Podcasts about sony aibo

Info: us.aibo.com  Sony Aibo es una mascota robótica avanzada diseñada para ofrecer una experiencia interactiva y emocional similar a la de un perro real. Equipado con inteligencia artificial y múltiples sensores, Aibo puede reconocer rostros, voces y responder al tacto, desarrollando una personalidad única basada en la interacción con su dueño. Su estructura cuenta con 22 ejes de movimiento, lo que le permite desplazarse de manera fluida y natural. Además, Aibo utiliza servicios en la nube para almacenar recuerdos y mejorar su comportamiento con el tiempo, brindando una experiencia cada vez más personalizada

Victoria is joined by guest co-host Joe Ferris, CTO at thoughtbot, and Seif Lotfy, the CTO and Co-Founder of Axiom. Seif discusses the journey, challenges, and strategies behind his data analytics and observability platform. Seif, who has a background in robotics and was a 2008 Sony AIBO robotic soccer world champion, shares that Axiom pivoted from being a Datadog competitor to focusing on logs and event data. The company even built its own logs database to provide a cost-effective solution for large-scale analytics. Seif is driven by his passion for his team and the invaluable feedback from the community, emphasizing that sales validate the effectiveness of a product. The conversation also delves into Axiom's shift in focus towards developers to address their need for better and more affordable observability tools. On the business front, Seif reveals the company's challenges in scaling across multiple domains without compromising its core offerings. He discusses the importance of internal values like moving with urgency and high velocity to guide the company's future. Furthermore, he touches on the challenges and strategies of open-sourcing projects and advises avoiding platforms like Reddit and Hacker News to maintain focus. Axiom (https://axiom.co/) Follow Axiom on LinkedIn (https://www.linkedin.com/company/axiomhq/), X (https://twitter.com/AxiomFM), GitHub (https://github.com/axiomhq), or Discord (https://discord.com/invite/axiom-co). Follow Seif Lotfy on LinkedIn (https://www.linkedin.com/in/seiflotfy/) or X (https://twitter.com/seiflotfy). Visit his website at seif.codes (https://seif.codes/). Follow thoughtbot on X (https://twitter.com/thoughtbot) or LinkedIn (https://www.linkedin.com/company/150727/). Become a Sponsor (https://thoughtbot.com/sponsorship) of Giant Robots! Transcript: VICTORIA: This is the Giant Robots Smashing Into Other Giant Robots Podcast, where we explore the design, development, and business of great products. I'm your host, Victoria Guido, and with me today is Seif Lotfy, CTO and Co-Founder of Axiom, the best home for your event data. Seif, thank you for joining me. SEIF: Hey, everybody. Thanks for having me. This is awesome. I love the name of the podcast, given that I used to compete in robotics. VICTORIA: What? All right, we're going to have to talk about that. And I also want to introduce a guest co-host today. Since we're talking about cloud, and observability, and data, I invited Joe Ferris, thoughtbot CTO and Director of Development of our platform engineering team, Mission Control. Welcome, Joe. How are you? JOE: Good, thanks. Good to be back again. VICTORIA: Okay. I am excited to talk to you all about observability. But I need to go back to Seif's comment on competing with robots. Can you tell me a little bit more about what robots you've built in the past? SEIF: I didn't build robots; I used to program them. Remember the Sony AIBOs, where Sony made these dog robots? And we would make them compete. There was an international competition where we made them play soccer, and they had to be completely autonomous. They only communicate via Bluetooth or via wireless protocols. And you only have the camera as your sensor as well as...a chest sensor throws the ball near you, and then yeah, you make them play football against each other, four versus four with a goalkeeper and everything. Just look it up: RoboCup AIBO. Look it up on YouTube. And I...2008 world champion with the German team. VICTORIA: That sounds incredible. What kind of crowds are you drawing out for a robot soccer match? Is that a lot of people involved with that? SEIF: You would be surprised how big the RoboCup competition is. It's ridiculous. VICTORIA: I want to go. I'm ready. I want to, like, I'll look it up and find out when the next one is. SEIF: No more Sony robots but other robots. Now, there's two-legged robots. So, they make them play as two-legged robots, much slower than four-legged robots, but works. VICTORIA: Wait. So, the robots you were playing soccer with had four legs they were running around on? SEIF: Yeah, they were dogs [laughter]. VICTORIA: That's awesome. SEIF: We all get the same robot. It's just a competition on software, right? On a software level. And some other competitions within the RoboCup actually use...you build your own robot and stuff like that. But this one was...it's called the Standard League, where we all have a robot, and we have to program it. JOE: And the standard robot was a dog. SEIF: Yeah, I think back then...we're talking...it's been a long time. I think it started in 2001 or something. I think the competition started in 2001 or 2002. And I compete from 2006 to 2008. Robots back then were just, you know, simple. VICTORIA: Robots today are way too complicated [laughs]. SEIF: Even AI is more complicated. VICTORIA: That's right. Yeah, everything has gotten a lot more complicated [laughs]. I'm so curious how you went from being a world-champion robot dog soccer player [laughs] programmer [laughs] to where you are today with Axiom. Can you tell me a little bit more about your journey? SEIF: The journey is interesting because it came from open source. I used to do open source on the side a lot–part of the GNOME Project. That's where I met Neil and the rest of my team, Mikkel Kamstrup, the whole crowd, basically. We worked on GNOME. We worked on Ubuntu. Like, most of them were working professionally on it. I was working for another company, but we worked on the same project. We ended up at Xamarin, which was bought by Microsoft. And then we ended up doing Axiom. But we've been around each other professionally since 2009, most of us. It's like a little family. But how we ended up exactly in observability, I think it's just trying to fix pain points in my life. VICTORIA: Yeah, I was reading through the docs on Axiom. And there's an interesting point you make about organizations having to choose between how much data they have and how much they want to spend on it. So, maybe you can tell me a little bit more about that pain point and what you really found in the early stages that you wanted to solve. SEIF: So, the early stages of what we wanted to solve we were mainly dealing with...so, the early, early stage, we were actually trying to be a Datadog competitor, where we were going to be self-hosted. Eventually, we focused on logs because we found out that's what was a big problem for most people, just event data, not just metric but generally event data, so logs, traces, et cetera. We built out our own logs database completely from scratch. And one of the things we stumbled upon was; basically, you have three things when it comes to logging, which is low cost, low latency, and large scale. That's what everybody wants. But you can't get all three of them; you can only get two of them. And we opted...like, we chose large scale and low cost. And when it comes to latency, we say it should be just fast enough, right? And that's where we focused on, and this is how we started building it. And with that, this is how we managed to stand out by just having way lower cost than anybody else in the industry and dealing with large scale. VICTORIA: That's really interesting. And how did you approach making the ingestion pipeline for masses amount of data more efficient? SEIF: Just make it coordination-free as possible, right? And get rid of Kafka because Kafka just, you know, drains your...it's where you throw in money. Like maintaining Kafka...it's like back then Elasticsearch, right? Elasticsearch was the biggest part of your infrastructure that would cost money. Now, it's also Kafka. So, we found a way to have our own internal way of queueing things without having to rely on Kafka. As I said, we wrote everything from scratch to make it work. Like, every now and then, I think that we can spin this out of the company and make it a new product. But now, eyes on the prize, right? JOE: It's interesting to hear that somebody who spent so much time in the open-source community ended up rolling their own solution to so many problems. Do you feel like you had some lessons learned from open source that led you to reject solutions like Kafka, or how did that journey go? SEIF: I don't think I'm rejecting Kafka. The problem is how Kafka is built, right? Kafka is still...you have to set up all these servers. They have to communicate, et cetera, etcetera. They didn't build it in a way where it's stateless, and that's what we're trying to go to. We're trying to make things as stateless as possible. So, Kafka was never built for the cloud-native era. And you can't really rely on SQS or something like that because it won't deal with this high throughput. So, that's why I said, like, we will sacrifice some latency, but at least the cost is low. So, if messages show after half a second or a second, I'm good. It doesn't have to be real-time for me. So, I had to write a couple of these things. But also, it doesn't mean that we reject open source. Like, we actually do like open source. We open-source a couple of libraries. We contribute back to open source, right? We needed a solution back then for that problem, and we couldn't find any. And maybe one day, open source will have, right? JOE: Yeah. I was going to ask if you considered open-sourcing any of your high latency, high throughput solutions. SEIF: Not high latency. You make it sound bad. JOE: [laughs] SEIF: You make it sound bad. It's, like, fast enough, right? I'm not going to compete on milliseconds because, also, I'm competing with ClickHouse. I don't want to compete with ClickHouse. ClickHouse is low latency and large scale, right? But then the cost is, you know, off the charts a bit sometimes. I'm going the other route. Like, you know, it's fast enough. Like, how, you know, if it's under two, three seconds, everybody's happy, right? If the results come within two, three seconds, everybody is happy. If you're going to build a real-time trading system on top of it, I'll strongly advise against that. But if you're building, you know, you're looking at dashboards, you're more in the observability field, yeah, we're good. VICTORIA: Yeah, I'm curious what you found, like, which customer personas that market really resonated with. Like, is there a particular, like, industry type where you're noticing they really want to lower their cost, and they're okay with this just fast enough latency? SEIF: Honestly, with the current recession, everybody is okay with giving up some of the speed to reduce the money because I think it's not linear reduction. It's more exponential reduction at this point, right? You give up a second, and you're saving 30%. You give up two seconds, all of a sudden, you're saving 80%. So, I'd say in the beginning, everybody thought they need everything to be very, very fast. And now they're realizing, you know, with limitations you have around your budget and spending, you're like, okay, I'm okay with the speed. And, again, we're not slow. I'm just saying people realize they don't need everything under a second. They're okay with waiting for two seconds. VICTORIA: That totally resonates with me. And I'm curious if you can add maybe a non-technical or a real-life example of, like, how this impacts the operations of a company or organization, like, if you can give us, like, a business-y example of how this impacts how people work. SEIF: I don't know how, like, how do people work on that? Nothing changed, really. They're still doing the, like...really nothing because...and that aspect is you run a query, and, again, as I said, you're not getting the result in a second. You're just waiting two seconds or three seconds, and it's there. So, nothing really changed. I think people can wait three seconds. And we're still like–when I say this, we're still faster than most others. We're just not as fast as people who are trying to compete on a millisecond level. VICTORIA: Yeah, that's okay. Maybe I'll take it back even, like, a step further, right? Like, our audience is really sometimes just founders who almost have no formal technical training or background. So, when we talk about observability, sometimes people who work in DevOps and operations all understand it and kind of know why it's important [laughs] and what we're talking about. So, maybe you could, like, go back to -- SEIF: Oh, if you're asking about new types of people who've been using it -- VICTORIA: Yeah. Like, if you're going to explain to, like, a non-technical founder, like, why your product is important, or, like, how people in their organization might use it, what would you say? SEIF: Oh, okay, if you put it like that. It's more of if you have data, timestamp data, and you want to run analytics on top of it, so that could be transactions, that could be web vitals, rather than count every time somebody visits, you have a timestamp. So, you can count, like, how many visitors visited the website and what, you know, all these kinds of things. That's where you want to use something like Axiom. That's outside the DevOps space, of course. And in DevOps space, there's so many other things you use Axiom for, but that's outside the DevOps space. And we actually...we implemented as zero-config integration with Vercel that kind of went viral. And we were, for a while, the number one enterprise for self-integration because so many people were using it. So, Vercel users are usually not necessarily writing the most complex backends, but a lot of things are happening on the front-end side of things. And we would be giving them dashboards, automated dashboards about, you know, latencies, and how long a request took, and how long the response took, and the content type, and the status codes, et cetera, et cetera. And there's a huge user base around that. VICTORIA: I like that. And it's something, for me, you know, as a managing director of our platform engineering team, I want to talk more to founders about. It's great that you put this product and this app out into the world. But how do you know that people are actually using it? How do you know that people, like, maybe, are they all quitting after the first day and not coming back to your app? Or maybe, like, the page isn't loading or, like, it's not working as they expected it to. And, like, if you don't have anything observing what users are doing in your app, then it's going to be hard to show that you're getting any traction and know where you need to go in and make corrections and adjust. SEIF: We have two ways of doing this. Right now, internally, we use our own tools to see, like, who is sending us data. We have a deployment that's monitoring production deployment. And we're just, you know, seeing how people are using it, how much data they're sending every day, who stopped sending data, who spiked in sending data sets, et cetera. But we're using Mixpanel, and Dominic, our Head of Product, implemented a couple of key metrics to that for that specifically. So, we know, like, what's the average time until somebody starts going from building its own queries with the builder to writing APL, or how long it takes them from, you know, running two queries to five queries. And, you know, we just start measuring these things now. And it's been going...we've been growing healthy around that. So, we tend to measure user interaction, but also, we tend to measure how much data is being sent. Because let's keep in mind, usually, people go in and check for things if there's a problem. So, if there's no problem, the user won't interact with us much unless there's a notification that kicks off. We also just check, like, how much data is being sent to us the whole time. VICTORIA: That makes sense. Like, you can't just rely on, like, well, if it was broken, they would write a [chuckles], like, a question or something. So, how do you get those metrics and that data around their interactions? So, that's really interesting. So, I wonder if we can go back and talk about, you know, we already mentioned a little bit about, like, the early days of Axiom and how you got started. Was there anything that you found in the early discovery process that was surprising and made you pivot strategy? SEIF: A couple of things. Basically, people don't really care about the tech as much as they care [inaudible 12:51] and the packaging, so that's something that we had to learn. And number two, continuous feedback. Continuous feedback changed the way we worked completely, right? And, you know, after that, we had a Slack channel, then we opened a Discord channel. And, like, this continuous feedback coming in just helps with iterating, helps us with prioritizing, et cetera. And that changed the way we actually developed product. VICTORIA: You use Slack and Discord? SEIF: No. No Slack anymore. We had a community Slack. We had a community [inaudible 13:19] Slack. Now, there's no community Slack. We only have a community Discord. And the community Slack is...sorry, internally, we use Slack, but there's a community Discord for the community. JOE: But how do you keep that staffed? Is it, like, everybody is in the Discord during working hours? Is it somebody's job to watch out for community questions? SEIF: I think everybody gets involved now just...and you can see it. If you go on our Discord, you will just see it. Just everyone just gets involved. I think just people are passionate about what they're doing. At least most people are involved on Discord, right? Because there's, like, Discord the help sections, and people are just asking questions and other people answering. And now, we reached a point where people in the community start answering the questions for other people in the community. So, that's how we see it's starting to become a healthy community, et cetera. But that is one of my favorite things: when I see somebody from the community answering somebody else, that's a highlight for me. Actually, we hired somebody from that community because they were so active. JOE: Yeah, I think one of the biggest signs that a product is healthy is when there's a healthy ecosystem building up around it. SEIF: Yeah, and Discord reminds me of the old days of open sources like IRC, just with memes now. But because all of us come from the old IRC days, being on Discord and chatting around, et cetera, et cetera, just gives us this momentum back, gave us this momentum back, whereas Slack always felt a bit too businessy to me. JOE: Slack is like IRC with emoji. Discord is IRC with memes. SEIF: I would say Slack reminds me somehow of MSN Messenger, right? JOE: I feel like there's a huge slam on MSN Messenger here. SEIF: [laughs] What do you guys use internally, Slack or? I think you're using Slack, right? Or Teams. Don't tell me you're using Teams. JOE: No, we're using Slack. SEIF: Okay, good, because I shit talk. Like, there is this, I'll sh*t talk here–when I start talking about Teams, so...I remember that one thing Google did once, and that failed miserably. JOE: Google still has, like, seven active chat products. SEIF: Like, I think every department or every, like, group of engineers just uses one of them internally. I'm not sure. Never got to that point. But hey, who am I to judge? VICTORIA: I just feel like I end up using all of them, and then I'm just rotating between different tabs all day long. You maybe talked me into using Discord. I feel like I've been resisting it, but you got me with the memes. SEIF: Yeah, it's definitely worth it. It's more entertaining. More noise, but more entertaining. You feel it's alive, whereas Slack is...also because there's no, like, history is forever. So, you always go back, and you're like, oh my God, what the hell is this? VICTORIA: Yeah, I have, like, all of them. I'll do anything. SEIF: They should be using Axiom in the background. Just send data to Axiom; we can keep your chat history. VICTORIA: Yeah, maybe. I'm so curious because, you know, you mentioned something about how you realized that it didn't matter really how cool the tech was if the product packaging wasn't also appealing to people. Because you seem really excited about what you've built. So, I'm curious, so just tell us a little bit more about how you went about trying to, like, promote this thing you built. Or was, like, the continuous feedback really early on, or how did that all kind of come together? SEIF: The continuous feedback helped us with performance, but actually getting people to sign up and pay money it started early on. But with Vercel, it kind of skyrocketed, right? And that's mostly because we went with the whole zero-config approach where it's just literally two clicks. And all of a sudden, Vercel is sending your data to Axiom, and that's it. We will create [inaudible 16:33]. And we worked very closely with Vercel to do this, to make this happen, which was awesome. Like, yeah, hats off to them. They were fantastic. And just two clicks, three clicks away, and all of a sudden, we created Axiom organization for you, the data set for you. And then we're sending it...and the data from Vercel is being forwarded to it. I think that packaging was so simple that it made people try it out quickly. And then, the experience of actually using Axiom was sticky, so they continued using it. And then the price was so low because we give 500 gigs for free, right? You send us 500 gigs a month of logs for free, and we don't care. And you can start off here with one terabyte for 25 bucks. So, people just start signing up. Now, before that, it was five terabytes a month for $99, and then we changed the plan. But yeah, it was cheap enough, so people just start sending us more and more and more data eventually. They weren't thinking...we changed the way people start thinking of “what am I going to send to Axiom” or “what am I going to send to my logs provider or log storage?” To how much more can I send? And I think that's what we wanted to reach. We wanted people to think, how much more can I send? JOE: You mentioned latency and cost. I'm curious about...the other big challenge we've seen with observability platforms, including logs, is cardinality of labels. Was there anything you had to sacrifice upfront in terms of cardinality to manage either cost or volume? SEIF: No, not really. Because the way we designed it was that we should be able to deal with high cardinality from scratch, right? I mean, there's open-source ways of doing, like, if you look at how, like, a column store, if you look at a column store and every dimension is its own column, it's just that becomes, like, you can limit on the amount of columns you're creating, but you should never limit on the amount of different values in a column could be. So, if you're having something like stat tags, right? Let's say hosting, like, hostname should be a column, but then the different hostnames you have, we never limit that. So, the cardinality on a value is something that is unlimited for us, and we don't really see it in cost. It doesn't really hit us on cost. It reflects a bit on compression if you get into technical details of that because, you know, high cardinality means a lot of different data. So, compression is harder, but it's not repetitive. But then if you look at, you know, oh, I want to send a lot of different types of fields, not values with fields, so you have hostname, and latency, and whatnot, et cetera, et cetera, yeah, that's where limitation starts because then they have...it's like you're going to a wide range of...and a wider dimension. But even that, we, yeah, we can deal with thousands at this point. And we realize, like, most people will not need more than three or four. It's like a Postgres table. You don't need more than 3,000 to 4000 columns; else, you know, you're doing a lot. JOE: I think it's actually pretty compelling in terms of cost, though. Like, that's one of the things we've had to be most careful about in terms of containing cost for metrics and logs is, a lot of providers will...they'll either charge you based on the number of unique metric combinations or the performance suffers greatly. Like, we've used a lot of Prometheus-based solutions. And so, when we're working with developers, even though they don't need more than, you know, a few dozen metric combinations most of the time, it's hard for people to think of what they need upfront. It's much easier after you deploy it to be able to query your data and slice it retroactively based on what you're seeing. SEIF: That's the detail. When you say we're using Prometheus, a lot of the metrics tools out there are using, just like Prometheus, are using the Gorilla data structure. And the real data structure was never designed to deal with high cardinality labels. So, basically, to put it in a simple way, every combination of tags you send for metrics is its own file on disk. That's, like, the very simple way of explaining this. And then, when you're trying to search through everything, right? And you have a lot of these combinations. I actually have to get all these files from this conversion back together, you know, and then they're chunked, et cetera. So, it's a problem. Generally, how metrics are doing it...most metrics products are using it, even VictoriaMetrics, et cetera. What they're doing is they're using either the Prometheus TSDB data structure, which is based on Gorilla. Influx was doing the same thing. They pivoted to using more and more like the ones we use, and Honeycomb uses, right? So, we might not be as fast on metrics side as these highly optimized. But then when it comes to high [inaudible 20:49], once we start dealing with high cardinality, we will be faster than those solutions. And that's on a very technical level. JOE: That's pretty cool. I realize we're getting pretty technical here. Maybe it's worth defining cardinality for the audience. SEIF: Defining cardinality to the...I mean, we just did that, right? JOE: What do you think, Victoria? Do you know what cardinality is now? [laughs] VICTORIA: All right. Now I'm like, do I know? I was like, I think I know what it means. Cardinality is, like, let's say you have a piece of data like an event or a transaction. SEIF: It's like the distinct count on a property that gives you the cardinality of a property. VICTORIA: Right. It's like how many pieces of information you have about that one event, basically, yeah. JOE: But with some traditional metrics stores, it's easy to make mistakes. For example, you could have unbounded cardinality by including response time as one of the labels -- SEIF: Tags. JOE: And then it's just going to -- SEIF: Oh, no, no. Let me give you a better one. I put in timestamp at some point in my life. JOE: Yeah, I feel like everybody has done that one. [laughter] SEIF: I've put a system timestamp at some point in my life. There was the actual timestamp, and there was a system timestamp that I would put because I wanted to know when the...because I couldn't control the timestamp, and the only timestamp I had was a system timestamp. I would always add the actual timestamp of when that event actually happened into a metric, and yeah, that did not scale. MID-ROLL AD: Are you an entrepreneur or start-up founder looking to gain confidence in the way forward for your idea? At thoughtbot, we know you're tight on time and investment, which is why we've created targeted 1-hour remote workshops to help you develop a concrete plan for your product's next steps. Over four interactive sessions, we work with you on research, product design sprint, critical path, and presentation prep so that you and your team are better equipped with the skills and knowledge for success. Find out how we can help you move the needle at tbot.io/entrepreneurs. VICTORIA: Yeah. I wonder if you could maybe share, like, a story about when it's gone wrong, and you've suddenly charged a lot of money [laughs] just to get information about what's happening in the system. Any, like, personal experiences with observability that kind of informed what you did with Axiom? SEIF: Oof, I have a very bad one, like, a very, very bad one. I used to work for a company. We had to deploy Elasticsearch on Windows Servers, and it was US-East-1. So, just a combination of Elasticsearch back in 2013, 2014 together with Azure and Windows Server was not a good idea. So, you see where this is going, right? JOE: I see where it's going. SEIF: Eventually, we had, like, we get all these problems because we used Elasticsearch and Kibana as our, you know, observability platform to measure everything around the product we were building. And funny enough, it cost us more than actually maintaining the infrastructure of the product. But not just that, it also kept me up longer because most of the downtimes I would get were not because of the product going down. It's because my Elasticsearch cluster started going down, and there's reasons for that. Because back then, Microsoft Azure thought that it's okay for any VM to lose connection with the rest of the VMs for 30 seconds per day. And then, all of a sudden, you have Elasticsearch with a split-brain problem. And there was a phase where I started getting alerted so much that back then, my partner threatened to leave me. So I bought a...what I think was a shock bracelet or a shock collar via Bluetooth, and I connected it to phone for any notification. And I bought that off Alibaba, by the way. And I would charge it at night, put it on my wrist, and go to sleep. And then, when alert happens, it will fully discharge the battery on me every time. JOE: Okay, I have to admit, I did not see where that was going. SEIF: Yeah, did that for a while; definitely did not save my relationship either. But eventually, that was the point where, you know, we started looking into other observability tools like Datadog, et cetera, et cetera, et cetera. And that's where the actual journey began, where we moved away from Elasticsearch and Kibana to look for something, okay, that we don't have to maintain ourselves and we can use, et cetera. So, it's not about the costs as much; it was just pain. VICTORIA: Yeah, pain is a real pain point, actual physical [chuckles] and emotional pain point [laughter]. What, like, motivates you to keep going with Axiom and to keep, like, the wind in your sails to keep working on it? SEIF: There's a couple of things. I love working with my team. So, honestly, I just wake up, and I compliment my team. I just love working with them. They're a lot of fun to work with. And they challenge me, and I challenge them back. And I upset them a lot. And they can't upset me, but I upset them. But I love working with them, and I love working with that team. And the other thing is getting, like, having this constant feedback from customers just makes you want to do more and, you know, close sales, et cetera. It's interesting, like, how I'm a very technical person, and I'm more interested in sales because sales means your product works, the product, the technical parts, et cetera. Because if technically it's not working, you can't build a product on top of it. And if you're not selling it, then what's the point? You only sell when the product is good, more or less, unless you're Oracle. VICTORIA: I had someone ask me about Oracle recently, actually. They're like, "Are you considering going back to it?" And I'm maybe a little allergic to it from having a federal consulting background [laughs]. But maybe they'll come back around. I don't know. We'll see. SEIF: Did you sell your soul back then? VICTORIA: You know, I feel like I just grew up in a place where that's what everyone did was all. SEIF: It was Oracle, IBM, or HP back in the day. VICTORIA: Yeah. Well, basically, when you're working on applications that were built in, like, the '80s, Oracle was, like, this hot, new database technology [laughs] that they just got five years ago. So, that's just, yeah, interesting. SEIF: Although, from a database perspective, they did a lot of the innovations. A lot of first innovations could have come from Oracle. From a technical perspective, they're ridiculous. I'm not sure from a product perspective how good they are. But I know their sales team is so big, so huge. They don't care about the product anymore. They can still sell. VICTORIA: I think, you know, everything in tech is cyclical. So, you know, if they have the right strategy and they're making some interesting changes over there, there's always a chance [laughs]. Certain use cases, I mean, I think that's the interesting point about working in technology is that you know, every company is a tech company. And so, there's just a lot of different types of people, personas, and use cases for different types of products. So, I wonder, you know, you kind of mentioned earlier that, like, everyone is interested in Axiom. But, you know, I don't know, are you narrowing the market? Or, like, how are you trying to kind of focus your messaging and your sales for Axiom? SEIF: I'm trying to focus on developers. So, we're really trying to focus on developers because the experience around observability is crap. It's stupid expensive. Sorry for being straightforward, right? And that's what we're trying to change. And we're targeting developers mainly. We want developers to like us. And we'll find all these different types of developers who are using it, and that's the interesting thing. And because of them, we start adding more and more features, like, you know, we added tracing, and now that enables, like, billions of events pushed through for, you know, again, for almost no money, again, $25 a month for a terabyte of data. And we're doing this with metrics next. And that's just to address the developers who have been giving us feedback and the market demand. I will sum it up, again, like, the experience is crap, and it's stupid expensive. I think that's the [inaudible 28:07] of observability is just that's how I would sum it up. VICTORIA: If you could go back in time and talk to yourself when you were still a developer, now that you're CTO, what advice would you give yourself? JOE: Besides avoiding shock collars. VICTORIA: [laughs] Yes. SEIF: Get people's feedback quickly so you know you're on the right track. I think that's very, very, very, very important. Don't just work in the dark, or don't go too long into stealth mode because, eventually, people catch up. Also, ship when you're 80% ready because 100% is too late. I think it's the same thing here. JOE: Ship often and early. SEIF: Yeah, even if it's not fully ready, it's still feedback. VICTORIA: Ship often and early and talk to people [laughs]. Just, do you feel like, as a developer, did you have the skills you needed to be able to get the most out of those feedback and out of those conversations you were having with people around your product? SEIF: I still don't think I'm good enough. You're just constantly learning, right? I just accepted I'm part of a team, and I have my contributions. But as an individual, I still don't think I know enough. I think there's more I need to learn at this point. VICTORIA: I wonder, what questions do you have for me or Joe? SEIF: How did you start your podcast, and why the name? VICTORIA: Oh, man, I hope I can answer. So, the podcast was started...I think it's, like, we're actually about to be at our 500th Episode. So, I've only been a host for the last year. Maybe Joe even knows more than I do. But what I recall is that one person at thoughtbot thought it would be a great idea to start a podcast, and then they did it. And it seems like the whole company is obsessed with robots. I'm not really sure where that came from. There used to be a tiny robot in the office, is what I remember. And people started using that as, like, the mascot. And then, yeah, that's it, that's the whole thing. SEIF: Was the robot doing anything useful or just being cute? JOE: It was just cute, and it's hard to make a robot cute. SEIF: Was it a real robot, or was it like a -- JOE: No, there was, at one point, a toy robot. The name...I actually forget the origin–origin of the name, but the name Giant Robots comes from our blog. So, we named the podcast the same as the blog: Giant Robots Smashing Into Other Giant Robots. SEIF: Yes, it's called transformers. VICTORIA: Yeah, I like it. It's, I mean, now I feel like -- SEIF: [laughs] VICTORIA: We got to get more, like, robot dogs involved [laughs] in the podcast. SEIF: Like, I wanted to add one thing when we talked about, you know, what gets me going. And I want to mention that I have a six-month-old son now. He definitely adds a lot of motivation for me to wake up in the morning and work. But he also makes me wake up regardless if I want to or not. VICTORIA: Yeah, you said you had invented an alarm clock that never turns off. Never snoozes [laughs]. SEIF: Yes, absolutely. VICTORIA: I have the same thing, but it's my dog. But he does snooze, actually. He'll just, like, get tired and go back to sleep [laughs]. SEIF: Oh, I have a question. Do dogs have a Tamagotchi phase? Because, like, my son, the first three months was like a Tamagotchi. It was easy to read him. VICTORIA: Oh yeah, uh-huh. SEIF: Noisy but easy. VICTORIA: Yes, yes. SEIF: Now, it's just like, yeah, I don't know, like, the last month he has opinions at six months. I think it's because I raised him in Europe. I should take him back to the Middle East [laughs]. No opinions. VICTORIA: No, dogs totally have, like, a communication style, you know, I pretty much know what he, I mean, I can read his mind, obviously [laughs]. SEIF: Sure, but that's when they grow a bit. But what when they were very...when the dog was very young? VICTORIA: Yeah, they, I mean, they also learn, like, your stuff, too. So, they, like, learn how to get you to do stuff or, like, I know she'll feed me if I'm sitting here [laughs]. SEIF: And how much is one dog year, seven years? VICTORIA: Seven years. SEIF: Seven years? VICTORIA: Yeah, seven years? SEIF: Yeah. So, basically, in one year, like, three months, he's already...in one month, he's, you know, seven months old. He's like, yeah. VICTORIA: Yeah. In a year, they're, like, teenagers. And then, in two years, they're, like, full adults. SEIF: Yeah. So, the first month is basically going through the first six months of a human being. So yeah, you pass...the first two days or three days are the Tamagotchi phase that I'm talking about. VICTORIA: [chuckles] I read this book, and it was, like, to understand dogs, it's like, they're just like humans that are trying to, like, maximize the number of positive experiences that they have. So, like, if you think about that framing around all your interactions about, like, maybe you're trying to get your son to do something, you can be like, okay, how do I, like, I don't know, train him that good things happen when he does the things I want him to do? [laughs] That's kind of maybe manipulative but effective. So, you're not learning baby sign language? You're just, like, going off facial expressions? SEIF: I started. I know how Mama looks like. I know how Dada looks like. I know how more looks like, slowly. And he already does this thing that I know that when he's uncomfortable, he starts opening and closing his hands. And when he's completely uncomfortable and basically that he needs to go sleep, he starts pulling his own hair. VICTORIA: [laughs] I do the same thing [laughs]. SEIF: You pull your own hair when you go to sleep? I don't have that. I don't have hair. VICTORIA: I think I do start, like, touching my head though, yeah [inaudible 33:04]. SEIF: Azure took the last bit of hair I had! Went away with Azure, Elasticsearch, and the shock collar. VICTORIA: [laughs] SEIF: I have none of them left. Absolutely nothing. I should sue Elasticsearch for this shit. VICTORIA: [laughs] Let me know how that goes. Maybe there's more people who could join your lawsuit, you know, with a class action. SEIF: [laughs] Yeah. Well, one thing I wanted to also just highlight is, right now, one of the things that also makes the company move forward is we realized that in a single domain, we proved ourselves very valuable to specific companies, right? So, that was a big, big thing, milestone for us. And now we're trying to move into a handful of domains and see which one of those work out the best for us. Does that make sense? VICTORIA: Yeah. And I'm curious: what are the biggest challenges or hurdles that you associate with that? SEIF: At this point, you don't want just feedback. You want constructive criticism. Like, you want to work with people who will criticize the applic...and you iterate with them based on this criticism, right? They're just not happy about you and trying to create design partners. So, for us, it was very important to have these small design partners who can work with us to actually prove ourselves as valuable in a single domain. Right now, we need to find a way to scale this across several domains. And how do you do that without sacrificing? Like, how do you open into other domains without sacrificing the original domain you came from? So, there's a lot of things [inaudible 34:28]. And we are in the middle of this. Honestly, I Forrest Gumped my way through half of this, right? Like, I didn't know what I was doing. I had ideas. I think it's more of luck at this point. And I had luck. No, we did work. We did work a lot. We did sleepless nights and everything. But I think, in the last three years, we became more mature and started thinking more about product. And as I said, like, our CEO, Neil, and Dominic, our head of product, are putting everything behind being a product-led organization, not just a tech-led organization. VICTORIA: That's super interesting. I love to hear that that's the way you're thinking about it. JOE: I was just curious what other domains you're looking at pushing into if you can say. SEIF: So, we are going to start moving into ETL a bit more. We're trying to see how we can fit in specific ML scenarios. I can't say more about the other, though. JOE: Do you think you'll take the same approaches in terms of value proposition, like, low cost, good enough latency? SEIF: Yes, that's definitely one thing. But there's also...so, this is the values we're bringing to the customer. But also, now, our internal values are different. Now it's more of move with urgency and high velocity, as we said before, right? Think big, work small. The values in terms of values we're going to take to the customers it's the same ones. And maybe we'll add some more, but it's still going to be low-cost and large-scale. And, internally, we're just becoming more, excuse my French, agile. I hate that word so much. Should be good with Scrum. VICTORIA: It's painful, but everyone knows what you're talking about [laughs], you know, like -- SEIF: See, I have opinions here about Scrum. I think Scrum should be only used in terms of iceScrum [inaudible 36:04], or something like that. VICTORIA: Oh no [laughter]. Well, it's a Rugby term, right? Like, that's where it should probably stay. SEIF: I did not know it's a rugby term. VICTORIA: Yeah, so it should stay there, but -- SEIF: Yes [laughs]. VICTORIA: Yeah, I think it's interesting. Yeah, I like the being flexible. I like the just, like, continuous feedback and how you all have set up to, like, talk with your customers. Because you mentioned earlier that, like, you might open source some of your projects. And I'm just curious, like, what goes into that decision for you when you're going to do that? Like, what makes you think this project would be good for open source or when you think, actually, we need to, like, keep it? SEIF: So, we open source libraries, right? We actually do that already. And some other big organizations use our libraries; even our competitors use our libraries, that we do. The whole product itself or at least a big part of the product, like database, I'm not sure we're going to open source that, at least not anytime soon. And if we open source, it's going to be at a point where the value-add it brings is nothing compared to how well our product is, right? So, if we can replace whatever's at the back with...the storage engine we have in the back with something else and the product doesn't get affected, that's when we open source it. VICTORIA: That's interesting. That makes sense to me. But yeah, thank you for clarifying that. I just wanted to make sure to circle back. Since you have this big history in open source, yeah, I'm curious if you see... SEIF: Burning me out? VICTORIA: Burning you out, yeah [laughter]. Oh, that's a good question. Yeah, like, because, you know, we're about to be in October here. Do you have any advice or strategies as a maintainer for not getting burned out during the next couple of weeks besides, like, hide in a cave and without internet access [laughs]? SEIF: Stay away from Reddit and Hacker News. That's my goal for October now because I'm always afraid of getting too attached to an idea, or too motivated, or excited by an idea that I drift away from what I am actually supposed to be doing. VICTORIA: Last question is, is there anything else you would like to promote? SEIF: Yeah, check out our website; I think it's at axiom.co. Check it out. Sign up. And comment on Discord and talk to me. I don't bite, sometimes grumpy, but that's just because of lack of sleep in the morning. But, you know, around midday, I'm good. And if you're ever in Berlin and you want to hang out, I'm more than willing to hang out. VICTORIA: Whoo, that's awesome. Yeah, Berlin is great. I was there a couple of years ago but no plans to go back anytime soon, but maybe I'll keep that in mind. You can subscribe to the show and find notes along with a complete transcript for this episode at giantrobots.fm. If you have questions or comments, email us at hosts@giantrobots.fm. And you could find me on Twitter @victori_ousg. And this podcast is brought to you by thoughtbot and produced and edited by Mandy Moore. Thanks for listening. See you next time. Did you know thoughtbot has a referral program? If you introduce us to someone looking for a design or development partner, we will compensate you if they decide to work with us. More info on our website at tbot.io/referral. Or you can email us at referrals@thoughtbot.com with any questions. Special Guests: Joe Ferris and Seif Lotfy.

Headline Mission Daily Report Sep 18, 2023 1. ราคาดัชนีตลาดหลักทรัพย์ / ราคาหุ้นต่างประเทศ / ราคาน้ำมันดิบ / ราคาทองคำ / ราคา Cryptocurrency 2. Morning Talk: ถ้าย้อนเวลาได้ คุณจะกลับไปช่วงเวลาใดของชีวิต? 3. อัปเดตสถานการณ์น้ำท่วมที่ประเทศลิเบีย 4. วิกฤตหนัก เอลนีโญ อินโดนีเซียต้องการข้าวจากไทยจำนวนมาก  5. เร่งด่วน เซเลนสกี ต้องการเข้าพบ โจ ไบเดน  6. Nasa ตั้งฝ่ายค้านตรวจสอบรายงานและการค้นหาเกี่ยวกับ UFO 7. ภารกิจสำรวจดวงจันทร์และดวงอาทิตย์ ของอินเดีย 8. ตะลึง!! Sony เปิดตัวชิปใหม่ ไม่ง้อแบตเตอรี่  9. Sony รับบริจาครอยยิ้ม หุ่นนยนต์ Aibo ส่งต่อให้กับองกรค์ที่ต้องการ 10. เจ้านายสายลุย VS ลูกน้องปากแจ๋ว 11. Tiktok ถูกปรับ 368 ล้านดอลลาร์ 12. อัปเดตประเด็นร้อนการเมืองประเทศไทย 13. ส่อถูกยกเลิก!!! โครงการแลนบริดจ์ เพราะหาผู้ลงทุนไม่ได้  14. เลื่อนจัดส่ง IPhone 15 หลังขายดีจนผลิตไม่ทัน 15. Morning talk: ถ้าย้อนเวลาได้ คุณจะกลับไปช่วงเวลาใดของชีวิต?

Headline Mission Daily Report Sep 18, 2023 1. ราคาดัชนีตลาดหลักทรัพย์ / ราคาหุ้นต่างประเทศ / ราคาน้ำมันดิบ / ราคาทองคำ / ราคา Cryptocurrency 2. Morning Talk: ถ้าย้อนเวลาได้ คุณจะกลับไปช่วงเวลาใดของชีวิต? 3. อัปเดตสถานการณ์น้ำท่วมที่ประเทศลิเบีย 4. วิกฤตหนัก เอลนีโญ อินโดนีเซียต้องการข้าวจากไทยจำนวนมาก  5. เร่งด่วน เซเลนสกี ต้องการเข้าพบ โจ ไบเดน  6. Nasa ตั้งฝ่ายค้านตรวจสอบรายงานและการค้นหาเกี่ยวกับ UFO 7. ภารกิจสำรวจดวงจันทร์และดวงอาทิตย์ ของอินเดีย 8. ตะลึง!! Sony เปิดตัวชิปใหม่ ไม่ง้อแบตเตอรี่  9. Sony รับบริจาครอยยิ้ม หุ่นนยนต์ Aibo ส่งต่อให้กับองกรค์ที่ต้องการ 10. เจ้านายสายลุย VS ลูกน้องปากแจ๋ว 11. Tiktok ถูกปรับ 368 ล้านดอลลาร์ 12. อัปเดตประเด็นร้อนการเมืองประเทศไทย 13. ส่อถูกยกเลิก!!! โครงการแลนบริดจ์ เพราะหาผู้ลงทุนไม่ได้  14. เลื่อนจัดส่ง IPhone 15 หลังขายดีจนผลิตไม่ทัน 15. Morning talk: ถ้าย้อนเวลาได้ คุณจะกลับไปช่วงเวลาใดของชีวิต?

Las cosas buenas y malas de los iPhone 15 / Energía gratis del ruido EM / Multa a los NFT de Hollywood / Lituania y la operación ANOM / Thunderbolt 5 Patrocinador: Si estás cansado de tarifas complicadas en tus conexiones, y de sorpresas en tu factura: hazme caso y pásate a O2. La compañía de fibra y móvil más transparente y sencilla, con la mejor atención al cliente, y las conexiones de mayor calidad. — Por ejemplo, por 35€ al mes tienes conexión de fibra de 300 Mbps y una línea móvil con 30 GB de datos. Descubre todas sus tarifas en O2Online.es Las cosas buenas y malas de los iPhone 15 / Energía gratis del ruido EM / Multa a los NFT de Hollywood / Lituania y la operación ANOM / Thunderbolt 5

This week's tech news: NASA Artemis 1 launch; Amazon's acquisitions, creepy?: Sony Aibo; Starlink, Tesla & T-Mobile; Moviepass returns;  Misdirected spam texts; Charging batteries; COVID test expiration; Recycle old TVs; Streaming

This week Harry continues to explore advances in "digital therapeutics" in a conversation with Paolo Pirjanian, the founder and CEO of the robotics company Embodied. They've created an 8-pound, 16-inch-high robot called Moxie that's intended as a kind of substitute therapist that can help kids with their social-emotional learning. Moxie draws on some of the same voice-recognition and voice-synthesis technologies found in digital assistants like Siri, Alexa, and Google Home, but it also has an expressive body and face designed to make it more engaging for kids. The device hit the market in 2020, and parents are already saying the robot helps kids learn how to talk themselves down when they're feeling angry or frustrated, and how to be more confident in their conversations with adults or other kids. But Moxie isn't inexpensive; it has a purchase price comparable to a high-end cell phone, and on top of that there's a required monthly subscription that costs as much as some cellular plans. So it feels like there are some interesting questions to work out about who's going to pay for this new wave of digital therapeutics, and whether they'll be accessible to everyone who needs them. Pirjanian discussed that with Harry, along with a bunch of other topics, from the product design choices that went into Moxie to the company's larger ambitions to build social robots for many other applications like entertainment or elder care.Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.TranscriptHarry Glorikian: Hello. I'm Harry Glorikian, and this is The Harry Glorikian Show, where we explore how technology is changing everything we know about healthcare.Two weeks ago, in our previous episode, I talked with Eddie Martucci, the CEO of a company called Akili Interactive that's marketing the first FDA-approved prescription video game. It's called EndeavorRx, and it's designed to help kids with ADHD improve their attention skills.It's one of the first examples of what some people are calling “digital therapeutics.”And this week we continue on that topic—but with a conversation about robots rather than video games. My guest Paolo Pirjanian is the founder and CEO of Embodied.They've created an 8-pound, 16-inch-high robot called Moxie that's intended as a kind of substitute therapist that can help kids with their social-emotional learning.Moxie draws on some of the same voice-recognition and voice-synthesis technologies found in digital assistants like Siri, Alexa, and Google Home. But it also has an expressive body and face designed to make it more engaging for kids.Moxie Video Clip: Hi, I'm Moxie. I'm a robot from the GRL. That's the Global Robotics Laboratory. This is my first time in the human world. It's nice to be here. Oh, where is here, exactly? It's a pretty big world for a little robot.Harry Glorikian: Moxie hit the market in 2020, and parents are already saying the robot helps kids learn how to talk themselves down when they're feeling angry or frustrated, and how to be more confident in their conversations with adults or other kids.But just like EndeavorRx, Moxie isn't inexpensive. The robot has a purchase price comparable to a high-end cell phone, and on top of that there's a required monthly subscription that costs as much as some cellular plans.So, it feels like there are some interesting questions to work out about who's going to pay for this new wave of digital therapeutics, and whether they'll be accessible to everyone who needs them.Paolo and I talked about that, as well as a bunch of other topics—from the product design choices that went into Moxie, to the company's larger ambitions to build social robots for many other applications like entertainment or elder care.So here's my conversation with Paolo. Harry Glorikian: Paolo, welcome to the show.Paolo Pirjanian: Thank you. Hey, for having me on the show.Harry Glorikian: Paolo, you're the co-founder and CEO of a company called Embodied. And and you guys are in the field of, I'm going to call it educational robotics. But this is not your first robotics company, right? Can you can you start by filling in listeners about your history in the consumer robotics field?Paolo Pirjanian: Absolutely. Yeah. So I actually got my education in Denmark. I got a PhD in A.I. and robotics and then moved to the US actually to work at NASA's JPL. Which was a childhood dream job. Shortly thereafter, I got approached by Bill Gross of Idealab, who started one of the earliest incubators, who wanted to start a robotics company. So I joined that company as the CTO originally and then eventually became the CEO. We developed Visual Slam Technology, which is a vision based, camera based ability for a robot to build a map of the environment and know how to navigate it autonomously. That company in 2012 was acquired by iRobot. And we integrated that technology across Roomba and the other iRobot portfolio products to allow them to be aware of the environment and know how to navigate around the home, primarily for cleaning the floors. I was a CTO there for a couple of years and then decided to move on to do something that's been a childhood dream, to really create AI friends that can help us through difficult times in our lives.Harry Glorikian: But one of the projects you worked on, and correct me if I'm wrong, was the Sony's Aibo Robot Dog, right? It's not necessarily educational, but it was aimed at kids. So what sort of drew your focus on robotics for education and socialization, I want to say.Paolo Pirjanian: Yes, correct. Sony Aibo, the robotic dog, my previous company, we developed a computer vision technology for it that enabled the robot to be able to see things and interact with things in the environment. And it was an amazing product, actually, the Sony Aibo. And I've always actually had interest in let's call it mental health. And of course, my craft is AI and robotics. And so after my last company was acquired, I decided the timing is now to go pursue that childhood dream of creating robots that can actually help us with mental health. So we don't categorize ourselves as education in the strict sense because we do not really focus on STEM education. We focus on for children. The first product is for children. It's called Moxie, and it's helping them with social emotional skills, learning, which in layman's term you could describe as EQ, emotional intelligence skills versus IQ, which are more related to STEM type education.Harry Glorikian: Yeah. And it's it's supposed to complement traditional therapy if I was reading everything correctly.Paolo Pirjanian: Exactly. Exactly. We don't believe in replacing humans in the loop. We want people to be treated by humans. But given the shortage and cost of mental health services, there's always room for complementing that with AI and other technologies. And that's what we are doing.Harry Glorikian: So if I ask the question, is Moxie more like a toy that's supposed to be fun, or is it a tool that's supposed to be therapeutic or correct some help help a child that's using it or is it both?Paolo Pirjanian: It's primarily a tool to help children with social emotional learning, things that you would go to a therapist for. The analogy that I use that may be helpful here is really Moxie is a tool to deliver therapy to children. But we we have to make it fun enough for the child to want to take that pill. So in a way, if you use pharmaceuticals as an analogy, a pill usually for children is sugar coated because you want them to take the pill to deliver the medicine to them. So the same way here, Moxie has a lot of fun activities and interesting things that attract a child to want to interact with Moxie. And then during those interactions, Moxie will find the opportunity to deliver techniques and therapies, for instance, to teach the child about mindfulness, teach them about emotion regulation, teach them social skills, to teach them about empathy and kindness, talking about your feelings and so on.Harry Glorikian: I know many adults that may need Moxie for sure. With all those categories you mentioned. Right.Paolo Pirjanian: I agree.Harry Glorikian: But but let's talk about the range of challenges, problems or issues that you've designed Moxie to help with. So can it help with relatively mild issues like shyness, or is it designed to help kids with more severe issues like, Autism Spectrum Disorder or all of the above?Paolo Pirjanian: Yeah, no, it's first of all, you're talking about the audience that it's appropriate for. Obviously, children that have been diagnosed with any neurodevelopmental challenges such as autism need to be trained on social emotional skills. But neurotypical children also can benefit from it. Actually in our customer base, we see a roughly 50-50 split between children that have mental, behavioral developmental disorders. And in the 50% are children that you would call neurotypical. But yet we know even within neurotypical children, they have to deal with things such as stress, anxiety, sometimes even depression. Covid obviously did not help it. It exacerbated a lot of mental health issues for every child, including adults, by the way, as you pointed out. And these techniques and tools that you use from therapy are really the same independent of the diagnosis. Now, some children may need more help with social skills. Let's say if there is a child on the autism spectrum, they may not be very comfortable making eye contact, which is an important social skill to have. When you're interacting with someone, you want to look them in their eyes and Moxie will help them, for instance, with that. And that's maybe something that a neurotypical child doesn't need. So Moxie will focus more on helping them with things such as coping skills, with coping with stress, coping with anxiety or managing anxiety, or even social skills. Like you can talk to Moxie about bullying and it will allow you to talk about it and understand how to navigate that and teach you skills about how to protect your own personal space. A lot of these foundational skills are are the type of skills that social emotional learning includes.Harry Glorikian: So. Let's talk a little bit more about the actual product. And because this is a podcast, I'm sort of like need to talk through some of the features, right? Because they everybody can't see it. But so on the hardware side, you know, the arms, the waist, it bends, the rotating ears, the rotating base, the ears, the face, the speakers, the camera, you know, the program that animates the face and gives Moxie, a personality, the computer vision elements. Right. And then all the scripts of all the different interactions. Right, you know. Why was it important to give Moxie an LCD screen as a face rather than mechanical mouth or eyes.Paolo Pirjanian: Yeah. Let me start maybe take a couple of steps back for the audience, as you said there are no visuals here. Think of Moxie as a AI character brought to real life. Right. So think of it as a, sorry, as a cartoon character brought to real life. So think of a cartoon character that has physical embodiment and it can talk to you. It can smile back at you. We can interact with you with body language and emotions and so on. To your question as to why it required a LCD display. We could potentially consider creating a mechanical face that can have enough expressivity, but that can add a lot of costs on one hand. On the other hand, if not done well enough, it can become uncanny and creepy. So we decided that the LCD display that, by the way, is very is curved because we did not want it to look like a monitor stuck in the head. But it was integral to the design. So it's curved and looks like a face. And what you see on the face is an animated character, Moxie's character, which is integrated very well with a hardware industrial design. So you can provide much more freedom of expression from facial expressions. And especially for children, you want to have a robot that has the ability to show facial expressions. By the way, the intonation of the voice will change as well, based on the type of conversation and the emotion we are trying to capture in the conversation.Paolo Pirjanian: And then the other question, actually, a macro level question becomes embodiment, why did this need to be embodied? Why physical? Why not just a digital character on a screen? Well, so, evidence from neuroscience, from MRI, fMRI scans shows that when we interact with something that has physical embodiment and agency, it triggers our mirror neurons, our imitation neurons are triggered at a much higher level and much wider level than when you're interacting with something just on a screen. And the implication of that is that things you can learn through interaction with the embodied agency have a deeper impact in terms of retention of the information, something that we may be able to anecdotally relate to during COVID. All education went online and the post mortem on that was that te quality of education that was delivered online doesn't compare to what happens in the classrooms. And that's, again, the same thing when it's not embodied. You don't feel that emotional connection. You don't feel an obligation. Many children will just turn off the monitor and walk away, whereas with something that's physically embodied, you feel you can't do that. It has feelings, you feel it has a perspective. You can't just turn it off. By the way, on Moxie, if you look at it closely, there are no buttons on Moxie. There is no input device on moxie like a keyboard or a touch screen or anything else. The way you interact with moxie is the way we interact with each other, using conversation, body language, intonation of voice, emotion, facial expressions and so on. There is one switch actually on the bottom of the robot that you don't see. That's for emergency situations in case something goes wrong. For certification reasons, we have to put that physical switch to turn it off if something goes wrong.Harry Glorikian: So not having played with it does, and only watching the video online, Moxie's voice synthesized like Siri or is it prerecorded? Like, how does it sound?Harry Glorikian: It's synthetic. Yes. So, yeah. So we cast the character of Moxie, decided what this character stands for, what are its values, what is the background story? And then based on that, decided the voice of Moxie, what it should be. And then the way you develop the synthetic voices that you take in neural network and train it based on a lot of samples that we captured from a voice actress in a studio recording hundreds and hundreds of hours of speech from a script. So we have this script and we know how it sounds based on the character's voice recording, and that gets fed into a deep neural network that is trained over and over again until it models that voice. So that later I can just give a text and it will generate a synthetic voice that sounds exactly like that character.Harry Glorikian: And then Moxie seems to emit a lot of sound effects and music. Does that element enhance the product somehow?Paolo Pirjanian: Yeah. So we can underline mood and so on with sound effects or background music. For instance, one of the activities Moxie will suggest if the child is talking about things that are have to do with stress and so on, is a mindfulness journey. Where it will ask you to close your eyes. Imagine you are in a forest or other places as well. There's a library of them. Let's say you're in a forest, listen to the wind and then it will start playing some sound effects in the background and calming music to get the child to imagine they're in that space. For some children that have high sensitivity disorders to certain stimuli like sound, the parents can actually, through a parent app, provide that information which will adjust the settings. In that case, Moxie will actually not use sound effects or any jarring effects that may disturb that child.Harry Glorikian: Interesting. So. Simple question, but is it battery operated? I mean, how long does it last on a single charge? Does it plug in?Paolo Pirjanian: Yeah, it's battery operated because the child usually likes to move it around. You carry the round almost like a baby on your arm. If you remember the days where we had young babies, it was literally ergonomically, it sits exactly right on your arm very nicely. And it has a battery that can run for hours of active usage. And then at night, usually like your cell phone, you plug it in any charges overnight.Harry Glorikian: So, you know, this begs the question of where did the idea of Moxie really come from? Because you don't decide on a whim to build a product this complex. You know, how did you persuade yourself and your investors that the technology is at a point where, you know, it could really make a difference with kids, you know, that have social emotional development issues?Paolo Pirjanian: Yeah. I mean, the idea was sparked probably early in my early childhood, I would say. So, very briefly at a very early age due to a war, my world was turned upside down. And unfortunately, I had to flee my my homeland and seek refuge in another country where I looked different, sounded different and was different. Right? And and unfortunately, as such, you do get rejected by the society. You have a harder time in school. You get exposed to racism and rejection and all these things. So. I remember during that time I saw the first animated short by Pixar. Which was Luxo Jr., the two lamps, mama lamp and baby lamp playing with a ball. Which blew me away that a computer can generate millions of pixels on the screen that are moving to create, to induce or elicit such emotion in the audience. So that inspired me to actually seek education in computer science and robotics and A.I. because before that, as many immigrants you were taught that you were going to be a doctor, so that that's.Harry Glorikian: Or a lawyer.Paolo Pirjanian: Lawyer comes second, but obviously doctor first. So so that inspired me actually to buy a computer and start coding by myself. And I started learning coding and then I decided I'm going to do well in high school so I can get into university and pursue my education. And I did. And to be honest with you, this has been something I've been wanting to do for since I can remember. My previous company, as I mentioned, Evolution Robotics, that was a Idealab company and I was the CTO then became the CEO. I wanted it to do it then, but that's almost a decade ago, or maybe slightly more than a decade ago. We even tried. It was not possible. Absolutely not possible. I remember back then. Just to use an example that I think most people can relate to, voice recognition for even a single command was hard. All of us have had in-car navigation systems with a voice assistant that you would press a button, hold it down and say navigation, and would pull up navigation and say, Enter your address. It will enter the address. And you would have, to by the time you were done, enter the address because it would constantly misunderstand you and then give you options. Did you say A, B or C and no, no, no. I didn't say that. By the time you were done entering the address, you were at the destination. So that was state of the art only a decade ago. Just for voice recognition. Same thing with computer vision.Paolo Pirjanian: My specialty actually was computer vision. Computer vision. Also, we couldn't recognize things very well. And the advancement that has happened in deep neural networks due to the increase in compute power, due to increase to labeled data sets that are available through many sources from YouTube and the Internet and so on. We have been able to solve age-old problems that for decades we were struggling with So it was not possible. The other piece that was probably not possible was that I was not ready as an entrepreneur probably to take on such a colossal challenge of building a product like this. So the stars aligned around 2015 when I decided to leave iRobot and said, You know what? The time is probably right now. And and fortunately, I was able to get some investors that believed in the vision of creating AI characters, AI friends that can help children with social emotional development. And obviously, this technology platform, we will in the future use it for also helping the elderly population with loneliness and Alzheimer's and dementia and so on. We have just scratched the surface with our first products, right? And there is a lot more work to do. But today it's possible. We have proven it. We have a product in the market. A five year old can will interact with it for months at a time without any human intervention. So yeah, so it was a series of events brewing over the last 30, 40 years for this to become possible today.[musical interlude]Harry Glorikian: Let's pause the conversation for a minute to talk about one small but important thing you can do, to help keep the podcast going. And that's leave a rating and a review for the show on Apple Podcasts.All you have to do is open the Apple Podcasts app on your smartphone, search for The Harry Glorikian Show, and scroll down to the Ratings & Reviews section. Tap the stars to rate the show, and then tap the link that says Write a Review to leave your comments. It'll only take a minute, but you'll be doing a lot to help other listeners discover the show.And one more thing. If you like the interviews we do here on the show I know you'll like my new book, The Future You: How Artificial Intelligence Can Help You Get Healthier, Stress Less, and Live Longer.It's a friendly and accessible tour of all the ways today's information technologies are helping us diagnose diseases faster, treat them more precisely, and create personalized diet and exercise programs to prevent them in the first place.The book is now available in print and ebook formats. Just go to Amazon or Barnes & Noble and search for The Future You by Harry Glorikian.And now, back to the show.[musical interlude]Harry Glorikian: I mean, just looking at the system, there's probably a lot of innovations that were required to put Moxie together. And so. I don't know, maybe you can give us a few, you know, like "Oh, my God" moments that took place in this, right? I mean. I don't know if it's the physical movements. I don't know if it's the, you know, personality or the scripts. But, you know, give us the highlights of what you think was like the big breakthroughs that made this possible.Paolo Pirjanian: Yeah. So there are many, many, many, many pieces of technology that we had to invent or partner for to make this happen. So   what I mentioned, deep neural networks, generally speaking, in the field of AI have advanced to the point where we can have very reliable speech recognition technology, for instance, right? Where you have an accent or not, you're speaking loud or soft and so on, you have background noise and so on, it will be able to transcribe what you're saying pretty accurately. There are still errors, but it's pretty accurate. It's accurate enough, let's put it that way. The next stage of the conversation pipeline is actually understanding. Now you have a transcript of what was said. Now I need to understand the semantics of what was meant, what was the intent behind this, this string of characters, and that's natural language understanding. In that area, Embodied has made huge advancements because we have to be able to understand what the child is saying. And the state of the art when we started is defined by Siri and Alexa and Google Home, where it's very command and response. "Alexa, play music for me. Alexa, how is the weather? Alexa, tell me a joke. Alexa, read a story or read the news for me." And so on. So short utterances and and direct mapping to a function that the device can do. Whereas in our case it's not about this transactional command and response, it's about relation and social interaction. So the child, Moxie will actually ask and encourage the child. It says, "So how was your day to day?" There is no way any human being can script all the possible answers that you could expect to hear because you could basically say anything possible to that question.Paolo Pirjanian: So we had to develop natural language understanding that can understand what was said no matter what was said, and provide a relevant response. Because if you don't, if the robot says something that's absolutely not related to what the child wanted to talk about, then children get disappointed. They say, well, this thing is a dumb robot. It doesn't doesn't understand me. And they will dismiss it, right? The illusion of intelligence breaks away very quickly as soon as you you misunderstand or say something off script, let's say. So we had to develop a combination of systems to be able to address that. Another major challenge, and this was actually much bigger than I thought, we spent a lot of time on this challenge to solve. Again, it has to do with interaction using Alexa as an example also, and Siri as well as Google. They all have this notion of a wake word, Hey, Google, hey Siri or Alexa. When you say this keyword known as a wake word, the device is actually at the, when it's on standby, it's putting all of its attention to look for that keyword before it does anything else. So as soon as you say it, a couple of things happen. It's almost like turning on a switch to say, I'm going to speak, right? So number one, you're telling it, I'm going to say something now. Number two, as soon as you have said that phrase, these things have multiple microphones on them. And the mic array allows you to be able to be informed and focus your attention on the location from which you heard this phrase. With doing that, you can also filter out anything that's in the background. So you focus the attention of the device on that location of the user that said Alexa. And then you say a phrase and then it processes and executes the action. In our case, in social interaction, it will not be appropriate if you had to say Moxie in every volley of the conversation. Every time you want to say a sentence to me, you would start by saying Paolo and I and I would look at you, and then you would say something, and then I would stop listening. And then you say, Paolo, for every sentence, right. That would that would be a very awkward social interaction. So we had to solve that problem. It's a tough problem to solve. And we use a combination of cameras to know where the child is, the voice, where it's coming from, and what was being said to focus the attention of Moxie on the person that's engaged with it so that Moxie doesn't respond to the TV or mom and dad maybe having a conversation on the phone over there and it filters all of that automatically, without the need for having a wake word phrase. And I can go down the list. There is many, many more. But this is just examples of the type of things we have to solve.Harry Glorikian: So, you know, I think some people might make the argument that kids should really be learning their social and emotional skills from other human beings. From a parent, from a teacher, from their peers, maybe their therapist if they have one. You know, how can a robot fit into that picture in a healthy, productive way? You know, how would you respond to the potential criticism, which I'm sure you've heard before. When a parent who buys Moxie for their kid, are they offloading their parental responsibilities?Paolo Pirjanian: That's an absolutely valid concern and a good question to ask. And obviously, even before inception of the company, I personally myself was thinking about this because there is a there's a contradiction in saying that a child that is not very good at social interaction, let's put them in front of a robot, they'll get better at it. There's a contradictory element to that potentially. Right. So let's put it this way. In the extreme case, what if the child does not have the ability to have interaction with their peers? Right. So they do not get the opportunity to interact with other peers from which they're actually learning to hone in their social skills. Well, that happened during the pandemic. There's a huge mental health crisis happening in the US now that will take years for us to to address. That was because children were locked in their home without the ability to socialize with other children because of worries about being getting COVID, right. So now pandemics are rare events that hopefully don't happen that often. But now let's put ourselves in the shoes of children that are, for various reasons, are not successful in providing social interactions. An extreme case is a child on the autism spectrum. That does not have the right skills to have social interactions nor interpret social cues in a conversation. Let's say if you're annoyed at someone on the spectrum, it's likely that they may not even understand that you're annoyed at them and they may keep saying the same thing or doing the same thing. That's going to make you more and more agitated or the other end of the spectrum, which is not as severe.Paolo Pirjanian: My example when I was a child. And I lived in a foreign country where I was different. I had an accent. I looked different. I came from a different cultural background and other kids didn't want to play with me. And there's everything in between. Right? So then. What do we do? Well, you can have therapies and that's what we do. There's a massive shortage of therapists. If you have a child, usually the way this works is that your school teacher will come and say, we think your your child may be on the spectrum or your child may have ADHD or your child have some other neurodevelopmental challenge. You should get your child diagnosed. Okay. Hopefully no one has to try this. The waiting list for getting diagnosed is minimum six months, minimum six months. And that's if you have connections and good providers and all these things. While imagine for six months your mind as a parent, you're like, dying. What the hell is going on with my child? I've got to figure this out quickly. Once your child is diagnosed and you spend 6000, 7000 hours on that, then you've got to find providers. There's a huge shortage of providers, and even when you get to the provider, there is a massive cost associated with it. So typically children on the spectrum, as an example, get diagnosed at the age of three or so. Ideally, actually, because the sooner you can intervene, the better the outcomes. And when they're diagnosed, they will be recommended to seek 20 to 40 hours of therapy per week. 20 to 40 hours of therapy per week. Yeah.Harry Glorikian: They're not doing anything else.Paolo Pirjanian: No. And many times, many times schools are supposed to provide it. But you have one or two special needs teachers that are to deal with the whole population of kids on the spectrum in their school as an example. So they're not going to get 20, 40 hours per week. The cost of therapy is super expensive. Insurance also has to pay for it. Nowadays, they're mandated to, but the cost still adds up. On average, a family will spend $27,000 out of pocket per year, even despite insurance coverage. So not everyone has access. And also if you live in rural areas and so on, you don't have access. So. Why not have an automated system that can do this, at least filling the gap? Right. We think of Moxie as a springboard to the real world. So we want to use Moxie as an opportunity to for the child to open up to Moxie, use that as an option, teach them a number of techniques for how they can be more successful in social interactions, and then Moxie will actually encourage them to go in the real world and experience these things and come and tell it about what what, how it went. So we use Moxie as a springboard to the real world. There is another phenomena that happens, and I don't know how to describe this. You may actually have more insights in neuroscience than I do. Children, especially children that have neurodevelopmental challenges, open up to a robot like Moxie better than they do to humans.Paolo Pirjanian: Let's take autism as an example again. I remember the very first experiment we did with our first prototype. We took that prototype to a family's home. They had a ten year old son on the spectrum, and we put Moxie down. At the time we did not have the AI yet. It was the robot remotely controlled by one of our therapists. On an iPad they were typing what the robot should do and say. The child immediately opened up and start talking to Moxie. And if you look at that child, you say. And you know, as a matter of fact, I asked Mom: "I don't see anything wrong with your child. Why do you think he's on the spectrum?" And he says, well, you have to see him how he treats his peers. He doesn't open up to them. He doesn't want to talk to them. When he comes home from school it takes me, mom, a couple of hours to "find," quote unquote, my child. Tuning into the channel. So they shut down. And there's a few reasons for for sort of, I think, anecdotal or maybe rational reasons to why that is. One is that children that are on the spectrum, they completely understand feelings and emotions and so on. They are not very good at expressing themselves or or showing their feelings, but they understand if they are being rejected or teased out in a conversation and so on. So they shut down. A robot is non-judgmental, right? They understand that it's a safe, non-judgmental space.Paolo Pirjanian: The other part is that when someone like me who comes with a warmer blood and too many gestures and intonation, voice and expressive, it's too much there's too many signals going on. And that's overwhelming to a lot of children on the spectrum. And they shut down. It's too much. I cannot deal with this. Right. And so hence, a robot is finding social doing social exercises and experiences on training wheels. And helping them develop those muscles and get better at how to handle different situations when they go in the real world to interact with their peers or other people in their circle, social circle, to be successful. And that success will hopefully breeds more success. So ideally we are successful when people actually stop using our product. And as a matter of fact, we have parents reaching out to us and say, my child could not stand up in front of their classroom to say a word. Now she stands up and gives a whole presentation and we have stopped using Moxie. Thank you so much for the help that that's what what it is. It's like it's stepping stone. It's training wheels for social emotional learning so that they can have a chance of being successful, because otherwise they do not have the chance to to have these exercises to learn. We learn a lot by interacting with each other.Harry Glorikian: So the company describes Moxie as just the first iteration of a larger platform that I think you call SocialX. So what is SocialX and what other kinds of products do you envision coming out of it?Paolo Pirjanian: Yes. SocialX is our technology platform, which which allows a machine to interact with us using real conversation, eye contact, body language, gestures, intonation of voice and and for the machine to do that as well as understand you on all those channels as well. That's what social platform is. The name SocialX is a juxtaposition to user experience, UX with an emphasis on the social experience. Right? We are creating a social experience. We are not just creating a user experience where you can push buttons or say a command, play music. Tell me the weather, what's the stock market like? But rather social interaction which involves social skills, emotion, skills, empathy and so on. And this is our first iteration. It's going to get exponentially more advanced. With every single user we add to our customer base, it allows us to improve SocialX because the data and the interactions that we can experience allows us to keep improving our algorithms to get better and better and better. So we decided to start with children because they are the most vulnerable in our society and we thought that's where we can have the most impact. The other end of the spectrum, where we become vulnerable again is when we are aging, right? And mental health is extremely important for aging people. And loneliness leads to a lot of mental health challenges that lead to a lot of physical challenges.Paolo Pirjanian: We know this. The surgeon general of U.S. said a couple of years ago that loneliness for elderly is equivalent to smoking a pack of cigarettes in terms of the health implications it has. And it's true. Again, during COVID, a lot of elderly that were alone suffered massively because they were high risk for COVID. Even my mom, who lives 5 minutes away from me, I didn't visit her for a few months until we sort of figured out that we think we know how to handle COVID so it was safe to to meet meet each other. It's extremely difficult. So that's the other end of the spectrum that we intend to address. And then in between every age group, in between that, from your teens to your aging, every person in their lifetime deals with mental health challenges. As a matter of fact, the US population, 17 percent of the population at any given time deals with mental health challenges stress, depression, suicidal thoughts and so on. And having a life coach that can help you through these difficult times, we believe can have a huge impact. So eventually with those three pillars, we will be able to help the entire population. You can go beyond mental health, which is what we are focused on, because that's where we think we can have the biggest impact you could imagine.Paolo Pirjanian: You go to Disney Park and you could have an interactive character coming up to you that's not a person inside a suit, but it's actually an animated character that's walking around and talking to you and entertaining you. You can imagine going to a hotel lobby where your intake to the lobby will be serviced by an interactive character, AI character. By the way, we are also working with hospitals and schools. Right now for hospitals we work with University of Rochester Medical Center. We are currently doing a pilot of using Moxie to help children, diabetic children, to educate them about how to treat themselves and how to adhere to their treatment plan. And then there is a number of other use cases that we are going to expand into, including intake to the hospital, dealing, sort of holding their hands and making sure they are not stressed out, coming to the hospital for the first time, pre-op and then post-op. Also a lot of complications you want to avoid by making sure there is someone to remind you about your care plan and so on. So to be honest with you, the sky is the limit. But the three areas we are focused on is children, elderly and then everyone in between that suffers from mental health or loneliness type of challenges.Harry Glorikian: Yeah, there are so many other applications that I can think of that I would, you know that I could use my self. So hopefully, that will come into play because this would be something interesting for me even to interact with, depending on, you know - Don't forget to work out or, you know, there's something that you interact with regularly. Right. But so let's go to sort of the crux of the some of the issues. Right. It's it's not an inexpensive device. I mean, it does a lot. So you can't expect that it's going to be inexpensive. Right. It's it's $999 to purchase plus a separate monthly subscription of about, what is it, $39 per month for a minimum of 12 months. And so how how do you get this out to a larger group of people that really need it. Is it subsidized purchases? Is it insurance? What are you guys thinking of from a business model perspective?Paolo Pirjanian: Yes. So we actually launched the product in the second half of last year for the first time and we sold out. But I agree with you that it would be much better if it was more affordable, because we don't want this to only be a product available for high income families, for rich kids to use a derogatory term maybe. We want it to be available to every every child. And for that to happen, there is a couple of different strategies we are pursuing. One is that once we get to a scale of efficacy studies that are convincing enough that we can get insurance, potentially insurance coverage to cover it or at least subsidize part of it to make it more affordable. The other approach is that we are working with bigger institutions such as hospitals and schools and libraries, by the way, which can buy it and make it available to their population. As an example, this library actually came to us, which is a very interesting business model that addresses the reach to the society that may not be high income. The library bought a fleet of Moxies from us, and they're lending them out to their society, to their members as a book. So a child gets to take Moxie home for a month and then bring it back, which is awesome because we have, by the way, we have done efficacy studies and it shows that even within a month you can see significant improvement on a lot of these social emotional skills.Paolo Pirjanian: But ultimately, that's that's how it goes. And also, just to put it in perspective to two examples. One is that robots of this nature....By the way, there is nothing like Moxie because the technology has not existed today, but people have tried, actually, SoftBank has a subsidiary called SoftBank Robotics that have spent hundreds of millions of dollars developing this robot called Pepper that costs $14,000 to buy and $2,000 a month to subscribe to it. Yeah. So we are orders of magnitude better than that. And that was part of the design principle that we said we want to be on par with an iPhone ownership of a cell phone. Buy it for roughly about $1,000. And you pay roughly about $50 a month in subscription. So we met that goal, which was a major accomplishment, very hard to do, but we are not satisfied with that because as I said, this has to be available. The other part of the other example is that if you have a child that needs therapy and if this cuts your therapy by a handful of therapy sessions, it pays for itself. Right? Again, ideally, we will have insurance pay for it. And so that will take some time. As you know, sort of navigating the medical fields and insurance organizations and so on will take some time, but we will get there eventually.Harry Glorikian: Yeah, I mean, I recently interviewed the CEO of Akili Interactive, Eddie Martucci, and they are the first group to get an FDA approved prescribed video game for children between eight and 12 years old with certain type of ADHD. And so, you know, they're using the prescription route as a way to have somebody pay for the clinical trials and everything else and the product itself. So I know that this business of robotics is not for the faint of heart. I mean, there's there's many different companies out there like Jibo, which was out here. Or I think there was a company in in San Francisco called Anki that, you know. You didn't pick an easy one, that's for sure, Paolo.Paolo Pirjanian: Definitely not. Definitely not.Harry Glorikian: But but, you know, I you know, I wish you incredible luck. I mean, this this thing sounds so exciting. I mean, it brings out, like, the Star Trekkie guy in me and wants to interact with it and have it do certain things or say certain things or or maybe even like interact with my wearable and be able to see something and then make a comment to me as I'm using it. So I can only wish you incredible luck and success.Paolo Pirjanian: Thank you. I need it and I appreciate it.Harry Glorikian: Excellent. We'll talk soon.Paolo Pirjanian: Talk soon, thank you so much for having me.Harry Glorikian: That's it for this week's episode. You can find a full transcript of this episode as well as the full archive of episodes of The Harry Glorikian Show and MoneyBall Medicine at our website. Just go to glorikian.com and click on the tab Podcasts.I'd like to thank our listeners for boosting The Harry Glorikian Show into the top three percent of global podcasts.If you want to be sure to get every new episode of the show automatically, be sure to open Apple Podcasts or your favorite podcast player and hit follow or subscribe. Don't forget to leave us a rating and review on Apple Podcasts. And we always love to hear from listeners on Twitter, where you can find me at hglorikian.Thanks for listening, stay healthy, and be sure to tune in two weeks from now for our next interview.

Drei Dingen schenken wir viel Zeit: Dem Googeln, den Video-Konsum und in Zukunft dem Gespräch mit Robotern. In allen drei Feldern bewegt sich etwas.

Welcome to the 32nd episode of The CEO Story Podcast!With weekly podcasts releasing, "The CEO Story" takes a deep dive into the success (and sometimes pitfalls) of being your own boss! We encourage each and every individual to candidly share their stories to help other entrepreneurs understand the highs and lows that come with the journey.As always be sure to check out more of our podcast episodes:Podcast Website - https://ceostory.buzzsprout.comYoutube - https://www.youtube.com/channel/UCasaMQttGpdFnIMeWXER1SQWebsite - https://www.togethercfo.com/Give us a Like on Facebook - https://www.facebook.com/TogetherCFO/Like our LinkedIn Page - https://www.linkedin.com/company/together-cfoGive us a Follow on Instagram - @TogethercfoIn this episode, I had the pleasure of interviewing Paolo Pirjanian.Paolo pirjanian is president and chief technology officer at Evolution Robotics. He holds a Ph.D. from the University of Aalborg, Denmark.NASA scientist turned robotics entrepreneur who has helped create technologies for many products ranging from the Sony AIBO to the iRobot Roomba.  Former CTO at iRobot and CEO at Evolution Robotics.Stay up to date with Paolo Pirjanian:Website: http://www.embodied.com/LinkedIn: https://www.linkedin.com/in/paolopirjanian/Embodied Inc LinkedIn: https://www.linkedin.com/company/embodiedinc/

This week’s episode brought to you by Slice on Broadway, and Sidekick Media Services. Celebrating 10 years of AwesomeCast! Original co-host Rob De La Cretaz returns and we hear from our friends from over the years! Chilla is looking at iOS14 accessibility features Dudders talks about the Animal Crossing Travel Guide app Rob deep dives the Wyze Cam Outdoor and the possibilities of outdoor videography Sorg played this week with the GeForce Now and Xbox XCloud streaming services on his newly acquired Samsung Galaxy S8 Brian submits his Airglide Navarro 110 inflatable kayak for Awesomeness Rizz and Doug discussed the end of Microsoft's Mixer NBA restart plan includes using Oura rings to catch COVID-19 symptoms Sony's Aibo robot will now greet you at the front door and consider a taxidermy opportunity WWDC News: iOS 14 has widgets, Apple ditches Intel for it's own Mac processors and CarKey for your iPhones. After the show remember to: Eat at Slice on Broadway (@Pgh_Slice) if you are in the Pittsburgh area! It is Awesome! (sliceonbroadway.com) Want to be part of our studio audience? Hit us up at awesomecast@sorgatronmedia.com and we’ll save you a seat! Join our AwesomeCast Facebook Group to see what we’re sharing and to join the discussion! Follow these awesome people on Twitter: Chilla (@chilla), Katie (@Kdudders), and Sorg (@Sorgatron) You can support the show at Patreon.com/awesomecast! Remember to check out our friends at the The 405 Media (@The405Radio), and Postindustrial Audio (@post_industry) who replay the show on their stream throughout the week! Also, check out sorgatronmedia.com and awesomecast.com for more entertainment; and view us livestreaming Tuesdays around 7:00 PM EST

This week’s episode brought to you by Slice on Broadway, and Sidekick Media Services. Celebrating 10 years of AwesomeCast! Original co-host Rob De La Cretaz returns and we hear from our friends from over the years! Chilla is looking at iOS14 accessibility features Dudders talks about the Animal Crossing Travel Guide app Rob deep dives the Wyze Cam Outdoor and the possibilities of outdoor videography Sorg played this week with the GeForce Now and Xbox XCloud streaming services on his newly acquired Samsung Galaxy S8 Brian submits his Airglide Navarro 110 inflatable kayak for Awesomeness Rizz and Doug discussed the end of Microsoft's Mixer NBA restart plan includes using Oura rings to catch COVID-19 symptoms Sony's Aibo robot will now greet you at the front door and consider a taxidermy opportunity WWDC News: iOS 14 has widgets, Apple ditches Intel for it's own Mac processors and CarKey for your iPhones. After the show remember to: Eat at Slice on Broadway (@Pgh_Slice) if you are in the Pittsburgh area! It is Awesome! (sliceonbroadway.com) Want to be part of our studio audience? Hit us up at awesomecast@sorgatronmedia.com and we’ll save you a seat! Join our AwesomeCast Facebook Group to see what we’re sharing and to join the discussion! Follow these awesome people on Twitter: Chilla (@chilla), Katie (@Kdudders), and Sorg (@Sorgatron) You can support the show at Patreon.com/awesomecast! Remember to check out our friends at the The 405 Media (@The405Radio), and Postindustrial Audio (@post_industry) who replay the show on their stream throughout the week! Also, check out sorgatronmedia.com and awesomecast.com for more entertainment; and view us livestreaming Tuesdays around 7:00 PM EST

Accountability is friction: On this week’s episode of Track Changes Paul and Rich sit down to chat about different types of accountability software. Whether it’s a CRM, a to-do list or an app, we discuss what works best for staying on track and getting things done. We talk about the importance of empathy and support and why tactics based on fear never work in the long run. We also discuss why some software is moving away from adding accountability into its workflows despite it’s importance.    Links:  Sony Aibo  Clippy  Pipedrive  Dash for Slack  Postlight Labs  Mirror  Peloton  Mother by The Police  Sydney Cummings - Youtube

Privacy, Google & Fitbit; Older iPhones need update; House call medical @HealApp; @Sony aibo get new skills; 5G Coverage maps; Russia's new internet

If complex systems science had a mascot, it might be the murmuration. These enormous flocks of starlings darken skies across the northern hemisphere, performing intricate airborne maneuvers with no central leadership or plan. Each bird behaves according to a simple set of rules about how closely it tracks neighbors, resulting in one of the world’s most awesome natural spectacles.This notion of self-organizing flocks of relatively simple agents has inspired a new paradigm of engineering, building simple, flexible, adaptive swarms that stand to revolutionize the way we practice medicine, map ecosystems, and extend our public infrastructure. We’re living at the dawn of the age of the robot swarm – and these metal murmurations help us create communications networks, fight cancer, and evolve to solve new problems for an age that challenges the isolated strategies of individuals.This week’s guest is Sabine Hauert, Assistant Professor in Robotics at the University of Bristol and President/Co-founder of robohub.org, a non-profit dedicated to connecting the robotics community to the world. In this episode, we talk about how swarms have changed the way we think about intelligence, and how we build technologies for everything from drug delivery to home construction.Visit our website for more information or to support our science and communication efforts.Join our Facebook discussion group to meet like minds and talk about each episode.Hauert Lab Website.RoboHub Website.NanoDoc Website.Sabine at Nature on the ethics of artificial intelligence.Sabine's 2019 SFI Community Lecture.Follow us on social media:Twitter • YouTube • Facebook • Instagram • LinkedIn

Sony Aibo 911 outage & security Roller coaster technology in Boring tunnel Tesla Store Experience Surgery students missing dexterity New study on longer life

Sony Aibo report INTERVIEW: Captain Hiller from NORAD Santa Call Santa on Google Home Is Amazon Prime getting worse? Elon Musk's Boring Company changes paths Privacy on Amazon, Google and Facebook Should you be using messaging apps?

Sony Aibo First look /  Can you do it? VitaminWater Challenge / Windows' Ugly Sweater / California considered a tax on text messages / Facebook bug reveals private photos / Apple News: Software update, Apple Watch warning, Apple music on Alexa / "Computer Vision syndrome" is a thing

On A Side Note Episode 12: You Won't Believe the Size of This Dik DikOn A Side Note episode 12:  You Won't Believe the Size of This Dik DikDrop A dollar in our hat: http://ko-fi.com/oasnofficialOur Patreon: https://www.patreon.com/OASNOur Twitter: https://twitter.com/OASNProductionsOur Twitch: https://www.twitch.tv/onasidenoteofficialOur RedBubble: https://tinyurl.com/OASNRBOur Discord: https://discord.gg/dt5cjKCGet Great Games Cheap at G2A: http://g2a.com/r/OASNThis week we talked about Dik Dik, Ken Penders, and Secret RailroadsKyle:http://steamcommunity.com/id/SegeMarlhttps://www.youtube.com/user/kenny0666https://twitter.com/SegeMarlhttps://soundcloud.com/segemarlJake:http://steamcommunity.com/id/StrangerJAKEhttps://www.youtube.com/channel/UC04MSywdydD6mHZbbKUZmsghttps://twitter.com/strangerJakehttps://soundcloud.com/strangerjakeJesse:https://www.youtube.com/channel/UCiKMoSwdaU02f1itZUyfAbQhttps://twitter.com/Player2X99https://www.instagram.com/player2x99/Trevor:https://twitter.com/cellr_dwellrDave:https://www.youtube.com/channel/UCRWlr5kl-QZ9DnIXXJWL5vAAaron:https://www.youtube.com/user/Whiteshadow467Recorded 08/23/2018Links------------------------------------------------------------------------Russian Ships - http://www.cnn.com/2009/WORLD/africa/01/14/somalia.piracy/index.htmlTear Drinking Butterflies - https://www.mnn.com/earth-matters/animals/blogs/phil-torres-video-shows-butterflies-drinking-turtle-tearsScary Tree - https://thumbor.forbes.com/thumbor/fit-in/500x0/filters%3Aformat%28jpg%29/https://specials-images.forbesimg.com/imageserve/5b7c81de4bbe6f48a94e523b/0x0.jpgYou wont believe [NSFW] - http://www.mandatory.com/living/1067224-you-wont-believe-the-size-of-these-animal-penisesDik Dik - https://en.wikipedia.org/wiki/Dik-dikThe Louvre Pronunciation - https://www.youtube.com/watch?v=4qb9wRsMiqQBread Dildo - https://en.wikipedia.org/wiki/Bread_dildoKen Penders - https://en.wikipedia.org/wiki/Ken_PendersUrinal cake story - https://twentytwowords.com/mom-finds-mysterious-fragrant-lump-in-her-bathroom-then-realizes-something-horrifying/?utm_source=deck&utm_medium=cpc&utm_term=influencer&utm_campaign=dm3Simpsons Words Spoken - http://toddwschneider.com/posts/the-simpsons-by-the-data/Abgus Oblong - https://www.angusoblong.com/Facebok Fugitive - https://www.reuters.com/article/us-facebook-ceglia/u-s-says-facebook-fugitive-paul-ceglia-arrested-in-ecuador-idUSKCN1L82HPASMR - https://en.wikipedia.org/wiki/Autonomous_sensory_meridian_responsealighn your chackras - https://longevity.media/how-to-activate-and-align-your-chakrasSony Aibo - https://gizmodo.com/sonys-aibo-is-one-dumb-dog-so-far-1828559275Oddjob is cheating - http://collider.com/goldeneye-007-oddjob-cheating/Dark Souls is Sexist - https://kotaku.com/souls-games-are-great-except-for-the-sexist-messages-f-1828561485Secret Railroad - http://www.reptoids.com/Vault/AllNewArticles/Tunnelsandshuttles.htmProfessor oak dead - https://kotaku.com/the-japanese-voice-of-pokemons-professor-oak-has-died-1828408810Albus Dumbeldor does is GAY? - https://www.cnn.com/2018/02/01/entertainment/jk-rowling-dumbledore-gay/index.htmlNerv agent North Korea - https://www.bbc.com/news/world-asia-43312052Hyoscine - https://en.wikipedia.org/wiki/Hyoscine------------------------------------------------------------------------

Tech’s version of the five families met today to get on the same page over election security, 23andMe shuts down its API just to be safe, robot puppies, and the weekend longreads suggestions.  Links:Google finds evidence of attack linked to Iran state media (Axios)Tech Companies Are Gathering For A Secret Meeting To Prepare A 2018 Election Strategy (Buzzfeed News)Microsoft Hit With U.S. Bribery Probe Over Deals in Hungary (WSJ)23andMe will no longer let app developers read your DNA data (CNBC)The Impossible Job: Inside Facebook’s Struggle to Moderate Two Billion People (Motherboard) The Betterment Weekend Longreads Suggestions:Late to the Driverless Revolution (WSJ)Posting Instagram Sponsored Content Is the New Summer Job (The Atlantic)THE UNTOLD STORY OF NOTPETYA, THE MOST DEVASTATING CYBERATTACK IN HISTORY (Wired)The Vanishing Idealism of Burning Man (The New Republic)Welcome to the Age of Privacy Nihilism (The Atlantic)A monstrous primer on the works of H.P. Lovecraft (Polygon) Bonus Link!Sony Aibo hands-on: An adorable robo-pup that needs training (Engadget)

In case you missed it, the robots are here. No, not the apocalyptic hordes of artificially intelligent machines that some believe are destined to enslave or eradicate us (hello, Boston Dynamics!), but the everyday devices and companions that are rapidly becoming commonplace. After decades of lofty sci-fi-inspired promises, robots like iRobot's Roomba vacuums and the many iterations of the Sony Aibo robodog are slowly carving out their places in our domestic lives. Even Amazon's Alexa is arguably a disembodied robot. A new entry into the field is Anki's Vector. Vector is a small tabletop robot with big features. First and foremost, unlike other "robots" like those from Sphero or even WowWee, Vector doesn't need a smartphone to control it. It's fully autonomous and loaded with sensors, enabling it to interact with and learn from its environment from the get-go. Vector is another milestone for Anki, a company that's had one of the most interesting stories in tech. Unknown to the world before its splash launch at Apple's Worldwide Developers Conference (WWDC) in 2013, the robotics company has come out with several products, including intelligent toy race cars and a previous, more limited robot, Cozmo. Where does the robustly funded company go next? And when will it move its robotics business into something more capable (i.e. not a toy). Anki CEO Boris Sofman dropped by Mashable's MashTalk podcast this week to give us the full story of his young company, why it's so focused on the "personality" of its robots, and what he sees in the future for domestic robots and AI.

It's another week, another Geekdays. Another Weekly Geek. Geekly week. Whatever the case may be, it's monday, and we have a new episode for you! Show notes and links: Tesla posts record $710m net loss as it struggles to produce Model 3 cars | Technology (theguardian.com) The Pentagon is working on a radio wave weapon that stops a speeding car in its tracks – TechCrunch (techcrunch.com) West Virginia candidate distorts reality in campaign ad (yahoo.com) Google Play Newsstand (google.com) Japanese Buddhist temple hosts funeral for 100 Sony Aibo robot dogs (mashable.com) An engineer modded a drone to rescue this puppy (theverge.com) Man admits to breaking into Pasadena Taco Bell to eat taco shells, police say – Pasadena Star News (pasadenastarnews.com)

Buy of the week; CES Products we liked: Sony Aibo robotic AI dog, Peloton, Propeaq glasses, Revl, Polaroid POP, PocketTalk, Eargo Max, Huawei Mater 10, The importance of using a VPN at WiFi Hotspots

Sony AIBO, Windows 10 Upgrade, HP Archives, Amazon, iPhone X, Belkin, Rapid X Sony's robotic dog Aibo is returning with AI

Tech Gifts on a budget; Pre-Pre Black Friday Sales; Amazon home broken screen repair, Fun shopping apps Wish and Tophatter; Google Assistant tells jokes and stories; YouTube TV, Dish Anywhere App, Top Movies of all time; The Orville

Chaosradio Express Nr. 15 blickt zurück auf einzelne Ereignisse der letzten Woche aus dem Technologiebereich. Zur Sprache kommen die Sicherheitslücke in Windows bei der Handhabung von Windows Metafile Dateien (WMF), die Einstellung der Produktion des Sony Aibo, die Einführung des Sony Reader, neue Prozessoren von Intel und eine kleiner Blick in die Podcastinglandschaft und sich dort derzeit entwickelnder Trends.