. I want to build great relationships with people like Cloudflare so we can agree, hey, here are these acceptable bots. We'll identify them for you and make sure we flag when they come to your website. This is a good bot, you know?Alessio [00:23:23]: I see. And Cloudflare said they want to do more of this. So they're going to set by default, if they think you're an AI bot, they're going to reject. I'm curious if you think this is something that is going to be at the browser level or I mean, the DNS level with Cloudflare seems more where it should belong. But I'm curious how you think about it.Paul [00:23:40]: I think the web's going to change. You know, I think that the Internet as we have it right now is going to change. And we all need to just accept that the cat is out of the bag. And instead of kind of like wishing the Internet was like it was in the 2000s, we can have free content line that wouldn't be scraped. It's just it's not going to happen. And instead, we should think about like, one, how can we change? How can we change the models of, you know, information being published online so people can adequately commercialize it? But two, how do we rebuild applications that expect that AI agents are going to log in on their behalf? Those are the things that are going to allow us to kind of like identify good and bad bots. And I think the team at Clerk has been doing a really good job with this on the authentication side. I actually think that auth is the biggest thing that will prevent agents from accessing stuff, not captchas. And I think there will be agent auth in the future. I don't know if it's going to happen from an individual company, but actually authentication providers that have a, you know, hidden login as agent feature, which will then you put in your email, you'll get a push notification, say like, hey, your browser-based agent wants to log into your Airbnb. You can approve that and then the agent can proceed. That really circumvents the need for captchas or logging in as you and sharing your password. I think agent auth is going to be one way we identify good bots going forward. And I think a lot of this captcha solving stuff is really short-term problems as the internet kind of reorients itself around how it's going to work with agents browsing the web, just like people do. Yeah.Managing Distributed Browser Locations and Proxiesswyx [00:24:59]: Stitch recently was on Hacker News for talking about agent experience, AX, which is a thing that Netlify is also trying to clone and coin and talk about. And we've talked about this on our previous episodes before in a sense that I actually think that's like maybe the only part of the tech stack that needs to be kind of reinvented for agents. Everything else can stay the same, CLIs, APIs, whatever. But auth, yeah, we need agent auth. And it's mostly like short-lived, like it should not, it should be a distinct, identity from the human, but paired. I almost think like in the same way that every social network should have your main profile and then your alt accounts or your Finsta, it's almost like, you know, every, every human token should be paired with the agent token and the agent token can go and do stuff on behalf of the human token, but not be presumed to be the human. Yeah.Paul [00:25:48]: It's like, it's, it's actually very similar to OAuth is what I'm thinking. And, you know, Thread from Stitch is an investor, Colin from Clerk, Octaventures, all investors in browser-based because like, I hope they solve this because they'll make browser-based submission more possible. So we don't have to overcome all these hurdles, but I think it will be an OAuth-like flow where an agent will ask to log in as you, you'll approve the scopes. Like it can book an apartment on Airbnb, but it can't like message anybody. And then, you know, the agent will have some sort of like role-based access control within an application. Yeah. I'm excited for that.swyx [00:26:16]: The tricky part is just, there's one, one layer of delegation here, which is like, you're authoring my user's user or something like that. I don't know if that's tricky or not. Does that make sense? Yeah.Paul [00:26:25]: You know, actually at Twilio, I worked on the login identity and access. Management teams, right? So like I built Twilio's login page.swyx [00:26:31]: You were an intern on that team and then you became the lead in two years? Yeah.Paul [00:26:34]: Yeah. I started as an intern in 2016 and then I was the tech lead of that team. How? That's not normal. I didn't have a life. He's not normal. Look at this guy. I didn't have a girlfriend. I just loved my job. I don't know. I applied to 500 internships for my first job and I got rejected from every single one of them except for Twilio and then eventually Amazon. And they took a shot on me and like, I was getting paid money to write code, which was my dream. Yeah. Yeah. I'm very lucky that like this coding thing worked out because I was going to be doing it regardless. And yeah, I was able to kind of spend a lot of time on a team that was growing at a company that was growing. So it informed a lot of this stuff here. I think these are problems that have been solved with like the SAML protocol with SSO. I think it's a really interesting stuff with like WebAuthn, like these different types of authentication, like schemes that you can use to authenticate people. The tooling is all there. It just needs to be tweaked a little bit to work for agents. And I think the fact that there are companies that are already. Providing authentication as a service really sets it up. Well, the thing that's hard is like reinventing the internet for agents. We don't want to rebuild the internet. That's an impossible task. And I think people often say like, well, we'll have this second layer of APIs built for agents. I'm like, we will for the top use cases, but instead of we can just tweak the internet as is, which is on the authentication side, I think we're going to be the dumb ones going forward. Unfortunately, I think AI is going to be able to do a lot of the tasks that we do online, which means that it will be able to go to websites, click buttons on our behalf and log in on our behalf too. So with this kind of like web agent future happening, I think with some small structural changes, like you said, it feels like it could all slot in really nicely with the existing internet.Handling CAPTCHAs and Agent Authenticationswyx [00:28:08]: There's one more thing, which is the, your live view iframe, which lets you take, take control. Yeah. Obviously very key for operator now, but like, was, is there anything interesting technically there or that the people like, well, people always want this.Paul [00:28:21]: It was really hard to build, you know, like, so, okay. Headless browsers, you don't see them, right. They're running. They're running in a cloud somewhere. You can't like look at them. And I just want to really make, it's a weird name. I wish we came up with a better name for this thing, but you can't see them. Right. But customers don't trust AI agents, right. At least the first pass. So what we do with our live view is that, you know, when you use browser base, you can actually embed a live view of the browser running in the cloud for your customer to see it working. And that's what the first reason is the build trust, like, okay, so I have this script. That's going to go automate a website. I can embed it into my web application via an iframe and my customer can watch. I think. And then we added two way communication. So now not only can you watch the browser kind of being operated by AI, if you want to pause and actually click around type within this iframe that's controlling a browser, that's also possible. And this is all thanks to some of the lower level protocol, which is called the Chrome DevTools protocol. It has a API called start screencast, and you can also send mouse clicks and button clicks to a remote browser. And this is all embeddable within iframes. You have a browser within a browser, yo. And then you simulate the screen, the click on the other side. Exactly. And this is really nice often for, like, let's say, a capture that can't be solved. You saw this with Operator, you know, Operator actually uses a different approach. They use VNC. So, you know, you're able to see, like, you're seeing the whole window here. What we're doing is something a little lower level with the Chrome DevTools protocol. It's just PNGs being streamed over the wire. But the same thing is true, right? Like, hey, I'm running a window. Pause. Can you do something in this window? Human. Okay, great. Resume. Like sometimes 2FA tokens. Like if you get that text message, you might need a person to type that in. Web agents need human-in-the-loop type workflows still. You still need a person to interact with the browser. And building a UI to proxy that is kind of hard. You may as well just show them the whole browser and say, hey, can you finish this up for me? And then let the AI proceed on afterwards. Is there a future where I stream my current desktop to browser base? I don't think so. I think we're very much cloud infrastructure. Yeah. You know, but I think a lot of the stuff we're doing, we do want to, like, build tools. Like, you know, we'll talk about the stage and, you know, web agent framework in a second. But, like, there's a case where a lot of people are going desktop first for, you know, consumer use. And I think cloud is doing a lot of this, where I expect to see, you know, MCPs really oriented around the cloud desktop app for a reason, right? Like, I think a lot of these tools are going to run on your computer because it makes... I think it's breaking out. People are putting it on a server. Oh, really? Okay. Well, sweet. We'll see. We'll see that. I was surprised, though, wasn't I? I think that the browser company, too, with Dia Browser, it runs on your machine. You know, it's going to be...swyx [00:30:50]: What is it?Paul [00:30:51]: So, Dia Browser, as far as I understand... I used to use Arc. Yeah. I haven't used Arc. But I'm a big fan of the browser company. I think they're doing a lot of cool stuff in consumer. As far as I understand, it's a browser where you have a sidebar where you can, like, chat with it and it can control the local browser on your machine. So, if you imagine, like, what a consumer web agent is, which it lives alongside your browser, I think Google Chrome has Project Marina, I think. I almost call it Project Marinara for some reason. I don't know why. It's...swyx [00:31:17]: No, I think it's someone really likes the Waterworld. Oh, I see. The classic Kevin Costner. Yeah.Paul [00:31:22]: Okay. Project Marinara is a similar thing to the Dia Browser, in my mind, as far as I understand it. You have a browser that has an AI interface that will take over your mouse and keyboard and control the browser for you. Great for consumer use cases. But if you're building applications that rely on a browser and it's more part of a greater, like, AI app experience, you probably need something that's more like infrastructure, not a consumer app.swyx [00:31:44]: Just because I have explored a little bit in this area, do people want branching? So, I have the state. Of whatever my browser's in. And then I want, like, 100 clones of this state. Do people do that? Or...Paul [00:31:56]: People don't do it currently. Yeah. But it's definitely something we're thinking about. I think the idea of forking a browser is really cool. Technically, kind of hard. We're starting to see this in code execution, where people are, like, forking some, like, code execution, like, processes or forking some tool calls or branching tool calls. Haven't seen it at the browser level yet. But it makes sense. Like, if an AI agent is, like, using a website and it's not sure what path it wants to take to crawl this website. To find the information it's looking for. It would make sense for it to explore both paths in parallel. And that'd be a very, like... A road not taken. Yeah. And hopefully find the right answer. And then say, okay, this was actually the right one. And memorize that. And go there in the future. On the roadmap. For sure. Don't make my roadmap, please. You know?Alessio [00:32:37]: How do you actually do that? Yeah. How do you fork? I feel like the browser is so stateful for so many things.swyx [00:32:42]: Serialize the state. Restore the state. I don't know.Paul [00:32:44]: So, it's one of the reasons why we haven't done it yet. It's hard. You know? Like, to truly fork, it's actually quite difficult. The naive way is to open the same page in a new tab and then, like, hope that it's at the same thing. But if you have a form halfway filled, you may have to, like, take the whole, you know, container. Pause it. All the memory. Duplicate it. Restart it from there. It could be very slow. So, we haven't found a thing. Like, the easy thing to fork is just, like, copy the page object. You know? But I think there needs to be something a little bit more robust there. Yeah.swyx [00:33:12]: So, MorphLabs has this infinite branch thing. Like, wrote a custom fork of Linux or something that let them save the system state and clone it. MorphLabs, hit me up. I'll be a customer. Yeah. That's the only. I think that's the only way to do it. Yeah. Like, unless Chrome has some special API for you. Yeah.Paul [00:33:29]: There's probably something we'll reverse engineer one day. I don't know. Yeah.Alessio [00:33:32]: Let's talk about StageHand, the AI web browsing framework. You have three core components, Observe, Extract, and Act. Pretty clean landing page. What was the idea behind making a framework? Yeah.Stagehand: AI web browsing frameworkPaul [00:33:43]: So, there's three frameworks that are very popular or already exist, right? Puppeteer, Playwright, Selenium. Those are for building hard-coded scripts to control websites. And as soon as I started to play with LLMs plus browsing, I caught myself, you know, code-genning Playwright code to control a website. I would, like, take the DOM. I'd pass it to an LLM. I'd say, can you generate the Playwright code to click the appropriate button here? And it would do that. And I was like, this really should be part of the frameworks themselves. And I became really obsessed with SDKs that take natural language as part of, like, the API input. And that's what StageHand is. StageHand exposes three APIs, and it's a super set of Playwright. So, if you go to a page, you may want to take an action, click on the button, fill in the form, etc. That's what the act command is for. You may want to extract some data. This one takes a natural language, like, extract the winner of the Super Bowl from this page. You can give it a Zod schema, so it returns a structured output. And then maybe you're building an API. You can do an agent loop, and you want to kind of see what actions are possible on this page before taking one. You can do observe. So, you can observe the actions on the page, and it will generate a list of actions. You can guide it, like, give me actions on this page related to buying an item. And you can, like, buy it now, add to cart, view shipping options, and pass that to an LLM, an agent loop, to say, what's the appropriate action given this high-level goal? So, StageHand isn't a web agent. It's a framework for building web agents. And we think that agent loops are actually pretty close to the application layer because every application probably has different goals or different ways it wants to take steps. I don't think I've seen a generic. Maybe you guys are the experts here. I haven't seen, like, a really good AI agent framework here. Everyone kind of has their own special sauce, right? I see a lot of developers building their own agent loops, and they're using tools. And I view StageHand as the browser tool. So, we expose act, extract, observe. Your agent can call these tools. And from that, you don't have to worry about it. You don't have to worry about generating playwright code performantly. You don't have to worry about running it. You can kind of just integrate these three tool calls into your agent loop and reliably automate the web.swyx [00:35:48]: A special shout-out to Anirudh, who I met at your dinner, who I think listens to the pod. Yeah. Hey, Anirudh.Paul [00:35:54]: Anirudh's a man. He's a StageHand guy.swyx [00:35:56]: I mean, the interesting thing about each of these APIs is they're kind of each startup. Like, specifically extract, you know, Firecrawler is extract. There's, like, Expand AI. There's a whole bunch of, like, extract companies. They just focus on extract. I'm curious. Like, I feel like you guys are going to collide at some point. Like, right now, it's friendly. Everyone's in a blue ocean. At some point, it's going to be valuable enough that there's some turf battle here. I don't think you have a dog in a fight. I think you can mock extract to use an external service if they're better at it than you. But it's just an observation that, like, in the same way that I see each option, each checkbox in the side of custom GBTs becoming a startup or each box in the Karpathy chart being a startup. Like, this is also becoming a thing. Yeah.Paul [00:36:41]: I mean, like, so the way StageHand works is that it's MIT-licensed, completely open source. You bring your own API key to your LLM of choice. You could choose your LLM. We don't make any money off of the extract or really. We only really make money if you choose to run it with our browser. You don't have to. You can actually use your own browser, a local browser. You know, StageHand is completely open source for that reason. And, yeah, like, I think if you're building really complex web scraping workflows, I don't know if StageHand is the tool for you. I think it's really more if you're building an AI agent that needs a few general tools or if it's doing a lot of, like, web automation-intensive work. But if you're building a scraping company, StageHand is not your thing. You probably want something that's going to, like, get HTML content, you know, convert that to Markdown, query it. That's not what StageHand does. StageHand is more about reliability. I think we focus a lot on reliability and less so on cost optimization and speed at this point.swyx [00:37:33]: I actually feel like StageHand, so the way that StageHand works, it's like, you know, page.act, click on the quick start. Yeah. It's kind of the integration test for the code that you would have to write anyway, like the Puppeteer code that you have to write anyway. And when the page structure changes, because it always does, then this is still the test. This is still the test that I would have to write. Yeah. So it's kind of like a testing framework that doesn't need implementation detail.Paul [00:37:56]: Well, yeah. I mean, Puppeteer, Playwright, and Slenderman were all designed as testing frameworks, right? Yeah. And now people are, like, hacking them together to automate the web. I would say, and, like, maybe this is, like, me being too specific. But, like, when I write tests, if the page structure changes. Without me knowing, I want that test to fail. So I don't know if, like, AI, like, regenerating that. Like, people are using StageHand for testing. But it's more for, like, usability testing, not, like, testing of, like, does the front end, like, has it changed or not. Okay. But generally where we've seen people, like, really, like, take off is, like, if they're using, you know, something. If they want to build a feature in their application that's kind of like Operator or Deep Research, they're using StageHand to kind of power that tool calling in their own agent loop. Okay. Cool.swyx [00:38:37]: So let's go into Operator, the first big agent launch of the year from OpenAI. Seems like they have a whole bunch scheduled. You were on break and your phone blew up. What's your just general view of computer use agents is what they're calling it. The overall category before we go into Open Operator, just the overall promise of Operator. I will observe that I tried it once. It was okay. And I never tried it again.OpenAI's Operator and computer use agentsPaul [00:38:58]: That tracks with my experience, too. Like, I'm a huge fan of the OpenAI team. Like, I think that I do not view Operator as the company. I'm not a company killer for browser base at all. I think it actually shows people what's possible. I think, like, computer use models make a lot of sense. And I'm actually most excited about computer use models is, like, their ability to, like, really take screenshots and reasoning and output steps. I think that using mouse click or mouse coordinates, I've seen that proved to be less reliable than I would like. And I just wonder if that's the right form factor. What we've done with our framework is anchor it to the DOM itself, anchor it to the actual item. So, like, if it's clicking on something, it's clicking on that thing, you know? Like, it's more accurate. No matter where it is. Yeah, exactly. Because it really ties in nicely. And it can handle, like, the whole viewport in one go, whereas, like, Operator can only handle what it sees. Can you hover? Is hovering a thing that you can do? I don't know if we expose it as a tool directly, but I'm sure there's, like, an API for hovering. Like, move mouse to this position. Yeah, yeah, yeah. I think you can trigger hover, like, via, like, the JavaScript on the DOM itself. But, no, I think, like, when we saw computer use, everyone's eyes lit up because they realized, like, wow, like, AI is going to actually automate work for people. And I think seeing that kind of happen from both of the labs, and I'm sure we're going to see more labs launch computer use models, I'm excited to see all the stuff that people build with it. I think that I'd love to see computer use power, like, controlling a browser on browser base. And I think, like, Open Operator, which was, like, our open source version of OpenAI's Operator, was our first take on, like, how can we integrate these models into browser base? And we handle the infrastructure and let the labs do the models. I don't have a sense that Operator will be released as an API. I don't know. Maybe it will. I'm curious to see how well that works because I think it's going to be really hard for a company like OpenAI to do things like support CAPTCHA solving or, like, have proxies. Like, I think it's hard for them structurally. Imagine this New York Times headline, OpenAI CAPTCHA solving. Like, that would be a pretty bad headline, this New York Times headline. Browser base solves CAPTCHAs. No one cares. No one cares. And, like, our investors are bored. Like, we're all okay with this, you know? We're building this company knowing that the CAPTCHA solving is short-lived until we figure out how to authenticate good bots. I think it's really hard for a company like OpenAI, who has this brand that's so, so good, to balance with, like, the icky parts of web automation, which it can be kind of complex to solve. I'm sure OpenAI knows who to call whenever they need you. Yeah, right. I'm sure they'll have a great partnership.Alessio [00:41:23]: And is Open Operator just, like, a marketing thing for you? Like, how do you think about resource allocation? So, you can spin this up very quickly. And now there's all this, like, open deep research, just open all these things that people are building. We started it, you know. You're the original Open. We're the original Open operator, you know? Is it just, hey, look, this is a demo, but, like, we'll help you build out an actual product for yourself? Like, are you interested in going more of a product route? That's kind of the OpenAI way, right? They started as a model provider and then…Paul [00:41:53]: Yeah, we're not interested in going the product route yet. I view Open Operator as a model provider. It's a reference project, you know? Let's show people how to build these things using the infrastructure and models that are out there. And that's what it is. It's, like, Open Operator is very simple. It's an agent loop. It says, like, take a high-level goal, break it down into steps, use tool calling to accomplish those steps. It takes screenshots and feeds those screenshots into an LLM with the step to generate the right action. It uses stagehand under the hood to actually execute this action. It doesn't use a computer use model. And it, like, has a nice interface using the live view that we talked about, the iframe, to embed that into an application. So I felt like people on launch day wanted to figure out how to build their own version of this. And we turned that around really quickly to show them. And I hope we do that with other things like deep research. We don't have a deep research launch yet. I think David from AOMNI actually has an amazing open deep research that he launched. It has, like, 10K GitHub stars now. So he's crushing that. But I think if people want to build these features natively into their application, they need good reference projects. And I think Open Operator is a good example of that.swyx [00:42:52]: I don't know. Actually, I'm actually pretty bullish on API-driven operator. Because that's the only way that you can sort of, like, once it's reliable enough, obviously. And now we're nowhere near. But, like, give it five years. It'll happen, you know. And then you can sort of spin this up and browsers are working in the background and you don't necessarily have to know. And it just is booking restaurants for you, whatever. I can definitely see that future happening. I had this on the landing page here. This might be a slightly out of order. But, you know, you have, like, sort of three use cases for browser base. Open Operator. Or this is the operator sort of use case. It's kind of like the workflow automation use case. And it completes with UiPath in the sort of RPA category. Would you agree with that? Yeah, I would agree with that. And then there's Agents we talked about already. And web scraping, which I imagine would be the bulk of your workload right now, right?Paul [00:43:40]: No, not at all. I'd say actually, like, the majority is browser automation. We're kind of expensive for web scraping. Like, I think that if you're building a web scraping product, if you need to do occasional web scraping or you have to do web scraping that works every single time, you want to use browser automation. Yeah. You want to use browser-based. But if you're building web scraping workflows, what you should do is have a waterfall. You should have the first request is a curl to the website. See if you can get it without even using a browser. And then the second request may be, like, a scraping-specific API. There's, like, a thousand scraping APIs out there that you can use to try and get data. Scraping B. Scraping B is a great example, right? Yeah. And then, like, if those two don't work, bring out the heavy hitter. Like, browser-based will 100% work, right? It will load the page in a real browser, hydrate it. I see.swyx [00:44:21]: Because a lot of people don't render to JS.swyx [00:44:25]: Yeah, exactly.Paul [00:44:26]: So, I mean, the three big use cases, right? Like, you know, automation, web data collection, and then, you know, if you're building anything agentic that needs, like, a browser tool, you want to use browser-based.Alessio [00:44:35]: Is there any use case that, like, you were super surprised by that people might not even think about? Oh, yeah. Or is it, yeah, anything that you can share? The long tail is crazy. Yeah.Surprising use cases of BrowserbasePaul [00:44:44]: One of the case studies on our website that I think is the most interesting is this company called Benny. So, the way that it works is if you're on food stamps in the United States, you can actually get rebates if you buy certain things. Yeah. You buy some vegetables. You submit your receipt to the government. They'll give you a little rebate back. Say, hey, thanks for buying vegetables. It's good for you. That process of submitting that receipt is very painful. And the way Benny works is you use their app to take a photo of your receipt, and then Benny will go submit that receipt for you and then deposit the money into your account. That's actually using no AI at all. It's all, like, hard-coded scripts. They maintain the scripts. They've been doing a great job. And they build this amazing consumer app. But it's an example of, like, all these, like, tedious workflows that people have to do to kind of go about their business. And they're doing it for the sake of their day-to-day lives. And I had never known about, like, food stamp rebates or the complex forms you have to do to fill them. But the world is powered by millions and millions of tedious forms, visas. You know, Emirate Lighthouse is a customer, right? You know, they do the O1 visa. Millions and millions of forms are taking away humans' time. And I hope that Browserbase can help power software that automates away the web forms that we don't need anymore. Yeah.swyx [00:45:49]: I mean, I'm very supportive of that. I mean, forms. I do think, like, government itself is a big part of it. I think the government itself should embrace AI more to do more sort of human-friendly form filling. Mm-hmm. But I'm not optimistic. I'm not holding my breath. Yeah. We'll see. Okay. I think I'm about to zoom out. I have a little brief thing on computer use, and then we can talk about founder stuff, which is, I tend to think of developer tooling markets in impossible triangles, where everyone starts in a niche, and then they start to branch out. So I already hinted at a little bit of this, right? We mentioned more. We mentioned E2B. We mentioned Firecrawl. And then there's Browserbase. So there's, like, all this stuff of, like, have serverless virtual computer that you give to an agent and let them do stuff with it. And there's various ways of connecting it to the internet. You can just connect to a search API, like SERP API, whatever other, like, EXA is another one. That's what you're searching. You can also have a JSON markdown extractor, which is Firecrawl. Or you can have a virtual browser like Browserbase, or you can have a virtual machine like Morph. And then there's also maybe, like, a virtual sort of code environment, like Code Interpreter. So, like, there's just, like, a bunch of different ways to tackle the problem of give a computer to an agent. And I'm just kind of wondering if you see, like, everyone's just, like, happily coexisting in their respective niches. And as a developer, I just go and pick, like, a shopping basket of one of each. Or do you think that you eventually, people will collide?Future of browser automation and market competitionPaul [00:47:18]: I think that currently it's not a zero-sum market. Like, I think we're talking about... I think we're talking about all of knowledge work that people do that can be automated online. All of these, like, trillions of hours that happen online where people are working. And I think that there's so much software to be built that, like, I tend not to think about how these companies will collide. I just try to solve the problem as best as I can and make this specific piece of infrastructure, which I think is an important primitive, the best I possibly can. And yeah. I think there's players that are actually going to like it. I think there's players that are going to launch, like, over-the-top, you know, platforms, like agent platforms that have all these tools built in, right? Like, who's building the rippling for agent tools that has the search tool, the browser tool, the operating system tool, right? There are some. There are some. There are some, right? And I think in the end, what I have seen as my time as a developer, and I look at all the favorite tools that I have, is that, like, for tools and primitives with sufficient levels of complexity, you need to have a solution that's really bespoke to that primitive, you know? And I am sufficiently convinced that the browser is complex enough to deserve a primitive. Obviously, I have to. I'm the founder of BrowserBase, right? I'm talking my book. But, like, I think maybe I can give you one spicy take against, like, maybe just whole OS running. I think that when I look at computer use when it first came out, I saw that the majority of use cases for computer use were controlling a browser. And do we really need to run an entire operating system just to control a browser? I don't think so. I don't think that's necessary. You know, BrowserBase can run browsers for way cheaper than you can if you're running a full-fledged OS with a GUI, you know, operating system. And I think that's just an advantage of the browser. It is, like, browsers are little OSs, and you can run them very efficiently if you orchestrate it well. And I think that allows us to offer 90% of the, you know, functionality in the platform needed at 10% of the cost of running a full OS. Yeah.Open Operator: Browserbase's Open-Source Alternativeswyx [00:49:16]: I definitely see the logic in that. There's a Mark Andreessen quote. I don't know if you know this one. Where he basically observed that the browser is turning the operating system into a poorly debugged set of device drivers, because most of the apps are moved from the OS to the browser. So you can just run browsers.Paul [00:49:31]: There's a place for OSs, too. Like, I think that there are some applications that only run on Windows operating systems. And Eric from pig.dev in this upcoming YC batch, or last YC batch, like, he's building all run tons of Windows operating systems for you to control with your agent. And like, there's some legacy EHR systems that only run on Internet-controlled systems. Yeah.Paul [00:49:54]: I think that's it. I think, like, there are use cases for specific operating systems for specific legacy software. And like, I'm excited to see what he does with that. I just wanted to give a shout out to the pig.dev website.swyx [00:50:06]: The pigs jump when you click on them. Yeah. That's great.Paul [00:50:08]: Eric, he's the former co-founder of banana.dev, too.swyx [00:50:11]: Oh, that Eric. Yeah. That Eric. Okay. Well, he abandoned bananas for pigs. I hope he doesn't start going around with pigs now.Alessio [00:50:18]: Like he was going around with bananas. A little toy pig. Yeah. Yeah. I love that. What else are we missing? I think we covered a lot of, like, the browser-based product history, but. What do you wish people asked you? Yeah.Paul [00:50:29]: I wish people asked me more about, like, what will the future of software look like? Because I think that's really where I've spent a lot of time about why do browser-based. Like, for me, starting a company is like a means of last resort. Like, you shouldn't start a company unless you absolutely have to. And I remain convinced that the future of software is software that you're going to click a button and it's going to do stuff on your behalf. Right now, software. You click a button and it maybe, like, calls it back an API and, like, computes some numbers. It, like, modifies some text, whatever. But the future of software is software using software. So, I may log into my accounting website for my business, click a button, and it's going to go load up my Gmail, search my emails, find the thing, upload the receipt, and then comment it for me. Right? And it may use it using APIs, maybe a browser. I don't know. I think it's a little bit of both. But that's completely different from how we've built software so far. And that's. I think that future of software has different infrastructure requirements. It's going to require different UIs. It's going to require different pieces of infrastructure. I think the browser infrastructure is one piece that fits into that, along with all the other categories you mentioned. So, I think that it's going to require developers to think differently about how they've built software for, you know

At CES in Las Vegas we got our annual update from Jane Stephenson, Marketing Director for what3words about how their location system continues to evolve and how the usage continues to spread. 

If your local emergency services aren't supporting what3words yet, show them this interview and suggest that they do. Both implementation and understanding how it works are simple, and could save critical minutes or even seconds when responding to a call. Jane demoed a new app that they have partnered with and reviewed recent success stories that illustrate the power of what3words' ability to identify a location to within a few feet in an easy-to-understand way.  Show Notes: Support:      Become a MacVoices Patron on Patreon      http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:      http://macvoices.com      Twitter:      http://www.twitter.com/chuckjoiner      http://www.twitter.com/macvoices      Mastodon:      https://mastodon.cloud/@chuckjoiner      Facebook:      http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:      http://www.facebook.com/macvoices/      MacVoices Group on Facebook:      http://www.facebook.com/groups/macvoice      LinkedIn:      https://www.linkedin.com/in/chuckjoiner/      Instagram:      https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes      Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

This episodes covers how Starlink users can be geolocated and how Cloudflare may help deanonymize users. The increased use of AI helpers leads to leaking data via careless prompts. Geolocation and Starlink https://isc.sans.edu/diary/Geolocation%20and%20Starlink/31612 Discover the potential geolocation risks associated with Starlink and how they might be exploited. This diary entry dives into new concerns for satellite internet users. Deanonymizing Users via Cloudflare https://gist.github.com/hackermondev/45a3cdfa52246f1d1201c1e8cdef6117 Deanonymizing users by identifying which cloudflare server cashed particular content Sage's AI Assistant and Customer Data Concerns https://www.theregister.com/2025/01/20/sage_copilot_data_issue/ Examine how a Sage AI tool inadvertently exposed sensitive customer data, raising questions about AI governance and trust in business applications. The Threat of Sensitive Data in Generative AI Prompts https://www.darkreading.com/threat-intelligence/employees-sensitive-data-genai-prompts Analyze how employees careless prompts to generative AI tools can lead to sensitive data breaches and the importance of awareness training. Homebrew Phishing https://x.com/ryanchenkie/status/1880730173634699393

Level up your vanilla JavaScript with these powerful Web APIs that every developer should know. In this episode, Matt and Mike dive into essential Web APIs that can take your web development skills to the next level. Discover how Web APIs differ from external APIs and explore their powerful capabilities—from manipulating the DOM and fetching data to enabling offline functionality for native app-like uses (ie PWAs). They'll cover must-know APIs like Fetch, Storage, and Service Worker, along with user experience (and native app-like) boosters like Geolocation and Notifications. Tune in to learn practical applications, security tips, and best practices that will help you create fast, interactive, and native-like web apps. Show Notes: https://www.htmlallthethings.com/podcasts/web-apis-that-every-javascript-developer-should-know Thanks to Wix Studio for sponsoring this episode! Check out Wix Studio, the web platform tailored to designers, developers, and marketers via this link: https://www.wix.com/studio

Privacy Commissioner Carly Kind was “surprised” – read underwhelmed – by the first tranche of Privacy Act legislation laid before parliament last month. But she says the hard stuff is still coming after the election, which means businesses now diverting budgets away from compliance to other activities may regret it, especially as the regulator has sharper teeth. Kind says firms are failing under the current Privacy Act – and they are in the regulator's crosshairs. Tracking pixels are under serious scrutiny across the piste, as are companies using data beyond what it was collected for and potentially passing it to third parties. In that vein, Kind has “existing concerns” about loyalty programs, customer data enrichment businesses and data broking: “It's something I'd like to look at again under the current framework,” she says, suggesting those operators “make sure that they're watertight”. Likewise firms targeting via geolocation: “We're looking at a case at the moment … We have some real concerns about how it's being used.” Lookalikes, customer audiences, hashed emails and data clean rooms appear to be in the clear. But under the next wave of reforms “the changing definition of personal information could certainly have an impact,” she says, though for now it's not clear-cut. In the meantime, Kind says there are four areas for businesses to laser in on – including small firms who will no longer be exempt from regulation. First, “know what data you hold and who you're giving it to.” Second, “make sure you've got a retention and destruction regime in place – anything that's old, you don't need to hold it any more.” Next, get into the weeds on contracts with third party service providers and be sure to have a data breach response plan in place. “It's an area of vulnerability we're seeing a lot at the moment,” says Kind. In short: “Don't take your foot off the gas, because we're looking to take a more enforcement-based approach to regulation in the interim.”See omnystudio.com/listener for privacy information.

Looking to learn more about Walmart Onsite and Offsite Display? Join us as we discuss Display Self-Serve, having a seat at the Trade Desk, Metrics and Reporting, and advantages when collaborating with VENDO. Topics Covered: - Key Differences between Walmart Onsite & Offsite (2:34) - Unique Advantages to using Walmart Offsite Display (3:03) - Walmart's Attribution Model (3:51) - How Does Display Self-Serve Work? (4:50) - Having a Trade Desk Seat when working with VENDO (5:40) - What is Walmart Connect & Best Practices (8:10) - Key Benefits & Advantages of Collaborating with VENDO (9:35) - What Creative Capabilities Do Advertisers (12:00) - Recommendations When First Starting (13:18) - Metrics & Reporting (17:39) - How Precise is Geolocation? (18:37) Speakers: - Steph Mai, Walmart Marketing Specialist, VENDO - Chase Snider, Walmart Marketing Specialist, VENDO - Delaney Del Mundo, Director of Amazon Account Strategy, VENDO Want to stay up to date on topics like this? Subscribe to our Amazon & Walmart Growth #podcast for bi-weekly episodes every other Thursday! ➡️ YouTube: https://www.youtube.com/channel/UCr2VTsj1X3PRZWE97n-tDbA ➡️ Spotify: https://open.spotify.com/show/4HXz504VRToYzafHcAhzke?si=9d57599ed19e4362 ➡️ Apple: https://podcasts.apple.com/us/podcast/vendo-amazon-walmart-growth-experts/id1512362107

There's little contention today that the pro-consumer privacy lobby is winning the war over industry on privacy reform - they're informed on industry techniques, loaded with compelling consumer research and aligned entirely on the need for a clampdown on the collection and use of an individual's online data trail. Former NSW Deputy Privacy Commissioner and Salinger Privacy boss Anna Johnston and Choice Consumer Data Advocate, Kate Bower unpack what and why they expect a series of hard, industry-challenging privacy reforms to land in parliament next month - that's less than six weeks away. Just how deeply the $25bn-plus marketing supply chain and tens of thousands of practitioners will be impacted will become clear as the reforms are tabled in Federal Parliament. Johnston and Bower think the updated Act will go harder than anywhere in the world. Hashed emails will be classified as personal information. Trading of geolocation data will be out. Trading of loyalty scheme data – the stuff that powers retail media and a vast targeting-attribution industry – will require companies to prove they have lawful consent to do so and they won't be able to deny services to those that say no. But consent, says Johnston, is a very fragile thing – and companies might actually be best off concentrating on one of the legislation's central tenets: Fair and reasonable use of data. In other words, says Choice's Bower, does what you are doing with customer's data pass “the privacy pub test?” If it does, meeting a very high consent threshold doesn't apply. Right now, most are badly flunking the test. Johnston has a checklist for brands that likely have a 12-month compliance window to get houses in order. But ultimately, she says $50m fines are now in play and that “some product lines and business processes will have to stop … and frankly, that is the point of the reforms.” Cleanrooms, she suggests, may come under intense scrutiny.See omnystudio.com/listener for privacy information.

Moin, passend zum Proide Monat, etwas verspätet eine Folge mit Regenbogenflagge. So gehört es sich.   https://www.rewe.de/rezepte/wuerziger-wurstsalat/   Musik: https://www.youtube.com/watch?v=f0mIJ5Y86bc   Links: https://en.wikipedia.org/wiki/Ashley_Madison https://en.wikipedia.org/wiki/Ashley_Madison_data_breach https://haveibeenpwned.com/PwnedWebsites https://www.theguardian.com/technology/article/2024/jun/04/x-twitter-porn-policy-under-18-opt-in https://www.wired.com/2015/08/happened-hackers-posted-stolen-ashley-madison-data/ https://www.spiegel.de/netzwelt/web/ashley-madison-fast-alle-frauen-profile-sind-fake-a-1050055.html https://torontosun.com/2013/04/12/porn-site-reveals-downloading-habits-of-vatican-city-residents https://www.reddit.com/r/dataisbeautiful/comments/18icl7e/the_2023_pornhub_year_in_review/ https://scottmax.com/pornhub-statistics/ https://media.ccc.de/v/gpn22-309-traut-euch-zivilcourage-zu-zeigen- https://www.dailymail.co.uk/news/article-13475895/father-counselling-buying-daughter-porn-fans-shrink-reveals.html https://www.kidspot.com.au/parenting/i-discovered-my-dad-was-watching-my-onlyfans-thats-not-even-the-worst-part/news-story/2b4bdba91b919447c155947a2616ae89 https://nypost.com/2022/03/25/onlyfans-star-discovers-her-dad-subscribes-to-her-channel/ https://www.reddit.com/r/BrandNewSentence/comments/10bnxg4/onlyfans_model_discovers_dad_pays_for_her_xrated/ https://www.reddit.com/r/confessions/comments/xr18iu/i_dad_subscribed_to_my_daughters_of/   Links für Feedback: Twitter: https://twitter.com/OchmennoP/ Mastodon: @ochmennoPODCAST@literatur.social Email:ochmennopodcast@gmail.com Bewerten: https://podcasts.apple.com/de/podcast/och-menno/id1470581030      

Geolocation is an essential tool to have to be an effective and compliant business in the North American online gaming space. Being able to identify where players are located and whether they are indeed within the state lines is crucial to comply with state laws.With Radar, the geolocation platform provider with years of experience servicing varying sectors now offering its services to the US market, todays episode of iGaming Daily, sponsored by Optimove, see's host and Editor of SBC Americas, Jessica Welman joined by CEO of Radar, Nick Patrick to talk all the latest developments in geolocation, and Radars plans having now moved into the iGaming space.To read more on the topic discussed in today's podcast, click on the following link:https://sbcamericas.com/2024/03/21/radar-geolocation-alternative-us/Host: Jessica WelmanGuests: Nick Patrick, CEO of RadarProducer: Anaya McDonaldEditor: James RossRemember to check out our partners Optimove at https://hubs.la/Q02gLC5L0 or go to optimove.com/sbc to get your first month free when buying the industry's leading customer-loyalty service.

Episode 215:     Let's jump into the show. On Today's show, we welcome Bruce Anderson. Bruce runs Next72 intelligence. He has extensive experience as a private investigator. Using his skill set and his relationships, he has developed a way to Geolocate a subject using Phone applications. This is a great alternative to a cell phone ping. There are so many great use cases for this technology and it is cutting edge. This is a great episode! Please welcome Bruce Anderson and your host, Private Investigator, Matt Spaier  Links:      Matt's email: MatthewS@Satellitepi.com   Linkedin: Matthew Spaier       www.investigators-toolbox.com   Bruce on Linkedin: Bruce Anderson Bruce's email: confidential@thenext72.com Video: https://thenext72.com/geolocation-data 
 
 PI-Perspectives Youtube link:  https://www.youtube.com/channel/UCYB3MaUg8k5w3k7UuvT6s0g Sponsors:     https://piinstitute.com/ https://pi-perspectivesinsurance.com/ https://www.skopenow.com https://www.pacificliability.com/en/athome FBI Tip Line https://tips.fbi.gov/home https://www.fbi.gov/contact-us/field-offices/newyork/about - (212) 384-1000

On this week of Serious Privacy, Paul Breitbarth of Catawiki and Dr. K Royal of Crawford & Company dive deep into the topic of location data, which is considered sensitive personal data and is often not disclosed in many apps. We talk about geopositioning satellites, a journalist investigation into the Polar's fitness app, transparency reports on responses to government requests, such as this one by TMobile, and creative uses such as tracking saguaro cacti in Arizona and raising money for No Kid Hungry. (and a bonus on Beyonce's Texas Hold Em in honor of K's session with Maggie Gloeckle and Ashley Slavik at IAPP Global Privacy Summit in DC and the LGBTQ party with Ron de Jesus themed on Alice in Wonderland... where K might just leverage a little cosplay on the Queen of Heart of Privacy. If you have comments or questions, find us on LinkedIn and IG @seriousprivacy @podcastprivacy @euroPaulB @heartofprivacy and email podcast@seriousprivacy.eu. Rate and Review us! Proudly sponsored by TrustArc. Learn more about NymityAI at https://trustarc.com/nymityai-beta/ #heartofprivacy #europaulb #seriousprivacy #privacy #dataprotection #cybersecuritylaw #CPO #DPO #CISO

This week on Rational Security, Quinta and Scott were joined by Molly Reynolds and (a prerecorded) Anna Bower to talk through some of the week's big national security news, including:“The Shutdown Rut.” Congress once again has the government on the verge of a shutdown. And while Speaker of the House Mike Johnson has reportedly committed to avoiding one, demands from within his caucus may make that hard—just as they continue to obstruct a path forward for the national security supplemental that contains essential assistance for Ukraine. Is there a way forward? Or are we shutdown-bound?“Sex, Lies, and Geolocation.” The criminal case against former President Trump and more than a dozen codefendants in Fulton County, Georgia, remains on hold as defense attorneys continue to dig into the details of Fani Willis's romantic relationship with subordinate Nathan Wade. Over the last week, we've seen filings on geolocation data and the examination of Wade's former attorney. But does any of this add up to a potentially disqualifying conflict of interest?“If This Segment Were a Newspaper, How Much Would It Weigh?” The Supreme Court heard extended oral arguments over the constitutionality of controversial Florida and Texas laws seeking to regulate content moderation on social media platforms this week. But amid some very interesting lines of questioning—including one inquiring the weight of YouTube if it were a newspaper—it wasn't clear the Court was really ready and interested in delving into the technical details. Is that a good thing or a bad thing? And where might the Court come out?For object lessons, Quinta answered Justice Alito's recent inquiry, “If YouTube were a newspaper, how much would it weigh?” Scott sang the praises of Bianco DiNapoli's fire-roasted tomatoes. And Molly recommended the podcast Short Walk, about one of the stranger state-level political controversies in recent memory.Support this show http://supporter.acast.com/lawfare. Hosted on Acast. See acast.com/privacy for more information.

This week, Quinta and Scott were joined by Molly Reynolds and (a prerecorded) Anna Bower to talk through some of the week's big national security news, including:“The Shutdown Rut.” Congress once again has the government on the verge of a shutdown. And while Speaker of the House Mike Johnson has reportedly committed to avoiding one, demands from within his caucus may make that hard—just as they continue to obstruct a path forward for the national security supplemental that contains essential assistance for Ukraine. Is there a way forward? Or are we shutdown-bound?“Sex, Lies, and Geolocation.” The criminal case against former President Trump and more than a dozen codefendants in Fulton County, Georgia, remains on hold as defense attorneys continue to dig into the details of Fani Willis's romantic relationship with subordinate Nathan Wade. Over the last week, we've seen filings on geolocation data and the examination of Wade's former attorney. But does any of this add up to a potentially disqualifying conflict of interest?“If This Segment Were a Newspaper, How Much Would It Weigh?” The Supreme Court heard extended oral arguments over the constitutionality of controversial Florida and Texas laws seeking to regulate content moderation on social media platforms this week. But amid some very interesting lines of questioning—including one inquiring the weight of YouTube if it were a newspaper—it wasn't clear the Court was really ready and interested in delving into the technical details. Is that a good thing or a bad thing? And where might the Court come out?For object lessons, Quinta answered Justice Alito's recent inquiry, “If YouTube were a newspaper, how much would it weigh?” Scott sang the praises of Bianco DiNapoli's fire-roasted tomatoes. And Molly recommended the podcast Short Walk, about one of the stranger state-level political controversies in recent memory. Hosted on Acast. See acast.com/privacy for more information.

In episode 86 of The Payments Show Podcast, I spoke to Jonathan Tomek who is the Vice President of Research & Development at Digital Element.   Digital Element empowers businesses to extract actionable insights from a consumer's internet connection, leveraging their IP address. These insights encompass location, connection type, demographic data, VPN usage, and proxy details. By harnessing this data, businesses can enhance ad targeting precision, optimize content localization, and mitigate online fraud.VIDEO and PDF Transcript: - click here https://thepaymentsshow.substack.com/p/86Summary of topics discussed:(00:00) - Start and Introduction(01:31) - VPN Stats and Their Implications(03:32) - How Do You Find the True Location of a VPN User?(05:19) - Non-human Internet Traffic: Proxies(07:48) - Additional IP Insights: Carrier Databases, Demographics and More(09:46) - IP Characteristics: Evolution of IP Addresses Over Time(11:30) - TOR, Anonymity and the Darknet(14:15) - Customers Using Digital Element: Context Is Key(18:46) - Overview of the Solution(21:11) - Strict Payment Processing Rules Don't Solve All Problems(24:16) - Next Steps: Getting Started with Digital Element(25:17) - New Threats: Connected TV Ad Fraud and Bots(28:22) - Threats from IoT Devices(35:09) - Chit Chat(36:15) - THOTCON Hacking Conference, ChicagoAnd much more…Details:- Recorded on 8 Feb 2024- Host: Satwant Phull- Guest: Jonathan Tomek, VP of R&D, Digital Element[Next Steps]- Get in touch with Satwant: digitalmoneylab.com - Digital Element: digitalelement.com

From DuckDuckGo's innovative approach to secure synchronization of user data across devices, to Appdome's cutting-edge Geo Compliance suite aimed at combating location spoofing, and the alarming resurgence of the Bumblebee malware loader in a new phishing campaign, we explore the implications of these advancements and threats. Join us as we unpack the significance of end-to-end encryption, the fight against location-based fraud, and the continuous battle against sophisticated cyber threats. Discover how these developments impact our digital lives and what measures can be taken to enhance security in the digital realm. DuckDuckGo's Privacy Innovation: Learn about DuckDuckGo's end-to-end encrypted Sync & Backup feature, providing users with a secure way to synchronize their data across devices without compromising privacy. Read more. Appdome's Battle Against Location Spoofing: Dive into Appdome's Geo Compliance suite, offering mobile brands a robust solution to verify user locations and detect fraudulent activities to uphold the integrity of mobile commerce. Read more. The Return of Bumblebee: Uncover the details of Bumblebee's comeback in a sophisticated phishing campaign, posing significant threats to organizational security and how these developments signal a broader wave of cyber threats. Read more. Stay informed about the latest in cybersecurity and digital privacy with our in-depth analysis and discussions on the most pressing issues facing the digital world today. Thanks to Jered Jones for providing the music for this episode. https://www.jeredjones.com/ Transcript: [ 00:00:00] Good morning listeners today is February 15th, 2024. And you're listening to the daily decrypt. I've got a quick episode for you today. We're just going to touch on a three stories. One duck, duck go has some new updates, which we're pretty excited about. A company called app dome is re-inventing geo compliance for mobile security. And for the nerdier folk, the bumblebee is back. This is a new wave of cyber threats. So let's dive right in. [00:01:00] All right. So our first article comes from bleeping computer and it discusses duck. Duck goes introduction. Of an end to end encrypted sync and backup feature for their privacy centric browser. Dr. Goh has been a beacon for those seeking to protect their online activities from prying eyes. And it's known for its search engine that promises not to track users. Its latest update, introduces a sync and backup feature, which allows users to securely synchronize bookmarks passwords and email protection settings without the need for an account. Or by revealing any sensitive information to duck, duck go. We love this. This is a huge step towards separating your identity from what you do on the internet. So what sets this feature apart is its use of end-to-end encryption. And for those of you who aren't super savvy in the tech field, this means that. The data is encrypted in such a way that only the user can access it. Not even duck duck go can peek into the transferred information. This [00:02:00] ensures that personal data like passwords and bookmarks remain private and secure. Which is a significant step forward in preserving user privacy online. Duck duck go employs local encryption to store sensitive data on the user's device. And during synchronization between devices, this data remains encrypted. And because the decryption key is stored locally on your devices, your information is inaccessible to anyone, but you. Little caveat to that is. Your information is inaccessible to anyone, but you or anyone who has access to your devices. Make sure your devices are password protected. And go to sleep or lock after a reasonable amount of time. One minute might be too quick. Five minutes might be too quick, but. Get in the habit of locking your devices when you walk away from them. Another feature of this is the easy setup. Users can sync their data by scanning a QR code or entering a text code, bridging their digital life across windows, Mac iOS, iOS, and Android devices seamlessly. duck Duck go provides recovery codes in a PDF document, ensuring that [00:03:00] users can retrieve their data, even if their device is lost or stolen. We don't love QR codes overall, but if it's being provided by duck, duck, go. You should be pretty safe. Attackers will also have this information, so they might try to generate fake QR codes or fake PDFs, but I've never really seen syncing across devices without creating an account. So I'm pretty excited to give this a try if you're also excited to give this a try. The duck duck go browser is available for download on various platforms. Though the browser is still in beta. It's still very accessible. So go out there, give it a shot and let us know what you think on Twitter or Instagram. We'd love to hear from you. So up next, we're talking about a company. called app dome, which might be behind many of your apps already on your phone. They. Provide security features for apps across Android and iOS. This can mean security features such as end-to-end automation. [00:04:00] Mobile apps, security anti-fraud anti-malware anti-China antibody and geo compliance. Their sites are focused on the geo compliance part of that. they've come up with a groundbreaking feature set, which is designed to help mobile brands, verify user locations and detect fraudulent activities such as location spoofing. Or fake GPS, app usage, VPNs, and SIM swaps. These are common methods that are often employed to bypass geographical restrictions and mobile applications, which can pose a significant challenge to maintaining the integrity of mobile commerce and transaction data. This is great, but. I have to point out the irony of discussing this right after talking about not being tracked online. By duck, duck go. Geolocation is a tough thing to nail down. IP addresses are wildly inaccurate. And yeah, your location can be mapped using different apps. Like VPNs or. All kinds of other things. So this is huge for. Government regulation of data, [00:05:00] privacy, but might be bad news for protecting yourself and your privacy online. Tom Tovar, who is the CEO of abdom discusses? The struggle mobile brands face. In achieving true geo compliance. Traditional products in this space have suffered from a fragmented approach requiring complex software development, kit integrations, and a heavy lift from engineering teams. solution. A unified automated platform that integrates geo compliance with over 300 other mobile app defense features, streamlining the process and ensuring compatibility across the board. this next piece is drawing attention to recent activities of the notorious malware loader and initial access broker known as bumblebee. Bumblebee is back and its resurgence is marked by a sophisticated phishing campaign targeting us organizations with cleverly disguised. Voicemail themes, lures leading to malicious one drive URLs. So watch out for. Suspicious looking voicemails. And if you do [00:06:00] happen to click on one. it opens one drive. You know what to do. Proof point and enterprise security firm has traced these activities. Noting that the malicious URLs guide unsuspecting victims to a word document that impersonates the consumer electronics company humane. That's not very humane of them. These documents named in a deceptive manner like release Evans, hashtag 96 dot doc. Employ VBA macros to execute a chain of commands that eventually download and run the bumblebee loader. This development is particularly alarming considering Bumblebee's reputation for downloading and executing ransomware among other malicious payloads. bumblebee was first identified in March of 2022 and has been a tool for various crime where actors replacing older loaders, such as Basel loader. It's development is suspected to be under the wings of the Conti and trick bot cyber crime syndicates showcasing a continuous evolution in cyber crime tactics. Interestingly the return of bumblebee coincides with the [00:07:00] reappearance of malware variants, like crackpot, Xeloda, and Pika bot. Which is highlighting a broader wave of cyber threats. There's a lot of vulnerabilities that involve Microsoft office macros. So keep an eye out for. A office template you might download for free on the internet that when you open it, it prompts you to enable macros. It is going to try to convince you that you need to enable these macros to use this template. But I would advise against enabling macros since that pretty much gives. The word document. The ability to launch other programs to run code, to do anything that malware would need to do. Download a template. It asks you to enable macros, probably delete that template and look on a different site. Microsoft has also taken steps to disable macros in an unsecure way, but there's always ways around it. The article we're referencing also touches on a broader context with Malwarebytes uncovering phishing campaigns that mimic financial institutions. Tricking individuals into [00:08:00] downloading legitimate remote desktop software. Like any desk under false pretenses further enabling cyber criminals to exploit unsuspecting users. All right. So that's all we got for today, Thank you so much for listening. Give us a tweet if you like, what you've heard. We'd love to hear from you on Instagram. We're posting little highlight reels. And Yeah, your recommendation means a lot to us. So send this podcast to a friend. If you thought it was fun or valuable or anything. Talk to you more tomorrow.

He shares insights on geolocating trucks in vast factory yards. His solution makes managing hundreds of trucks seamless, bringing immense value to Volvo Group's business operations. Watch the full episode here

How do you sell a virtual consult to a reluctant patient? Maybe someone who's technologically challenged? In my practice, when a patient calls to make an appointment, we walk them through the advantages of using the JetVC app, encouraging even the most resistant patients to say YES to a virtual consult. So, what does our call center script look like? And how do we communicate with patients once we've sold them on JetVC? On this episode of Dentist Brian Candy, we continue our discussion of JetVC.ai, looking at the texting, geolocation and virtual consult features of the app. I explain how we communicate with patients via SMS as well as the JetVC app, using AI to avoid texting sensitive, healthcare specific patient information. We cover how the app uses geolocation for patient check-in and why we still ask patients to schedule an appointment over the phone. Listen in for insight on the case types that aren't amenable to a virtual consult and learn how to explain the benefits of JetVC to reluctant patients. Key Takeaways How we communicate with patients via text message and the JetVC app How JetVC uses AI to avoid texting sensitive patient information Why we communicate healthcare specific information to through the app How the app uses geolocation for patient check-in Why we still ask patients to make an appointment over the phone The only 2 reasons we would not conduct a virtual consult for a patient Our script for explaining the benefits of a virtual consult to reluctant patients How we approach virtual consults for the technologically challenged Which case types are amenable to virtual consults (and which ones are not) Connect with Dr. Bryan McLelland Dentist Brain Candy  Dentist Brain Candy on Facebook Dentist Brain Candy on YouTube Dentist Brain Candy Podcast Dentist Brain Candy App Dentist Brain Candy Continuing Education About Dr. Bryan McLelland Dr. Jawbreaker on YouTube Email bryanmclelland@hotmail.com  Call (509) 922-2273 Resources JetVC.ai

Geolocation, misinformation, verification… we answer your questions on how the BBC monitors and reports on the most important events of the war in Ukraine.Olga Robinson, an editor at BBC Monitoring and Verify specialising in Russian disinformation, and Francis Scarr, a journalist at BBC Monitoring, join Vitaly in the Ukrainecast studio and reveal all.Today's episode is presented by Vitaly Shevchenko. The producers were Clare Williamson, Arsenii Sokolov, Ivana Davidovic and Keiligh Baker. The technical producer was Jack Graysmark. The series producer is Lucy Boast. The senior news editor is Sam Bonham. Email Ukrainecast@bbc.co.uk with your questions and comments. You can also send us a message or voice note via WhatsApp, Signal or Telegram to +44 330 1239480

Ever wondered how to make the most of data analysis tools like iOS Spotlight Store DB and Realm Databases? We're here to share our experiences, tips, and favorite resources to help you elevate your data extraction skills. Join us, as we discuss the amazing work of Yogesh Khatri, the creator of a game-changing parser and as we guide you through the vast world of data extraction and analysis techniques.We begin our journey with iOS Spotlight Store DB, revealing the treasures hidden within and how to use Yogesh's parser to uncover its secrets. We then navigate through Realm Databases, sharing our encounters with data stores and tools for parsing extracted data. We also share our personal workflow process, granting you a peek into our data analysis strategies. But we're not done yet. Our adventure takes a detour towards Google Maps Geolocation Artifacts, where we highlight the amazing work of The Binary Hick and his research of the audio files and geolocation points related to navigation.Finally, we explore the nuanced art of analyzing timestamps and locations in images, revealing a fascinating intersection of data and intent. We share how we use Python scripts, manual offsets, and more to make data time-zone aware. Wrapping up our discussion, we emphasize the vitality of research in data analysis and the role of code in automation. So, buckle up for a thrilling ride into the mesmerizing world of data extraction and analysis. You'll come out the other side armed with fresh insights and new tools at your disposal.Notes:iOS Spotlight store.db:https://github.com/ydkhatri/spotlight_parserRealm Databases:https://www.mongodb.com/docs/realm/studio/The Binary Hick-Finding Phones with Google Maps:https://thebinaryhick.blog/2023/10/17/finding-phones-with-google-maps-part-1-android/iOS Media Adjustments:https://www.doubleblak.com/blogPosts.php?id=23

A WPProAtoZHost.com Company.... It's Episode 612 and we have plugins for Bottoming Out & Geolocation... and WordPress News. It's all coming up on WordPress Plugins A-Z! The post Don't Get Stung by Bad WordPress Plugins appeared first on WordPress Plugins A to Z.

It's Episode 612 and we have plugins for Bottoming Out & Geolocation... and WordPress News. It's all coming up on WordPress Plugins A-Z! For more articles visit WordPress Specialist with a focus on... - WordPress Training, Classes and Emergency Support... for more articles like Don’t Get Stung by Bad WordPress Plugins.

We discuss recent Bellingcat reports on whether AI has the capability to reliably identify AI. The reporter and fellow shares his research on AI for OSINT and the results.Key takeawaysTesting AI's ability to recognize AI artBlending journalism and OSINT at BellingcatHow machine learning should and shouldn't be used in OSINTAbout Dennis KovtunDennis Kovtun is a freelance journalist with interest in OSINT and a 2023 Bellingcat Summer Fellow. Further readingTesting AI or Not: How Well Does an AI Image Detector Do Its Job?Can AI Chatbots Be Used for Geolocation?Dennis Kovtun's website

Producers Aubrey and Shannon review the latest articles and research on using AI in OSINT. Should you consider using AI chatbots in research now or in the future? And if so, how can you do so securely and with verification in mind?Key takeawaysAI chatbots aren't great at OSINT right now, but they might be one dayVerification is keyYou need an access policyReferences from the showCriminals Have Created Their Own ChatGPT Clones from WiredCan AI Chatbots Be Used for Geolocation? from BellingcatBest practices for creating a dark web access policy

The Smoke Loader botnet has a creepy new payload. Ransomware gets faster. How AI has evolved in malicious directions. The Snatch ransomware gang threatens to snitch. The FSB continues to use both USBs and phishing emails as attack vectors. A ransomware attack shutters Belgian social service offices. Tim Starks from the Washington Post explains a Biden administration win in a DC court. Our guest Ben Sebree of CivicPlus describes how the public sector could combat cybercrime during cloud adoption. And the deadline for comment on US cybersecurity regulations? It's been extended. For links to all of today's stories check out our CyberWire daily news briefing: https://thecyberwire.com/newsletters/daily-briefing/12/161 Selected reading. Smoke Loader Drops Whiffy Recon Wi-Fi Scanning and Geolocation Malware (SecureWorks)  Time keeps on slippin' slippin' slippin': The 2023 Active Adversary Report for Tech Leaders (Sophos News)  HP Wolf Security Threat Insights Report Q2 2023 | HP Wolf Security (HP Wolf Security)  Barracuda XDR Insights: How AI learns your patterns to protect you (Barracuda) Deep Instinct Study Finds Significant Increase in Cybersecurity Attacks Fueled by Generative AI (Deep Instinct)  Cyberattack on Belgian social service centers forces them to close (Record) Ukraine's Military Hacked by Russian Backed USB Malware (Ophtek) Request for Information on Cyber Regulatory Harmonization; Request for Information: Opportunities for and Obstacles To Harmonizing Cybersecurity Regulations (Federal Register) Learn more about your ad choices. Visit megaphone.fm/adchoices

Microsoft's dirty old API games, the new, even more restrictive rules Apple developers will now have to follow, and why Google's "Web Integrity API" seems gross.

In this episode, Caitlin Chin speaks with Nathan Freed Wessler, deputy director of the ACLU's Speech, Privacy, and Technology Project, about how technological advancements have shifted the U.S. government's relationship with the private sector. Nate and Caitlin talk about how government agencies access cell phone location data and face images, as well as some related privacy, civil liberties, and free speech considerations. For additional resources on this topic, check out: Surveillance for Sale: The Underregulated Relationship between U.S. Data Brokers and Domestic and Foreign Government Agencies (CSIS): https://www.csis.org/analysis/surveillance-sale New Records Detail DHS Purchase and Use of Vast Quantities of Cell Phone Location Data (ACLU): https://www.aclu.org/news/privacy-technology/new-records-detail-dhs-purchase-and-use-of-vast-quantities-of-cell-phone-location-data Privacy & Technology (ACLU): https://www.aclu.org/issues/privacy-technology

This week's guest is Jeff Jockisch, Partner at Avantis Privacy and co-host of the weekly LinkedIn Live event, Your Bytes = Your Rights, a town hall-style discussion around ownership, digital rights, and privacy. Jeff is currently a data privacy researcher at PrivacyPlan, where he focuses specifically on privacy data sets. In this conversation, we delve into current risks to location privacy; how precise location data really is; how humans can have more control over their data; and what organizations can do to protect humans' data privacy. For access to a dataset of data resources and privacy podcasts, check out Jeff's robust database — the Shifting Privacy Left podcast was recently added.Topics Covered:Jeff's approach to creating privacy data sets and what “gaining insight into the privacy landscape” means.How law enforcement can be a threat actor to someone's privacy, using the example of Texas' abortion lawWhether data brokers are getting exact location information or are inferring someone's location.Why geolocation brokers had not considered themselves data brokers.Why anonymization is insufficient for location privacy. How 'consent theater' coupled with location leakage is an existential threat to our privacy.How people can protect themselves from having data collected and sold by data and location brokers.Why apps permissions should be more specific when notifying users about personal data collection and use. How Apple and Android devices treat Mobile Ad ID (MAID) differently and how that affects your historical location data.How companies can protect data by using broader geolocation information instead of precise geolocation information. More information about Jeff's LinkedIn Live show, Your Bytes = Your Rights.Resources Mentioned:Avantis PrivacyPrivacy PlanThreat modeling episode with Kim Wuyts"Your Bytes = Your Rights" LinkedIn LiveThe California Delete ActPrivacy Podcast DatabaseContaining Big Tech Guest Info:Follow Jeff on LinkedIn Privado.ai Privacy assurance at the speed of product development. Get instant visibility w/ privacy code scans.Shifting Privacy Left Media Where privacy engineers gather, share, & learnDisclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.Copyright © 2022 - 2024 Principled LLC. All rights reserved.

Episode brought to you by Trend & Finaloop.On this episode of DTC POD, Frank joins blaine to chat about how e-commerce companies can use AI models to personalize the shopping experience for each individual shopper. They talk about how ML automation and AI can enrich the product side by considering factors such as color, category, and weight to predict the behavior of shoppers in real time. They discuss the importance of having good data management and collecting as much non-PII customer event data as possible which will make them more agile and competitive in leveraging AI components later on, and thinking deeply about product catalog attributes and categories. Key themes discussed include:1. Personalized shopping experiences2. Advancements in AI and ML3. Making AI accessible to all4. Language models for consumer use cases5. AI for e-commerce conversion optimization6. Importance of human oversight in AI7. Importance of data management for AITimestamps[00:05:04] Recent surge in AI due to generative models; open AI major player.[00:09:38] Prediction and automation are ultimate goals with countless use cases.[00:14:26] XGen AI enables user-controlled ML systems for transparency and democratization.[00:20:50] E-commerce requires AI-powered tools to optimize customer experience for product recommendations.[00:28:51] User prediction pipelines create personalized shopping experiences that adapt to activities.[00:34:04] Data organization for Shopify Plus crucial for ML; deep analysis important.[00:41:05] Focus on partnerships for ML education; customize services; AI should automate repetitive interactions.[00:46:36] Need for accessible education on AI tools for the average person. Shownotes powered by CastmagicP.S. Get our pod highlights delivered directly to your inbox with the DTC Pod Newsletter! Episode brought to you by Finaloop, the real-time accounting service trusted by hundreds of DTC Brands. Try Finaloop free - no credit card required. Visit finaloop.com/dtcpod and get 14 days free and a 2-month P&L within 24 hours.Past guests & brands on DTC Pod include Gilt, PopSugar, Glossier, MadeIN, Prose, Bala, P.volve, Ritual, Bite, Oura, Levels, General Mills, Mid Day Squares, Prose, Arrae, Olipop, Ghia, Rosaluna, Form, Uncle Studios & many more.Additional episodes you might like:• #175 Ariel Vaisbort - How OLIPOP Runs Influencer, Community, & Affiliate Growth• #184 Jake Karls, Midday Squares - Turning Your Brand Into The Influencer With Content• #205 Kasey Stewart: Suckerz- - Powering Your Launch With 300 Million Organic Views• #219 JT Barnett: The TikTok Masterclass For Brands• #223 Lauren Kleinman: The PR & Affiliate Marketing Playbook• ​​​​#243 Kian Golzari - Source & Develop Products Like The World's Best Brands-----Have any questions about the show or topics you'd like us to explore further?Shoot us a DM; we'd love to hear from you.Want the weekly TL;DR of tips delivered to your mailbox?Check out our newsletter hereFollow us for content, clips, giveaways, & updates!DTCPod InstagramDTCPod TwitterDTCPod TikTokFrank Faricy - Founder and CEO of XGenRamon Berrios - CEO of Trend.ioBlaine Bolus - Co-Founder of Seated

On this episode of Rehash, we sit down with Keiran Sim, co-founder of Mirage to talk about augmented reality. We dive into everything Keiran is working on at Mirage, including AR social, persistent AR, the intersection of AR and web3, and the value of collecting digital media. He shares what Mirage is doing to combat harmful content as well as how Mirage is embracing decentralization, and we look to the future as Keiran shares his vision for AR in the coming years.  COLLECT THIS EPISODEhttps://www.rehashweb3.xyz/ FOLLOW USRehash: https://twitter.com/rehashweb3Diana: https://twitter.com/ddwchenKeiran: https://twitter.com/keirsimMirage: https://twitter.com/thismirage EDITORSEllie: https://twitter.com/elliedotsTyler: https://twitter.com/tylerinternet SPONSORSLens Protocol: https://lens.xyzAmbire Wallet: https://www.ambire.com/NFT.Storage: https://twitter.com/NFTdotStorage LINKSHYPER REALITY by Keiichi Matsuda: https://youtu.be/YJg02ivYzSs TIMESTAMPS0:00 Intro5:48 What is Augmented Reality?9:15 AR vs. VR9:57 AR Social16:28 Mirage20:34 Sensoring harmful content22:51 Decentralizing Mirage28:25 Why collect digital media?31:43 The future of AR35:17 Closing thoughts37:18 Diana's Game39:03 Follow Keiran DISCLAIMER: The information in this video is the opinion of the speaker(s) only and is for informational purposes only. You should not construe it as investment advice, tax advice, or legal advice, and it does not represent any entity's opinion but those of the speaker(s). For investment or legal advice, please seek a duly licensed professional.

The podcast discusses how Alex Cox's cell phone data led investigators to the remains of Lori Vallow's children, Tylee Ryan and Joshua "JJ" Vallow. Geolocation data from Cox's phone was used to trace his movements, revealing that he had been at the burial site on the days the children were last seen alive. This crucial piece of evidence played a significant role in solving the case and implicating both Lori Vallow and her husband, Chad Daybell, in the tragic deaths of the children. Want to listen to ALL of our Podcasts Ad-Free? Subscribe through Apple Podcasts, and try it for 3 days free: https://tinyurl.com/ycw626tj Follow Our Other Cases:   Hidden Killers With Tony Brueski (All Cases) - https://audioboom.com/channels/5040505-hidden-killers-with-tony-brueski-breaking-news-commentary Chad & Lori Daybell - https://audioboom.com/channels/5098105-demise-of-the-daybells-the-lori-chad-daybell-story The Murder of Ana Walshe - https://audioboom.com/channels/5093967-finding-ana-this-disappearance-of-ana-walshe Alex Murdaugh - https://audioboom.com/channels/5097527-the-trial-of-alex-murdaugh The Idaho Murders, The Case Against Bryan Kohberger - https://audioboom.com/channels/5098223-the-idaho-murders-the-case-against-bryan-kohberger Lucy Letby - https://audioboom.com/channels/5099406-nurse-of-death-the-lucy-letby-story Follow Tony Brueski On Twitter https://twitter.com/tonybpod Join our Facebook Discussion Group: https://www.facebook.com/groups/834636321133

The podcast discusses how Alex Cox's cell phone data led investigators to the remains of Lori Vallow's children, Tylee Ryan and Joshua "JJ" Vallow. Geolocation data from Cox's phone was used to trace his movements, revealing that he had been at the burial site on the days the children were last seen alive. This crucial piece of evidence played a significant role in solving the case and implicating both Lori Vallow and her husband, Chad Daybell, in the tragic deaths of the children. Want to listen to ALL of our Podcasts Ad-Free? Subscribe through Apple Podcasts, and try it for 3 days free: https://tinyurl.com/ycw626tj Follow Our Other Cases:   Hidden Killers With Tony Brueski (All Cases) - https://audioboom.com/channels/5040505-hidden-killers-with-tony-brueski-breaking-news-commentary Chad & Lori Daybell - https://audioboom.com/channels/5098105-demise-of-the-daybells-the-lori-chad-daybell-story The Murder of Ana Walshe - https://audioboom.com/channels/5093967-finding-ana-this-disappearance-of-ana-walshe Alex Murdaugh - https://audioboom.com/channels/5097527-the-trial-of-alex-murdaugh The Idaho Murders, The Case Against Bryan Kohberger - https://audioboom.com/channels/5098223-the-idaho-murders-the-case-against-bryan-kohberger Lucy Letby - https://audioboom.com/channels/5099406-nurse-of-death-the-lucy-letby-story Follow Tony Brueski On Twitter https://twitter.com/tonybpod Join our Facebook Discussion Group: https://www.facebook.com/groups/834636321133

Kyle, Matt, and Linda have a lively discussion with Peter J. Williams about his book "Can We Trust the Gospels?" Dr. Williams tells us the importance of being able to trust the Gospels, and how they help us know we can trust all of Scripture. Matt engages with Dr. Williams in a discussion about how geolocation helps confirm the stories of Jesus as told in the Gospels. Linda asks a helpful question about so-called contradictions, and Dr. Williams provides a helpful way for us to discuss paradox with our students. He also encourages us to stretch our students academically far more than we often think they can handle.

(00:00) Boston Boxing hero Danny O'Connor joins Toucher & Rich to talk about his long-awaited return to the ring in a super welterweight clash against Luis ‘Vicious' Garcia on March 16th.(23:39) Opening Weekend for Massachusetts Sports Betting had 8.1 million Geolocation transactions and 400,000 online sports betting accounts opened.(29:33) THE STACKCONNECT WITH TOUCHER & RICH https://twitter.com/toucherandrich https://twitter.com/fredtoucher https://twitter.com/KenGriffeyRuleshttps://www.instagram.com/Toucherandrichofficial https://www.instagram.com/fredtoucher https://www.twitch.tv/thesportshub https://www.instagram.com/985thesportshub https://twitter.com/985thesportshub https://www.facebook.com/985TheSportsHub

Senators show concern about how the FBI collected geolocation data without going through normal procedures. Google pays out a large settlement relating to how the company handled location tracking. Plus we have stories about facial recognition tech, how Tesla is under scrutiny for accidents (and for steering wheels popping off of SUVs) and more.See omnystudio.com/listener for privacy information.

Nullification Movement News, Episode 6. Reports include: -Sound Money, anti-CBDC bill passes Missouri Senate -Taking on Geolocation tracking and Gun Purchase Surveillance -Nullifying Federal Gun Control The post Nullify the Fed and a CBDC and ATF too first appeared on Tenth Amendment Center.

About RamDr. Ram Sriharsha held engineering, product management, and VP roles at the likes of Yahoo, Databricks, and Splunk. At Yahoo, he was both a principal software engineer and then research scientist; at Databricks, he was the product and engineering lead for the unified analytics platform for genomics; and, in his three years at Splunk, he played multiple roles including Sr Principal Scientist, VP Engineering and Distinguished Engineer.Links Referenced: Pinecone: https://www.pinecone.io/ XKCD comic: https://www.explainxkcd.com/wiki/index.php/1425:_Tasks TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: This episode is sponsored in part by our friends at Chronosphere. Tired of observability costs going up every year without getting additional value? Or being locked into a vendor due to proprietary data collection, querying, and visualization? Modern-day, containerized environments require a new kind of observability technology that accounts for the massive increase in scale and attendant cost of data. With Chronosphere, choose where and how your data is routed and stored, query it easily, and get better context and control. 100% open-source compatibility means that no matter what your setup is, they can help. Learn how Chronosphere provides complete and real-time insight into ECS, EKS, and your microservices, wherever they may be at snark.cloud/chronosphere that's snark.cloud/chronosphere.Corey: This episode is brought to you in part by our friends at Veeam. Do you care about backups? Of course you don't. Nobody cares about backups. Stop lying to yourselves! You care about restores, usually right after you didn't care enough about backups. If you're tired of the vulnerabilities, costs, and slow recoveries when using snapshots to restore your data, assuming you even have them at all living in AWS-land, there is an alternative for you. Check out Veeam, that's V-E-E-A-M for secure, zero-fuss AWS backup that won't leave you high and dry when it's time to restore. Stop taking chances with your data. Talk to Veeam. My thanks to them for sponsoring this ridiculous podcast.Corey: Welcome to Screaming in the Cloud. I'm Corey Quinn. Today's promoted guest episode is brought to us by our friends at Pinecone and they have given their VP of Engineering and R&D over to suffer my various sling and arrows, Ram Sriharsha. Ram, thank you for joining me.Ram: Corey, great to be here. Thanks for having me.Corey: So, I was immediately intrigued when I wound up seeing your website, pinecone.io because it says right at the top—at least as of this recording—in bold text, “The Vector Database.” And if there's one thing that I love, it is using things that are not designed to be databases as databases, or inappropriately referring to things—be they JSON files or senior engineers—as databases as well. What is a vector database?Ram: That's a great question. And we do use this term correctly, I think. You can think of customers of Pinecone as having all the data management problems that they have with traditional databases; the main difference is twofold. One is there is a new data type, which is vectors. Vectors, you can think of them as arrays of floats, floating point numbers, and there is a new pattern of use cases, which is search.And what you're trying to do in vector search is you're looking for the nearest, the closest vectors to a given query. So, these two things fundamentally put a lot of stress on traditional databases. So, it's not like you can take a traditional database and make it into a vector database. That is why we coined this term vector database and we are building a new type of vector database. But fundamentally, it has all the database challenges on a new type of data and a new query pattern.Corey: Can you give me an example of what, I guess, an idealized use case would be of what the data set might look like and what sort of problem you would have in a vector database would solve?Ram: A very great question. So, one interesting thing is there's many, many use cases. I'll just pick the most natural one which is text search. So, if you're familiar with the Elastic or any other traditional text search engines, you have pieces of text, you index them, and the indexing that you do is traditionally an inverted index, and then you search over this text. And what this sort of search engine does is it matches for keywords.So, if it finds a keyword match between your query and your corpus, it's going to retrieve the relevant documents. And this is what we call text search, right, or keyword search. You can do something similar with technologies like Pinecone, but what you do here is instead of searching our text, you're searching our vectors. Now, where do these vectors come from? They come from taking deep-learning models, running your text through them, and these generate these things called vector embeddings.And now, you're taking a query as well, running them to deep-learning models, generating these query embeddings, and looking for the closest record embeddings in your corpus that are similar to the query embeddings. This notion of proximity in this space of vectors tells you something about semantic similarity between the query and the text. So suddenly, you're going beyond keyword search into semantic similarity. An example is if you had a whole lot of text data, and maybe you were looking for ‘soda,' and you were doing keyword search. Keyword search will only match on variations of soda. It will never match ‘Coca-Cola' because Coca-Cola and soda have nothing to do with each other.Corey: Or Pepsi, or pop, as they say in the American Midwest.Ram: Exactly.Corey: Yeah.Ram: Exactly. However, semantic search engines can actually match the two because they're matching for intent, right? If they find in this piece of text, enough intent to suggest that soda and Coca-Cola or Pepsi or pop are related to each other, they will actually match those and score them higher. And you're very likely to retrieve those sort of candidates that traditional search engines simply cannot. So, this is a canonical example, what's called semantic search, and it's known to be done better by these other vector search engines. There are also other examples in say, image search. Just if you're looking for near duplicate images, you can't even do this today without a technology like vector search.Corey: What is the, I guess, translation or conversion process of existing dataset into something that a vector database could use? Because you mentioned it was an array of floats was the natural vector datatype. I don't think I've ever seen even the most arcane markdown implementation that expected people to wind up writing in arrays of floats. What does that look like? How do you wind up, I guess, internalizing or ingesting existing bodies of text for your example use case?Ram: Yeah, this is a very great question. This used to be a very hard problem and what has happened over the last several years in deep-learning literature, as well as in deep-learning as a field itself, is that there have been these large, publicly trained models, examples will be OpenAI, examples will be the models that are available in Hugging Face like Cohere, and a large number of these companies have come forward with very well trained models through which you can pass pieces of text and get these vectors. So, you no longer have to actually train these sort of models, you don't have to really have the expertise to deeply figured out how to take pieces of text and build these embedding models. What you can do is just take a stock model, if you're familiar with OpenAI, you can just go to OpenAIs homepage and pick a model that works for you, Hugging Face models, and so on. There's a lot of literature to help you do this.Sophisticated customers can also do something called fine-tuning, which is built on top of these models to fine-tune for their use cases. The technology is out there already, there's a lot of documentation available. Even Pinecone's website has plenty of documentation to do this. Customers of Pinecone do this [unintelligible 00:07:45], which is they take piece of text, run them through either these pre-trained models or through fine-tuned models, get the series of floats which represent them, vector embeddings, and then send it to us. So, that's the workflow. The workflow is basically a machine-learning pipeline that either takes a pre-trained model, passes them through these pieces of text or images or what have you, or actually has a fine-tuning step in it.Corey: Is that ingest process something that not only benefits from but also requires the use of a GPU or something similar to that to wind up doing the in-depth, very specific type of expensive math for data ingestion?Ram: Yes, very often these run on GPUs. Sometimes, depending on budget, you may have compressed models or smaller models that run on CPUs, but most often they do run on GPUs, most often, we actually find people make just API calls to services that do this for them. So, very often, people are actually not deploying these GPU models themselves, they are maybe making a call to Hugging Face's service, or to OpenAI's service, and so on. And by the way, these companies also democratized this quite a bit. It was much, much harder to do this before they came around.Corey: Oh, yeah. I mean, I'm reminded of the old XKCD comic from years ago, which was, “Okay, I want to give you a picture. And I want you to tell me it was taken within the boundaries of a national park.” Like, “Sure. Easy enough. Geolocation information is attached. It'll take me two hours.” “Cool. And I also want you to tell me if it's a picture of a bird.” “Okay, that'll take five years and a research team.”And sure enough, now we can basically do that. The future is now and it's kind of wild to see that unfolding in a human perceivable timespan on these things. But I guess my question now is, so that is what a vector database does? What does Pinecone specifically do? It turns out that as much as I wish it were otherwise, not a lot of companies are founded on, “Well, we have this really neat technology, so we're just going to be here, well, in a foundational sense to wind up ensuring the uptake of that technology.” No, no, there's usually a monetization model in there somewhere. Where does Pinecone start, where does it stop, and how does it differentiate itself from typical vector databases? If such a thing could be said to exist yet.Ram: Such a thing doesn't exist yet. We were the first vector database, so in a sense, building this infrastructure, scaling it, and making it easy for people to operate it in a SaaS fashion is our primary core product offering. On top of that, this very recently started also enabling people who have who actually have raw text to not just be able to get value from these vector search engines and so on, but also be able to take advantage of traditional what we call keyword search or sparse retrieval and do a combined search better, in Pinecone. So, there's value-add on top of this that we do, but I would say the core of it is building a SaaS managed platform that allows people to actually easily store as data, scale it, query it in a way that's very hands off and doesn't require a lot of tuning or operational burden on their side. This is, like, our core value proposition.Corey: Got it. There's something to be said for making something accessible when previously it had only really been available to people who completed the Hello World tutorial—which generally resembled a doctorate at Berkeley or Waterloo or somewhere else—and turn it into something that's fundamentally, click the button. Where on that, I guess, a spectrum of evolution do you find that Pinecone is today?Ram: Yeah. So, you know, prior to Pinecone, we didn't really have this notion of a vector database. For several years, we've had libraries that are really good that you can pre-train on your embeddings, generate this thing called an index, and then you can search over that index. There is still a lot of work to be done even to deploy that and scale it and operate it in production and so on. Even that was not being, kind of, offered as a managed service before.What Pinecone does which is novel, is you no longer have to have this pre-training be done by somebody, you no longer have to worry about when to retrain your indexes, what to do when you have new data, what to do when there is deletions, updates, and the usual data management operations. You can just think of this is, like, a database that you just throw your data in. It does all the right things for you, you just worry about querying. This has never existed before, right? This is—it's not even like we are trying to make the operational part of something easier. It is that we are offering something that hasn't existed before, at the same time, making it operationally simple.So, we're solving two problems, which is we building a better database that hasn't existed before. So, if you really had this sort of data management problems and you wanted to build an index that was fresh that you didn't have to super manually tune for your own use cases, that simply couldn't have been done before. But at the same time, we are doing all of this in a cloud-native fashion; it's easy for you to just operate and not worry about.Corey: You've said that this hasn't really been done before, but this does sound like it is more than passingly familiar specifically to the idea of nearest neighbor search, which has been around since the '70s in a bunch of different ways. So, how is it different? And let me of course, ask my follow-up to that right now: why is this even an interesting problem to start exploring?Ram: This is a great question. First of all, nearest neighbor search is one of the oldest forms of machine learning. It's been known for decades. There's a lot of literature out there, there are a lot of great libraries as I mentioned in the passing before. All of these problems have primarily focused on static corpuses. So basically, you have a set of some amount of data, you want to create an index out of it, and you want to query it.A lot of literature has focused on this problem. Even there, once you go from small number of dimensions to large number of dimensions, things become computationally far more challenging. So, traditional nearest neighbor search actually doesn't scale very well. What do I mean by large number of dimensions? Today, deep-learning models that produce image representations typically operate in 2048 dimensions of photos [unintelligible 00:13:38] dimensions. Some of the OpenAI models are even 10,000 dimensional and above. So, these are very, very large dimensions.Most of the literature prior to maybe even less than ten years back has focused on less than ten dimensions. So, it's like a scale apart in dealing with small dimensional data versus large dimensional data. But even as of a couple of years back, there hasn't been enough, if any, focus on what happens when your data rapidly evolves. For example, what happens when people add new data? What happens if people delete some data? What happens if your vectors get updated? These aren't just theoretical problems; they happen all the time. Customers of ours face this all the time.In fact, the classic example is in recommendation systems where user preferences change all the time, right, and you want to adapt to that, which means your user vectors change constantly. When even these sort of things change constantly, you want your index to reflect it because you want your queries to catch on to the most recent data. [unintelligible 00:14:33] have to reflect the recency of your data. This is a solved problem for traditional databases. Relational databases are great at solving this problem. A lot of work has been done for decades to solve this problem really well.This is a fundamentally hard problem for vector databases and that's one of the core focus areas [unintelligible 00:14:48] painful. Another problem that is hard for these sort of databases is simple things like filtering. For example, you have a corpus of say product images and you want to only look at images that maybe are for the Fall shopping line, right? Seems like a very natural query. Again, databases have known and solved this problem for many, many years.The moment you do nearest neighbor search with these sort of constraints, it's a hard problem. So, it's just the fact that nearest neighbor search and lots of research in this area has simply not focused on what happens to that, so those are of techniques when combined with data management challenges, filtering, and all the traditional challenges of a database. So, when you start doing that you enter a very novel area to begin with.Corey: This episode is sponsored in part by our friends at Redis, the company behind the incredibly popular open-source database. If you're tired of managing open-source Redis on your own, or if you are looking to go beyond just caching and unlocking your data's full potential, these folks have you covered. Redis Enterprise is the go-to managed Redis service that allows you to reimagine how your geo-distributed applications process, deliver and store data. To learn more from the experts in Redis how to be real-time, right now, from anywhere, visit snark.cloud/redis. That's snark dot cloud slash R-E-D-I-S.Corey: So, where's this space going, I guess is sort of the dangerous but inevitable question I have to ask. Because whenever you talk to someone who is involved in a very early stage of what is potentially a transformative idea, it's almost indistinguishable from someone who is whatever the polite term for being wrapped around their own axle is, in a technological sense. It's almost a form of reverse Schneier's Law of anyone can create an encryption algorithm that they themselves cannot break. So, the possibility that this may come back to bite us in the future if it turns out that this is not potentially the revelation that you see it as, where do you see the future of this going?Ram: Really great question. The way I think about it is, and the reason why I keep going back to databases and these sort of ideas is, we have a really great way to deal with structured data and structured queries, right? This is the evolution of the last maybe 40, 50 years is to come up with relational databases, come up with SQL engines, come up with scalable ways of running structured queries on large amounts of data. What I feel like this sort of technology does is it takes it to the next level, which is you can actually ask unstructured questions on unstructured data, right? So, even the couple of examples we just talked about, doing near duplicate detection of images, that's a very unstructured question. What does it even mean to say that two images are nearly duplicate of each other? I couldn't even phrase it as kind of a concrete thing. I certainly cannot write a SQL statement for it, but I cannot even phrase it properly.With these sort of technologies, with the vector embeddings, with deep learning and so on, you can actually mathematically phrase it, right? The mathematical phrasing is very simple once you have the right representation that understands your image as a vector. Two images are nearly duplicate if they are close enough in the space of vectors. Suddenly you've taken a problem that was even hard to express, let alone compute, made it precise to express, precise to compute. This is going to happen not just for images, not just for semantic search, it's going to happen for all sorts of unstructured data, whether it's time series, where it's anomaly detection, whether it's security analytics, and so on.I actually think that fundamentally, a lot of fields are going to get disrupted by this sort of way of thinking about things. We are just scratching the surface here with semantic search, in my opinion.Corey: What is I guess your barometer for success? I mean, if I could take a very cynical point of view on this, it's, “Oh, well, whenever there's a managed vector database offering from AWS.” They'll probably call it Amazon Basics Vector or something like that. Well, that is a—it used to be a snarky observation that, “Oh, we're not competing, we're just validating their market.” Lately, with some of their competitive database offerings, there's a lot more truth to that than I suspect AWS would like.Their offerings are nowhere near as robust as what they pretend to be competing against. How far away do you think we are from the larger cloud providers starting to say, “Ah, we got the sense there was money in here, so we're launching an entire service around this?”Ram: Yeah. I mean, this is a—first of all, this is a great question. There's always something that's constantly, things that any innovator or disrupter has to be thinking about, especially these days. I would say that having a multi-year head, start in the use cases, in thinking about how this system should even look, what sort of use cases should it [unintelligible 00:19:34], what the operating points for the [unintelligible 00:19:37] database even look like, and how to build something that's cloud-native and scalable, is very hard to replicate. Meaning if you look at what we have already done and kind of tried to base the architecture of that, you're probably already a couple of years behind us in terms of just where we are at, right, not just in the architecture, but also in the use cases in where this is evolving forward.That said, I think it is, for all of these companies—and I would put—for example, Snowflake is a great example of this, which is Snowflake needn't have existed if Redshift had done a phenomenal job of being cloud-native, right, and kind of done that before Snowflake did it. In hindsight, it seems like it's obvious, but when Snowflake did this, it wasn't obvious that that's where everything was headed. And Snowflake built something that's very technologically innovative, in a sense that it's even now hard to replicate. Plus, it takes a long time to replicate something like that. I think that's where we are at.If Pinecone does its job really well and if we simply execute efficiently, it's very hard to replicate that. So, I'm not super worried about cloud providers, to be honest, in this space, I'm more worried about our execution.Corey: If it helps anything, I'm not very deep into your specific area of the world, obviously, but I am optimistic when I hear people say things like that. Whenever I find folks who are relatively early along in their technological journey being very concerned about oh, the large cloud provider is going to come crashing in, it feels on some level like their perspective is that they have one weird trick, and they were able to crack that, but they have no defensive mode because once someone else figures out the trick, well, okay, now we're done. The idea of sustained and lasting innovation in a space, I think, is the more defensible position to take, with the counterargument, of course, that that's a lot harder to find.Ram: Absolutely. And I think for technologies like this, that's the only solution, which is, if you really want to avoid being disrupted by cloud providers, I think that's the way to go.Corey: I want to talk a little bit about your own background. Before you wound up as the VP of R&D over at Pinecone, you were in a bunch of similar… I guess, similar styled roles—if we'll call it that—at Yahoo, Databricks, and Splunk. I'm curious as to what your experience in those companies wound up impressing on you that made you say, “Ah, that's great and all, but you know what's next? That's right, vector databases.” And off, you went to Pinecone. What did you see?Ram: So, first of all, in was some way or the other, I have been involved in machine learning and systems and the intersection of these two for maybe the last decade-and-a-half. So, it's always been something, like, in the in between the two and that's been personally exciting to me. So, I'm kind of very excited by trying to think about new type of databases, new type of data platforms that really leverages machine learning and data. This has been personally exciting to me. I obviously learned very different things from different companies.I would say that Yahoo was just the learning in cloud to begin with because prior to joining Yahoo, I wasn't familiar with Silicon Valley cloud companies at that scale and Yahoo is a big company and there's a lot to learn from there. It was also my first introduction to Hadoop, Spark, and even machine learning where I really got into machine learning at scale, in online advertising and areas like that, which was a massive scale. And I got into that in Yahoo, and it was personally exciting to me because there's very few opportunities where you can work on machine learning at that scale, right?Databricks was very exciting to me because it was an earlier-stage company than I had been at before. Extremely well run and I learned a lot from Databricks, just the team, the culture, the focus on innovation, and the focus on product thinking. I joined Databricks as a product manager. I hadn't played the product manager hat before that, so it was very much a learning experience for me and I think I learned from some of the best in that area. And even at Pinecone, I carry that forward, which is think about how my learnings at Databricks informs how we should be thinking about products at Pinecone, and so on. So, I think I learned—if I had to pick one company I learned a lot from, I would say, it's Databricks. The most [unintelligible 00:23:50].Corey: I would also like to point out, normally when people say, “Oh, the one company I've learned the most from,” and they pick one of them out of their history, it's invariably the most recent one, but you left there in 2018—Ram: Yeah.Corey: —then went to go spend the next three years over at Splunk, where you were a Senior Principal, Scientist, a Senior Director and Head of Machine-Learning, and then you decided, okay, that's enough hard work. You're going to do something easier and be the VP of Engineering, which is just wild at a company of that scale.Ram: Yeah. At Splunk, I learned a lot about management. I think managing large teams, managing multiple different teams, while working on very different areas is something I learned at Splunk. You know, I was at this point in my career when I was right around trying to start my own company. Basically, I was at a point where I'd taken enough learnings and I really wanted to do something myself.That's when Edo and I—you know, the CEO of Pinecone—and I started talking. And we had worked together for many years, and we started working together at Yahoo. We kept in touch with each other. And we started talking about the sort of problems that I was excited about working on and then I came to realize what he was working on and what Pinecone was doing. And we thought it was a very good fit for the two of us to work together.So, that is kind of how it happened. It sort of happened by chance, as many things do in Silicon Valley, where a lot of things just happen by network and chance. That's what happened in my case. I was just thinking of starting my own company at the time when just a chance encounter with Edo led me to Pinecone.Corey: It feels from my admittedly uninformed perspective, that a lot of what you're doing right now in the vector database area, it feels on some level, like it follows the trajectory of machine learning, in that for a long time, the only people really excited about it were either sci-fi authors or folks who had trouble explaining it to someone without a degree in higher math. And then it turned into—a couple of big stories from the mid-2010s stick out at me when we've been people were trying to sell this to me in a variety of different ways. One of them was, “Oh, yeah, if you're a giant credit card processing company and trying to detect fraud with this kind of transaction volume—” it's, yeah, there are maybe three companies in the world that fall into that exact category. The other was WeWork where they did a lot of computer vision work. And they used this to determine that at certain times of day there was congestion in certain parts of the buildings and that this was best addressed by hiring a second barista. Which distilled down to, “Wait a minute, you're telling me that you spent how much money on machine-learning and advanced analyses and data scientists and the rest have figured out that people like to drink coffee in the morning?” Like, that is a little on the ridiculous side.Now, I think that it is past the time for skepticism around machine learning when you can go to a website and type in a description of something and it paints a picture of the thing you just described. Or you can show it a picture and it describes what is in that picture fairly accurately. At this point, the only people who are skeptics, from my position on this, seem to be holding out for some sort of either next-generation miracle or are just being bloody-minded. Do you think that there's a tipping point for vector search where it's going to become blindingly obvious to, if not the mass market, at least more run-of-the-mill, more prosaic level of engineer that haven't specialized in this?Ram: Yeah. It's already, frankly, started happening. So, two years back, I wouldn't have suspected this fast of an adoption for this new of technology from this varied number of use cases. I just wouldn't have suspected it because I, you know, I still thought, it's going to take some time for this field to mature and, kind of, everybody to really start taking advantage of this. This has happened much faster than even I assumed.So, to some extent, it's already happening. A lot of it is because the barrier to entry is quite low right now, right? So, it's very easy and cost-effective for people to create these embeddings. There is a lot of documentation out there, things are getting easier and easier, day by day. Some of it is by Pinecone itself, by a lot of work we do. Some of it is by, like, companies that I mentioned before who are building better and better models, making it easier and easier for people to take these machine-learning models and use them without having to even fine-tune anything.And as technologies like Pinecone really mature and dramatically become cost-effective, the barrier to entry is very low. So, what we tend to see people do, it's not so much about confidence in this new technology; it is connecting something simple that I need this sort of value out of, and find the least critical path or the simplest way to get going on this sort of technology. And as long as it can make that barrier to entry very small and make this cost-effective and easy for people to explore, this is going to start exploding. And that's what we are seeing. And a lot of Pinecone's focus has been on ease-of-use, in simplicity in connecting the zero-to-one journey for precisely this reason. Because not only do we strongly believe in the value of this technology, it's becoming more and more obvious to the broader community as well. The remaining work to be done is just the ease of use and making things cost-effective. And cost-effectiveness is also what the focus on a lot. Like, this technology can be even more cost-effective than it is today.Corey: I think that it is one of those never-mistaken ideas to wind up making something more accessible to folks than keeping it in a relatively rarefied environment. We take a look throughout the history of computing in general and cloud in particular, were formerly very hard things have largely been reduced down to click the button. Yes, yes, and then get yelled at because you haven't done infrastructure-as-code, but click the button is still possible. I feel like this is on that trendline based upon what you're saying.Ram: Absolutely. And the more we can do here, both Pinecone and the broader community, I think the better, the faster the adoption of this sort of technology is going to be.Corey: I really want to thank you for spending so much time talking me through what it is you folks are working on. If people want to learn more, where's the best place for them to go to find you?Ram: Pinecone.io. Our website has a ton of information about Pinecone, as well as a lot of standard documentation. We have a free tier as well where you can play around with small data sets, really get a feel for vector search. It's completely free. And you can reach me at Ram at Pinecone. I'm always happy to answer any questions. Once again, thanks so much for having me.Corey: Of course. I will put links to all of that in the show notes. This promoted guest episode is brought to us by our friends at Pinecone. Ram Sriharsha is their VP of Engineering and R&D. And I'm Cloud Economist Corey Quinn. If you've enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you've hated this podcast, please leave a five-star review on your podcast platform of choice along with an angry, insulting comment that I will never read because the search on your podcast platform is broken because it's not using a vector database.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.Announcer: This has been a HumblePod production. Stay humble.

This week, Micah (@WebBreacher) and Christina (@ChristinaLekati), are joined by Robin (@NothicEye) to talk about this month's #OSINT News & Tools. Our conversation started by focusing on the individuals that are wishing to enter the world of open-source intelligence not only as hobbyists but also, perhaps, as professionals. We talked about our latest blog post “Five tips to get you started in OSINT” in which 5 of our OSINT Curious members are sharing one quick tip each on getting started in this space. Thinking of the ones who would like to start a career in OSINT or look for different opportunities, we moved on to discuss a series of new interviews that were posted last month in the OSINT Jobs website. The blog/interview series is called “What hiring managers are looking for” and draws from the perspectives of 6 different hiring managers in the OSINT industry. The questions in these interviews include "how can candidates stand out right away?" and "What does the recruitment process look like in your organization?" among other, many interesting questions. Few things can help an OSINT practitioner develop their skills and broaden their perspective more than belonging to a small or large group or community. Robin (@NothicEye) who is also one of the moderators of the OSINT Curious Discord group, was able to share with us her observations from participating in OSINT-focused groups. She points out that smaller groups of practitioners can have a wide range of benefits. Our team then moved on to discussing Nico Deken's (@dutch_osintguy) updates on his programmable search engine for people's digital business cards and social media details. For the Geolocation fans we shared and discussed two resources: 1. Benjamin Strick's (@BenDoBrown) YouTube videos in which he goes through different tips, techniques and tools in geolocating visual elements. Last week, Benjamin started a new video series called "Let's Geolocate" 2. A Geolocation Cheat Sheet from @TheSEINT - a pretty detailed mind map with different elements that you can investigate when you analyze an image and try to geolocate it. All the relevant links can be found below!

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What is privacy in a Post-Roe world? TPG Host Reema Moussa chats with Eva Galperin on surveillance, data privacy, and digital liberties in the wake of the overturning of Roe v. Wade.

Fedora gets serious about its server editions, our thoughts on Valve's increased Steam Deck production, and the surprising results of booting Linux on the Apple M2 SoC.

A Cyberattack is suspected of causing false alarms in Israel. Risk surface assessments. Renewed warning of the potential security risks of fitness apps. Cyber options may grow more attractive to Russia as kinetic operations stall. DDoS in St. Petersburg. Ben Yeling details a Senate bill restricting the sale of location data. Our guest is Jon Check from Raytheon's Intelligence and Space Division discussing the National Collegiate Cyber Defense Competition. A conviction in the Capital One hacking case. For links to all of today's stories check out our CyberWire daily news briefing: https://thecyberwire.com/newsletters/daily-briefing/11/118 Selected reading. Suspected cyberattack triggers sirens in Jerusalem, Eilat (Israel Hayom) Suspected Iranian Cyberattack on Israel Triggers Sirens (Haaretz) Iranian cyberattack may be behind false rocket warning sirens in Jerusalem (Jerusalem Post)  Israel suspects Iranian cyber-attack behind false siren alerts (Middle East Monitor)  Strava fitness app used to spy on Israeli military officials (Computing)  Treasury's Adeyemo sees elevated cyber threats in wake of Russia's war in Ukraine (Reuters) More cyber warfare with Russia lies on the horizon (Interesting Engineering) Prolonged war may make Russia more cyber aggressive, US official says (C4ISRNet)  What the Russia-Ukraine war means for the future of cyber warfare (The Hill)  Complex Russian cyber threat requires we go back to basics (ComputerWeekly.com)  Vladimir Putin speech delayed 'because of cyber-attack' as he hits out at 'economic blitzkrieg' against Russia (Scotsman) UPDATE 1-Putin's St Petersburg speech postponed by an hour after cyberattack (Yahoo) Think of the Russia-Ukraine conflict as a microcosm of the cyber war  (SC Magazine) The link between cyberattacks and war: Gartner (CRN Australia)  Ex-Amazon Worker Convicted in Capital One Hacking (New York Times) Jury Convicts Seattle Woman in Massive Capital One Hack (SecurityWeek) Former Seattle tech worker convicted of wire fraud and computer intrusions (US Attorney's Office, Western District of Washington)

This week we cover the WWDC 2022 Keynote and Platform State of the Union. We're joined by Friend of the Show Joe Cieplinski. We fact check Sir Adam Beck and Steve Westgarth. We discuss Awesome lists and a calculator on the Lock Screen. We get into the new HIG, WWDC Keynote, iOS 16, Apple Watch and watchOS 9, Mac hardware and M2, macOS Ventura, iPadOS 16, Platforms State of the Union, Xcode Cloud, Swift, SwiftUI, System Experience, MapKit, WeatherKit, Live Text API and Data Scanner API. Picks: WWDC Community links updated for 2022, return of the UK iOS conferences, iOS Dev UK and Codemobile UK, Hello Swift Charts Special Guest: Joe Cieplinski.

In this episode of Syntax, Wes and Scott talk about 10 browser API's you might not be familiar with including getUserMedia, Resize Observer, SpeechRecognition, and more! Prismic - Sponsor Prismic is a Headless CMS that makes it easy to build website pages as a set of components. Break pages into sections of components using React, Vue, or whatever you like. Make corresponding Slices in Prismic. Start building pages dynamically in minutes. Get started at prismic.io/syntax. LogRocket - Sponsor LogRocket lets you replay what users do on your site, helping you reproduce bugs and fix issues faster. It's an exception tracker, a session re-player and a performance monitor. Get 14 days free at logrocket.com/syntax. Freshbooks - Sponsor Get a 30 day free trial of Freshbooks at freshbooks.com/syntax Show Notes 00:13 Welcome 01:05 Dishwasher talk 04:30 getUserMedia Hair.WesBos.com Javascript 30 07:22 FileSystem Level Up Tutorials: Browser APIs Electron 12:50 Geolocation 15:07 Sponsor: Prismic 16:41 Permissions 22:36 Web Animations Web Animations API Framer Motion Motion One 26:31 Resize Observer Resize Observer API 29:33 Sponsor: LogRocket 30:45 Clipboard Clipboard API 34:10 Web storage Web storage 37:11 Sponsor: Freshbooks 38:09 SpeechSynthesis 41:32 SpeechRecognition 46:14 ××× SIIIIICK ××× PIIIICKS ××× ××× SIIIIICK ××× PIIIICKS ××× Scott: RCA to HDMI adapter Wes: SlimLED Shameless Plugs Scott: LevelUp Tutorials Wes: Wes Bos Tutorials Tweet us your tasty treats Scott's Instagram LevelUpTutorials Instagram Wes' Instagram Wes' Twitter Wes' Facebook Scott's Twitter Make sure to include @SyntaxFM in your tweets

Crypto gaming needs a bridge to get the traditional gamers onboard. Izumi World appears to be that bridge. Izumi is the world's first AR metaverse that is revolutionizing pop culture through NFT gaming. In this episode, CEO Joe Pokrzywa and CMO Jamie Davies tell us what makes the game so compelling, especially to people who come from the gaming space and not necessarily the crypto and NFT space. Coming from a gaming background themselves, the Izumi leadership team understands the need to create a game-first experience without relegating the crypto component into the background. Joe and Jamie rub off on us their excitement over Izumi's role in putting AR gaming into the spotlight once again after being relatively pushed into the sidelines for too long. We're going to see the Izumi beta starting Q4 of 2022, so that's going to be exciting!More from Edge of NFT:

Crypto gaming needs a bridge to get the traditional gamers onboard. Izumi World appears to be that bridge. Izumi is the world's first AR metaverse that is revolutionizing pop culture through NFT gaming. In this episode, CEO Joe Pokrzywa and CMO Jamie Davies tell us what makes the game so compelling, especially to people who come from the gaming space and not necessarily the crypto and NFT space. Coming from a gaming background themselves, the Izumi leadership team understands the need to create a game-first experience without relegating the crypto component into the background. Joe and Jamie rub off on us their excitement over Izumi's role in putting AR gaming into the spotlight once again after being relatively pushed into the sidelines for too long. We're going to see the Izumi beta starting Q4 of 2022, so that's going to be exciting!