Dr. Jeremy Weisz: 17:46
This is great. elmerwheeler.net. If people want to check it out. Justin, it’s always a pleasure. I appreciate you sharing some of your hidden secrets on the shelf there with us. And people can check out, as we mentioned, AdSkills.com and AgentSkills.ai to learn more. And thanks, Justin. Appreciate it.
Justin Brooke: 18:06
Yeah, thanks for having me on this episode.
Dr. Jeremy Weisz: 18:09
Great resources, great people. I have Seva Ustinov he’s the founder of Elly Analytics. And Seva thanks for joining me. Tell people a little bit about Elly Analytics. And we’re going to get into favorite software and tools. And he’s a perfect person to talk about because he ran an agency for many years. Now he runs a SaaS company. So so talk about Elly Analytics first and what you do.
Seva Ustinov: 18:35
Yeah, thanks for having me here. So we do AI agents that automate ad management and not for everyone, but specifically for consumer software and services companies. So think about fintech healthtech apps. Anyone who generates leads, signups, or trials from their website. They need to manage ads at scale, and they have specific problems like delayed conversions, long-term LTV, and offsite revenue. So we centralize the data and run agents that automate your ads.
Dr. Jeremy Weisz: 19:13
What kind of companies are using it? I mean, I’m sure there are specific companies and there are agencies that use it too.
Seva Ustinov: 19:20
Mostly end customers, like internal teams that run ads. You can click on testimonials to see examples of clients. Yeah. So fintech companies.
Dr. Jeremy Weisz: 19:34
So they usually have like an in-house marketing person that’s using it or a marketing team.
Seva Ustinov: 19:40
Mostly yes. So they run like hundreds or thousands of ads at the same time, spending hundreds of thousands, sometimes millions of dollars per month. And they need to manage that volume of different ads, make decisions, scale, stop, and relaunch different ads. So we centralized data for them, calculated attribution models, and then ran agents that optimize ads for them.
Dr. Jeremy Weisz: 20:10
That’s cool. Yeah, I’ve actually got FlexPro Meals here. I’ve actually bought stuff from them before. See, I’m surprised by your background. And it looks like there’s a betting company, a betting and mattress e-commerce brand. So big e-commerce brands are good. I’m surprised from your background, running an agency previously for so many years, that you didn’t go that route of having agencies use it for all their clients.
Seva Ustinov: 20:39
We’ll get there eventually. It’s just like end customers. Like you see this specific niche. The first problem to solve is to centralize the data from back-end platforms, payment systems, CRM systems, and so on. And agencies typically don’t go that deep into the data side.
So we need to sell the solution to clients first, and then agencies can use it. Actually.
Dr. Jeremy Weisz: 21:05
What are what gave you the idea for this? Going from talking about the transition from agency to the software.
Seva Ustinov: 21:15
Well, I saw that, like for me, it’s so obvious to run like data-driven marketing to make decisions using data and numbers. And in e-commerce with e-commerce companies, it’s like an industry standard. Everybody tries to optimize for us, but for consumer software and services. They mostly optimized for leads for sign-ups. So some actions on the website or in the app, that don’t really translate to actual paying customers and revenue, because it’s a hard problem to get that data and attribution and automate that.
So it looked, and it still is a very big niche. Like this segment is in the top five segments of advertisers that don’t have a default solution. Like, if I ask marketers, like, hey, what do you who do you know to build attribution for, like, fintech companies, for healthcare companies, or for apps? And it’s like, well, I don’t know, maybe like for apps, it’s AppsFlyer for everyone else, like, I don’t know. So it’s still an underserved segment with very large potential and an opportunity to build a 100 million company.
Dr. Jeremy Weisz: 22:35
How did you get your first? Milestone client. Right. You started several years ago.
Seva Ustinov: 22:43
Yeah, that was relatively easy. Specifically because of the agency background. I just started talking to some of our existing customers and potential customers, and actually, I got the first five sales before we had a dedicated team for this product. So that was that.
Dr. Jeremy Weisz: 23:02
Sounds like the way to do it. Kind of pre-sold the, you know, funded the first version, I imagine.
Seva Ustinov: 23:11
Yeah, exactly. And we had some small scripts and things we did in-house with the agency. So it was not from, from scratch.
Dr. Jeremy Weisz: 23:19
Yeah. I mean, that’s how MailChimp, I believe, started as an agency. And they were doing email internally for the clients, and they came up with like a separate, you know, SaaS solution that made it easier. So it came out of an agency.
Seva Ustinov: 23:32
Yes. That’s what got me, like, actually started questioning my roles. First, I met a community of founders, maybe 100 of them, who built tech businesses like software businesses, and like 60% of them told me a story that they ran some kind of services business before, like a web studio, design, agency, or something like that. And I’m like, okay, this looks like a standard path for interpreters, for interpreters. To start with, the services businesses first, get your expertise, team management, sales skills, and everything in place, and then convert it to building a large-scale product thing.
Dr. Jeremy Weisz: 24:17
Yeah, yeah, because I was just looking it up as we’re talking about stuff and it says and this is obviously a unicorn, not all cases but MailChimp it looks like sold for $12 billion to Intuit.
Seva Ustinov: 24:30
Crazy crazy. Yeah.
Dr. Jeremy Weisz: 24:31
Right. So started it from like an agency to building out a software solution. Right. So hopefully early analytics has a similar type of trajectory and success. Talk about we’ll talk about some tools. Some of your favorite tools software Plurio AI agent I see on your site. What’s that.
Seva Ustinov: 24:52
That’s the name of our agent. So we are analytics. And we’ve built our own agent that analyzes the data and actually manages ads. So we started as a data platform to get all the data. And now we run AI agents that actually analyze it and take actions.
Dr. Jeremy Weisz: 25:10
Awesome. So some of your favorite software tools I’ll mention some interesting ones. I’ve had on the podcast, the founder of Zapier on Wade Foster, one of the founders of Zapier. That was an interesting one, talking about how that got built up. One of the co-founders of Pipedrive also was a good one. What are some of your favorite tools, software that you use or your clients use?
Seva Ustinov: 25:38
We actually integrate with Zapier, with Pipedrive and many others. That’s fantastic.
Dr. Jeremy Weisz: 25:43
Who else? Who are some of the other integrations? I’m going to pull up. It’s under the connectors page.
Seva Ustinov: 25:48
Yeah, yeah. Like HubSpot, Salesforce, Zoho CRM, Klaviyo, Shopify, Google Analytics, all kind of mobile analytics, like basically anything. But yeah, talking about software, I think this year’s top one piece of software is Corsair and not as a tool for developers, but actually as a tool, as a generic, powerful AI agent for marketing for founders and managers right here. Yeah. So everybody knows cursor as a like ID like a development platform.
AI development platform for developers where they can type code things run like write code, debug code and so on. But what I found out is that you can actually use the same platform to do a pitch deck, to draft an email to a potential customer, to run a deep research on your competitors to automate. Second, opinions on hiring people. And like that’s, that’s that’s changed my my own work life. And that changed the whole company’s internal life and processes and everything.
Dr. Jeremy Weisz: 27:21
Love it. Yeah. What are some other ones you use? I see, I’m just looking through the your. I always like to explore people’s connectors because then it’s like, what else should I be using to connect to this software? But you may like this one. I did an interview with the AI clone, okay, of Brian Halligan, Co-founder of HubSpot. So it was with his AI clone, not with him. Just to be clear, because I had the founder of Delphi AI. I don’t know if you’ve seen that before.
He helps clone people. You know they have to enter a bunch of inputs in. But I could have a conversation with someone like through Delphi AI so people could check that out. But this is with his AI clone.
Seva Ustinov: 28:09
So I, I’m so curious. I’ll definitely do.
Dr. Jeremy Weisz: 28:11
That. I’ll I’ll send it to you. What are some other your favorite. So cursor. That’s a good one.
What are some other ones that you use on a daily basis? It could be apps on your phone. It could be on the computer.
Seva Ustinov: 28:23
I haven’t forgot how it’s named like launch keys or something. Or Minimalist, Minimalist app. So this is how my Android looks like. No icons, no nothing. Just a list of apps. And if I need to find something, I just have to type it to type the name.
Dr. Jeremy Weisz: 28:43
Just to like productivity perspective or what.
Seva Ustinov: 28:46
Yeah. So it’s it’s just reduces distraction from the apps so much because you have to like have a specific intention. What exactly do you want to do with your phone and type the name of the app and do it. And there are no like colorful icons that are neatly grouped.
Dr. Jeremy Weisz: 29:06
I’m assuming this is it here. Minimalist.
Seva Ustinov: 29:08
Yeah, exactly. Yeah, yeah, I’ve been with it like for half a year, I think. And I won’t go back. Yeah, yeah.
Dr. Jeremy Weisz: 29:16
Wow. So but you could put some I got like phone calendar like some other things on there that you. It’s a one click also.
Seva Ustinov: 29:24
Yeah like ChatGPT music streaming but no social media, no messengers, no games or something. And it actually works. Yeah. What are other apps?
Dr. Jeremy Weisz: 29:40
Yeah. What other apps you use on your phone besides this one? Obviously you mentioned ChatGPT. I’m assuming you have slack on your phone. I don’t know, what are those other things you have?
Seva Ustinov: 29:52
I know, yes. ChatGPT. Obviously. Whoop. The health tracking.
Dr. Jeremy Weisz: 30:00
Okay. Device, you have the whoop band? Yep. I have an Oura Ring.
Seva Ustinov: 30:06
Cool. Yeah. And Perplexity and Comet. I use it for most of my searches online, both from the app and from the web.
Dr. Jeremy Weisz: 30:22
What about on your computer? What do you use or like internally for the team? What do you use for project management or SOPs.
Seva Ustinov: 30:29
It’s funny, like we used to use Confluence as a knowledge base for developers and product team. Now we scrapped it completely and moved everything to Cursor. So now we have agents and I can ask things like, hey courser, go check my our specs and tell me what kind of metrics do we get from TikTok? And if there is no specs for that, go to the code and explore that and answer me.
Dr. Jeremy Weisz: 31:02
So you have to connect cursor to like the different channels then for you. So it can kind of grab data.
Seva Ustinov: 31:10
So we’ve moved every thing from Google Drive to Cursor. We used to use Notion. We almost don’t do it anymore because most of that move to Cursor we use ClickUp for task management and project management. But every night the whole state of tasks and comments and everything is synced into Cursor. So our agents have access to that data and can run like in-depth analysis, answer complicated questions, create new tasks. We actually recently had the first example where Customer Success Manager created. Like downloaded the conversation with the meeting transcript with the client, asked cursor to update the project card and the list of tasks.
Create a new task and in click up with all the details based on the project context and that meeting transcript. And then our data engineer pulled up his Cursor and said it like, hey, go download, go read the details of this task and click up and implement it for me and for the first time, the whole analytical and engineering task was done in courser just by referencing a task in the ClickUp. It’s still not like a large scale operation like that. People like data engineers and engineers in general. They still needed to oversee and run these flows, but it was.
Dr. Jeremy Weisz: 32:48
Probably cuts out a lot of steps, I imagine, though.
Seva Ustinov: 32:51
Oh yes, a lot of questions, a lot of unnecessary meetings, a lot of simple checks. Like you now you need people only for hard stuff, for complex things, not for obvious ones.
Dr. Jeremy Weisz: 33:09
How else do you use ClickUp to Cursor?
Seva Ustinov: 33:12
So we have a a set of WIP coded scripts, like simple Python scripts that can be executed from cursor to create a task to add a comment, something like that. And we have a separate script that just downloads everything into MD files into Cursor every night. So our agents have full access to the full company knowledge.
Dr. Jeremy Weisz: 33:39
It’s pretty cool. We also use Clickup as a PM tool. I mean it’s a great, great tool. Really robust. What about from like a CRM or email perspective? What do you use?
Seva Ustinov: 33:51
We do use HubSpot, but I’m not sure if we’re going to use it at a larger scale because as of now, it’s just a system of record for set of deals and history of emails and interactions. But actual work is done with a cursor or other tools. And also like I run that like it’s an evening project I want to implement personal CRM in cursor with all of my contacts statuses. Follow ups? To do lists and I can. It’s already helped me draft like complex emails and track all my contacts there. It’s not there yet to completely manage my inbox, but maybe like after this holidays winter holidays, we’ll see where it goes. Ideally, I want it to help.
Dr. Jeremy Weisz: 34:54
Manage your inbox.
Seva Ustinov: 34:55
Everything fully manage my inbox and only ask like complex questions where my input is needed.
Dr. Jeremy Weisz: 35:02
Like will a pre-draft emails or how would it work?
Seva Ustinov: 35:05
Like there are two steps there. First one that is already working, just like one message at a time. It’s creates new contacts. If I don’t have them, it researches them on LinkedIn and on internet. It downloads all messages from LinkedIn and email, so I have full history of conversation with each person and its updates are like action points. What we discussed from meeting transcripts, from emails, from LinkedIn messages. So I have the full state of like what I promised to each of my contacts. And the next step is to actually, like draft those emails based on my talking points, key updates, full history of interactions with this person and everything.
Dr. Jeremy Weisz: 35:57
It’s really interesting. What other AI tools are you using? I mentioned Cursor, ChatGPT like I’ve been using heavily Gemini inside of Gmail to help with some of those things. I’m curious, what else do you use like AI tools to just from a productivity or efficiency standpoint?
Seva Ustinov: 36:16
I think 90% of my AI use went to Cursor and within Cursor I use colored sand at 4.5 max. One obvious thing I use Parallel AI. Parallel AI. It’s the best tool for deep research. It’s even better than Gemini and ChatGPT. And like when I have like some really, really deep question, I always ask Parallel AI. I use most of the others as well. Notion AI.
Dr. Jeremy Weisz: 36:54
This is Parallel.ai.
Seva Ustinov: 36:56
- Yeah, yeah, yeah. And you can use it from the web interface, from the app, or from your Corsair cloud code, your own products and so on. So it’s both like a web interface and an API.
Dr. Jeremy Weisz: 37:10
Yeah. This is most accurate deep and wide research.
Seva Ustinov: 37:15
And it’s true. So like if I do a competitor analysis I tend to use this one. If I search for other important details about health insurance for the next year, I’ll use Parallel AI, not something else.
Dr. Jeremy Weisz: 37:34
Yeah. Any other software apps that you recommend that you use?
Seva Ustinov: 37:43
I don’t want to go that wide. There are like so many apps out there out there. I just like I big believer in this generic AI tools like Cursor, Cloud code, Antigravity by Google just really was released recently. It’s just, you see like using ChatGPT and Gemini and others as a question answering machine is cool, but it’s just like ten 5% of what I can do for you and any kind of actual engine.
Dr. Jeremy Weisz: 38:19
You’re talking about?
Seva Ustinov: 38:20
Yeah, yeah. Like all as of now, they are all branded as developer tools. But like, just ignore that. It’s a generic AI agent that can work with any kind of text data. It can create and run code, it can connect to any kind of systems or where they have connectors or not. It’s a thing that can run like 30 minute workflows autonomously, and it listens to what you say. And you can ask it like, hey, when we do competitor analysis, take into account like founding grounds and pricing pages and user reviews, and it will save it and next time you ask it to do. It will follow your workflow. So those generic AI agents, they are already here. They’re just branded for developers. But you can. But actually anyone can use it even without a zero understanding of the code you know.
Dr. Jeremy Weisz: 39:18
So first of all, I want to thank you. Everyone could check out ellyanalytics.com to learn more who should be going to your site. Big e-commerce brands. Who who should be checking this out.
Seva Ustinov: 39:32
So companies that spend hundreds of thousands of dollars on Google ads, Meta ads, TikTok influencers, affiliates and like similar channels, and especially those that generate signups or trials or leads from their website. So for e-commerce, there are a lot of tools out there already for consumer software and services. We are pretty much the only one that can help them.
Dr. Jeremy Weisz: 39:58
Seva, thanks so much. Check out ellyanalytics.com. I’m here. This is a top resource series where we talk about some of the favorite resources founders have. I’m here with Paul Powers and he’s a Co-founder of Physna. You can check him out Physna.com and Physna is short for Physical DNA. And they bridge the gap between physical and digital, and they do that by turning 3D representations of parts into normalized code, which we’ll go more into. Paul, thanks for joining me and talk about what you do.
Paul Powers: 40:29
Thanks for having me. Sure. You gave a great intro. So you have your physical DNA. What are our core technology does is, as you mentioned, turns everything physical via 3D, whether that’s a scan or a CAD model or whatever into code. And the reason that that’s important is because traditionally, unlike things like images or text or even videos, 3D data, 3D models are not actually normalized. So there’s no way for software to actually understand and interpret a physical item in all three dimensions the way that it can understand text or images. And so by normalizing that, it’s helpful for a number of areas. One 3D data is much more information rich than images are or than words, of course. And so as a training signal for AI machine learning.
It’s much, much stronger. And by bridging that gap and really allowing people to understand or allowing software to understand what parts are and how they’re related to each other and how they’re different from each other. It enables machine learning and AI to to learn at about 10,000 times the rate that it can if you don’t normalize that data. So it’s very, very valuable for AI, for it’s really the what makes physical AI and world models possible. And beyond that, we work with customers directly for a handful of use cases that are, you know, not just AI in general, not just API’s that we leveraged for with other tech, but actually people using directly, kind of as you’re seeing on the screen. And that’s typically around part identification, deduplication, standardization and also part sourcing. Right. So do I have this part. Am I ordering the exact same part from different suppliers. Are there different parts that I could standardize across Who sells this part?
Who can manufacture this part? And then those are the. Well, those are the core use cases. The the fact that we understand models so well means that we can be leveraged via our APIs to give much deeper insights. So you might use things like Palantir Foundry, right. Or you might use something like Google’s Gemini product. And what you can do is plug that into that and create a physical AI layer that understands your inventory, understands the parts that you order, understands the parts that you’re manufacturing or designing, and can just exponentially accelerate the everything from the design process to the maintenance speed to the procurement speed, to lowering manufacturing costs. Automating quoting. There’s quite a lot you can do once you implement that understanding of your physical data.
Dr. Jeremy Weisz: 43:02
And your customers are typically automotive and aerospace type customers.
Paul Powers: 43:07
Automotive, aerospace, really, anyone who manufactures or deals with lots of complex parts has a more immediate need for us than anyone else. We, of course, work with companies that manufacture a whole lot of very simple parts, like consumer packaged goods. Right? But typically what we find is that people who work with or manufacture or consume lots of complex assemblies. So things like, you know, like what you’re showing there right now might be lawn mowers, might be refrigerators, might be airplanes, might be automotive, and also a lot in defense. So those are the areas that where we typically see the fastest adoption because they have some of the most pressing needs.
Dr. Jeremy Weisz: 43:47
So would like a manufacturing company use your technology on top of their shopping cart to make it easier for people to buy.
Paul Powers: 43:58
You can. Yeah, we have APIs that allow you to do that, right? So you can say, hey, what is this part that I, I found something that fell off of an engine. Who has it? This company does.
There you go. It’s connected to it. Right? We actually already have that. And so we actually.
And the Department of War. Now a lot of them are using to source parts. Exactly that process. Right? What is this part? Who sells it? Even if they call it something totally different, right? We’re able to figure that out. What’s crazy is that 3D intelligence actually enhances computer vision.
And so we’re not recreating computer vision. But what we’re able to do is take the learnings from the 3D relationships that we’re able to understand and make it easier for computer vision to understand the differences between things that are more obscure, or where the differences are very hard to pick up on visually. Like think the difference between different bolts, nuts, screws, you know. Washers. I mean, things that are very, very different. Like they look almost identical. There’s very, very small differences. Traditionally computer vision struggled with that. It’s better with faces. It’s better with, you know, like text obviously or really or things that it sees quite often. But we make it just as easy for computer vision to differentiate between different bolts and washers, etc.
Or even more complex parts, as it is for them to differentiate between things like Coca-Cola versus Pepsi. Right. So that’s one of the reasons why we’re used not just in manufacturing design and inventory, but also out in the field for maintenance. We even have consumer level applications that we’ve been used for or are used for now. Lots of tech partnerships where we’re leveraged, where people actually have no idea the 3D intelligence is making computer vision smarter. But it is.
Dr. Jeremy Weisz: 45:39
This is really cool. Paul and I know this is highly technical, so we can go down the route of like, how did you even get into this? But I do want to hear some of your, your favorite apps, software and what you’re using for business for personal. What kind of things are you using these days?
Paul Powers: 45:59
Sure. So I use a lot of AI. I think that it’s important to stay current with AI. It’s it’s developing very rapidly. So obviously a big user of ChatGPT, Gemini. All the all all the common suspects. But then I also like to use actually, I think more importantly than like what I use is how I use them. Right? So I use things I use ChatGPT for more than what the average person would use, because I actually will go create my own GPT and it becomes like my own personalized app, or I’ll use it to do things that I normally would download a separate app for. So I actually find myself using LLM interfaces more often than app interfaces.
And that’s actually one of the reasons why with Physna we said, hey, we have to make sure that we can integrate with every LLM out there and we create, you know, we actually just released that recently so that you don’t have to use our interface. Right. You can use whatever’s most convenient for you. So that’s what I typically rely on both professionally and personally. But outside of that obviously, you know, things like the Google Suite. So Gmail, Google Calendar, Google Meet, things like that. Also a big user of, you know, for for business purposes, things like Omniverse, Palantir Foundry. You know, those are the technologies that we’re fascinated by that we integrate really well with.
Dr. Jeremy Weisz: 47:14
Talk about maybe an interesting use case of ChatGPT and how you’re using it.
Paul Powers: 47:21
So I use it for calorie monitoring, right. For example, like I’ll every time I eat anything, I will either enter the calories and protein macronutrients or if I’m lazy, I’ll just take a picture of it or describe what I’m eating, and then it’ll just calculate that. And then I’ve told it via building a really basic GPT, like here, here’s my weight, here’s my resting metabolic rate, you know, analyze if I’m consuming above or below maintenance calories and if I’m getting the right macronutrients in there. So I’ve done that to help lose weight and to live a healthier lifestyle.
Dr. Jeremy Weisz: 47:59
And so instead of an app per se, Paul, you’ll be like, okay, I have a I don’t know how you set it up, but I have a project in ChatGPT and all the custom prompts and everything in there. So you could just say, here’s the food intake. Like, how does it set up? Yeah, because you’re using it kind of like as an app, right?
Paul Powers: 48:17
Yeah, I use well, initially I set up a GPT four, but then I found that actually with 5.2 it was unnecessary to to really even need a GPT. So I just actually go to regular ChatGPT and just say in a regular conversation, hey, this is, you know, this is the baseline information. And then every day when it’s a new day, I’ll literally just say new day. And then it.
Dr. Jeremy Weisz: 48:36
Resets.
Paul Powers: 48:37
Like basically a conversation inside of ChatGPT that you just.
Dr. Jeremy Weisz: 48:40
Keep on going. Conversation. Exactly. For obviously for work, I’ll use it differently. One thing I found really powerful is integrating Llms with more with our our data. Like my my calendar, my email. So being able to just ask ChatGPT like, hey, what was going on recently with this one conversation with this one customer saved me a ridiculous amount of time, right? And it’s not just ChatGPT I also use Gemini. Gemini in some ways is a lot more powerful, I’m finding, than ChatGPT, and I think it’s just fundamentally changing the way that we interface with technology that’s only going to accelerate. I’m also a big adopter of of augmented reality, so I use things like not wearing them right now, but like Meta Ray-Bans display, they’re not quite to like. I’ve seen those where I think.
Dr. Jeremy Weisz: 49:30
I’ve used the Oculus Quest, but I don’t know what that that is.
Paul Powers: 49:35
Yeah, we’ve got basically everything here because we’re believers that eventually that’s going to be something that will overtake the smartphone in large part not now, but in a few years when it becomes lighter, more user friendly. Meta Rayban display specifically is pretty new. It just came out like November, I think, and it is just a really small it’s not even really fair to call it augmented reality. It’s just a little small screen on the right side of your glasses and you can talk to it and, you know, analyze your environment that you’re in. It’s not quite to a point where I find it valuable enough to use it on a regular basis, to be honest. That’s not what.
Dr. Jeremy Weisz: 50:15
We’re talking about right here.
Paul Powers: 50:16
It’s exactly what we’re talking about. It’s also kind of heavy compared to my regular glasses, but it’s way more user friendly than did you get.
Dr. Jeremy Weisz: 50:22
Like, prescription lenses inside of this or what do you. How did you do that? You did okay.
Paul Powers: 50:28
Yeah. So I find that really cool to use too. And I’m not so much I don’t know that I would suggest that people go out and get that, but I would definitely keep an eye on the space. I think that in the next couple of years, we’ll start seeing apple glasses, you know, probably Google Pixel glasses or whatever they’ll call them. And I think that’s going to be a lot more compelling than.
Dr. Jeremy Weisz: 50:44
What do you use this? Like how do you use these glasses.
Paul Powers: 50:47
So use that to I mean, to be honest with you, I don’t find a whole lot of utility in them, primarily because the battery life isn’t that great. By the end of the day, they’re dead. But when I do use them, it’s typically because I’ll be driving and I want to be able to, you know, hear the messages is coming in or be able to see them. And when I was traveling in the past, over New Years, when we were in Mexico, I found it valuable because I don’t speak Spanish, but I can do a live translation. Didn’t work backwards, but at least can understand what they were saying, what we’re saying, and then I could show them on the phone what I meant to say.
That was kind.
Dr. Jeremy Weisz: 51:23
Of how did you understand? Is it show? Is it, input it and then transcribe it and back to you. In English.
Paul Powers: 51:29
It’s like closed caption on the display.
Dr. Jeremy Weisz: 51:31
Captioning.
Paul Powers: 51:32
I just see it translated into English. That’s it’s not perfect. You can definitely see some areas where I’ve made some mistakes, but you get the gist of what they’re saying anyway.
Dr. Jeremy Weisz: 51:41
Any other cool technology that you use? Maybe, you know, hardware?
Paul Powers: 51:46
Yeah. So I’m actually well, I haven’t received it yet, so I can’t say how good or how bad this is, but I’m in the group of early adopters for the neo robot, which obviously is not going to be fully autonomous when it first comes out. That’s from, I think, One X technologies or whatever they’re called. So that’ll be neat though. It’d be like the first true, like human like household robot. So we’ll see how good that ends up being. I’m also a big adopter.
Dr. Jeremy Weisz: 52:16
When is that supposed to come out?
Paul Powers: 52:17
I think it’s supposed to be later this year, later this year or early next year, if I remember correctly. So that’s fascinating. I’m also for myself.
Dr. Jeremy Weisz: 52:25
What will you use it for? I’m curious.
Paul Powers: 52:28
Honestly, I don’t even have a specific use case in mind. I’m just so fascinated by the technology that I like to be on the cutting edge and see figure out what can you use this for, right? And figure out what role can we play with technologies like these and enhancing them and making them more effective? That’s why we’re big on, you know, trying things out in the augmented and virtual reality space, not because there’s an immediate, obvious use case, but because we want to figure out how might people utilize our software and our capabilities later in the future as this technology develops. So for me, it’s mainly a business curiosity. That said, I’m not paying for it out of the business, I’m paying for it out of pocket because I’m sure that I’ll find something stupid for it to do around the house, and that’ll be the main thing it does. But my curiosity is mainly actually for business applications at first.
Dr. Jeremy Weisz: 53:11
Fascinating, yeah. Any other hardware you use? I don’t know if you use anything else for health.
Paul Powers: 53:17
I do a lot of. I do a lot of 3D printing, you know, also started the site things like things but with an A we then sold that to Shapeways, but that actually grew to be the world’s largest 3D printing community. It’s over. I’m not sure where it’s at today, but when we sold it, it was about 25 million monthly active users. So pretty, pretty big community there.
And you know, obviously we got really big into 3D printing from that. Outside of that and augmented reality, I’m also a big adopter of wearables. So I typically will get like the latest smartwatch or something. And just again, trying to figure out what’s the next hardware phase of technology going to be beyond software.
Dr. Jeremy Weisz: 53:59
Are there any wearables That you’ve either heard of that you want to look into, or that you’ve gotten that people should check out?
Paul Powers: 54:08
You know, I’m honestly so far, I mean, the reason why I’m curious about this space is because I expect a lot of improvements to come in the pretty near future, but so far it’s not quite where I’d expect it to be. I think that long term we’re moving towards technology being more one spatially aware, which is what business is all about. Right? But then to being able to understand context better, right. Which again would be helpful for it to be context aware, it needs to know not just your location, but your current surroundings visually and the context of what you’re living in.
I think you’re going to find you’ll have to reach for your phone less often once you start wearing smarter, lighter, smart glasses that have longer battery life because they’ll be able to guess what you’re going to ask, what you’re going to want to do, right? Preemptively give you directions if you’re, you know, in getting into your car, and it knows that you always ask for directions. Right. You know, things like that. I think you’re going to find less need to reach for your phone than you do today.
And so I’m looking for how that future is going to develop. Right now, as far as devices I would recommend, there’s not a whole lot that I would say you need to rush out and get, but I would closely keep an eye on the augmented reality space and the personal robotics space. I bought my mom a robot, a robot vacuum cleaner that has a robot arm that can pick up socks and throw them into a bin for her. Because she’s as nerdy as I am. And so that was like the coolest thing ever. So things like that are fun. But in practical terms, augmented reality and maybe a little more versatile robotics reality.
Dr. Jeremy Weisz: 55:41
If it folded socks. You had me sold. Yeah.
Paul Powers: 55:44
It picks them up and throws them. Yes.
Dr. Jeremy Weisz: 55:47
Just to just to wrap up. Well first of all thank you. And people can check out Physna.com who should be checking out Physna?
Paul Powers: 55:58
If you work at a manufacturer or a like an OEM, like, say, at an automotive OEM, aerospace OEM, or at a tech company that’s working on AI. For example, you might be a prime contractor for defense. We do a lot of work in defense. If you’re a defense contractor, if you’re a manufacturer, or if you’re like an enterprise or even consumer AI type company, but you’re working in an area adjacent to spatial intelligence or computer vision, those are the companies that typically get the most immediate benefit out of Physna directly.
Dr. Jeremy Weisz: 56:34
I love it, Paul. Thanks so much everyone check out Physna.com we’ll see you next time.
Paul Powers: 56:39
Thank you.
