Conversations on Applied AI - Stories from Experts in Artificial Intelligence

Edge AI on-Chip Processing and Learning

June 21, 2022 Justin Grammens Season 2 Episode 17
Conversations on Applied AI - Stories from Experts in Artificial Intelligence
Edge AI on-Chip Processing and Learning
Show Notes Transcript

The conversation this week is with Rob Telson. Rob is an experienced sales leader with a demonstrated successful history working in the software and semiconductor industry, skilled and driving growth, negotiation, sales management, organizational leadership and technology. He holds degrees from the University of Arizona and Harvard Business School, and is the Vice President of Worldwide Sales and Marketing at BrainChip Holdings Limited, a company that is focused on software and hardware-accelerated solutions for advanced artificial intelligence and machine learning applications.

If you are interested in learning about how AI is being applied across multiple industries, be sure to join us at a future AppliedAI Monthly meetup and help support us so we can make future Emerging Technologies North non-profit events!

Resources and Topics Mentioned in this Episode

Enjoy!

Your host,
Justin Grammens

Rob Telson  0:00  

Now we're learning on the device, we're processing on the device. And we're consuming at least 50% less power than other architectures that exist today. So all this functionality in a very efficient manner is where brain chips can start really changing the world in regards to what you can do with your devices.


AI Announcer  0:25  

Welcome to the conversations on Applied AI podcast where Justin Grammens and the team at emerging technologies know of talk with experts in the fields of artificial intelligence and deep learning. In each episode, we cut through the hype and dive into how these technologies are being applied to real-world problems today. We hope that you find this episode educational and applicable to your industry and connect with us to learn more about our organization at applied ai.mn. Enjoy.


Justin Grammens  0:56  

Welcome, everyone to the conversations on applied AI Podcast. Today we're talking with Rob Telson. Rob is an experienced sales leader with a demonstrated successful history working in the software and semiconductor industry, skilled and driving growth, negotiation, sales management, organizational leadership and technology. He holds degrees from the University of Arizona and Harvard Business School. And as the Vice President of Worldwide Sales and Marketing at BrainChip Holdings Limited, a company which is focused on software and hardware accelerated solutions for advanced artificial intelligence and machine learning applications. So this is perfect, as we love to talk about applications of AI and ML here on the applied AI podcast. Thanks, Rob, for being on the show today.


Rob Telson  1:34  

Justin, thank you for having me. I'm really looking forward to this conversation.


Justin Grammens  1:38  

Likewise. Yeah. So I appreciate you taking me up on the offer to join us for a conversation here today. And I I mentioned that your brain ship, but you know, one of the things that I do like to ask people maybe is, you know, what was the path to get you to where to where you are today?


Rob Telson  1:51  

That's a great question. And, you know, I've been really fortunate, I started in the technology space by random circumstance. And I had been in sales my whole career. And I started in the EDA side of the world. So working with software applications to support then build out semiconductors and the circuit boards that go with that. And I've been fortunate enough to work for very large companies and very small companies that have either gone public or have been acquired. And so I've been able to experience a lot of structure and a lot of chaos along the way. But in the last 15 to 20 years or so a majority of my time was spent through two large organizations, one being arm, being able to join them through an acquisition, and then get involved in sales leadership there and drive a lot of success, as arm grew dramatically during that time, and run sales organizations for the Americas, as well as in the foundry side of the world and the manufacturing side and supporting all the partners in that space. And then also through a synopsis and working with them on building out their disruptive technology, business and supporting new incumbents coming to the new players into the semiconductor development space. And as I've evolved in my career, one of the things I've really appreciated is working in structured environments, but also working in unstructured environments, and build it out organizations building out models and, and really seeing the success, the fruits of the labor turn into something great. And so I've been at branch it now for a little over a year and a half, really, there was no sales infrastructure when I joined the company, and the marketing infrastructure wasn't there at all, and been able to build that out work with the right people to do that. And now we've gotten to a point where, you know, we've got sales, we've hired a very talented cmo who's joined us and his working out building out our marketing organization and doing a lot of exciting things on that end, which is allowing me to build out our sales organization and focus on that. And as well, then it's a lot of fun.


Justin Grammens  3:56  

Excellent, cool. Well, I mean, while you were at arm for quite quite a period of time, you probably have seen the sort of semiconductor industry really change and evolve over the, you know, 10 years or so. I mean, what are some things and it doesn't even need to be technology related, just from from the sales side? How is this? How is this industry really changed,


Rob Telson  4:12  

You got to put the last two years in a box and label it weird when you talk about sales, the whole process of selling in the business that we're in when it comes to developing semiconductors. And all the ecosystem around that is really about this is big investment. These companies that are building chips and going down this path are actually building products are spending hundreds of millions of dollars to do so. So finding the right partners that you can trust and you can depend upon and will make sure that you're successful is key. And so demonstrating that you're the right partner to do that, demonstrating that you're going to be answering the phone at two in the morning, when something in Asia didn't go right and the team in the region that you're in needs to support that is where it really comes Stand to play. And so the last two years have been weird because having that ability to get in front of new customers, companies trying to adopt technology and build that level of trust, through zoom, or through teens, or whatever it is, it's not the same as really sitting face to face and saying, Okay, let's map out how we're going to do this. But prior to that, I'll go back to the word that I've used a couple of times here, it's trust. It's really about being able to articulate and quantify the value of trust and selling on that. And knowing that the person sitting across the table from you or the team sitting across the table from you, knows that you and your team, not only are they technically capable of doing what you want them to do, but you're going to have their back. And that's I think, differentiates very successful salespeople and sales organizations, and those that struggled to get to that point.


Justin Grammens  5:54  

Yeah, it makes total sense. Yeah, I mean, that that is really about what a relationship or partnership is, is trusting that the other person is going to be there. Do you see manufacturing change from Asia? To the United States? You know, at all? Are you where do you see things? Or is there any advantage to bring it more onshore?


Rob Telson  6:10  

That's a tricky one, my friend, especially now the geopolitical dynamics are as heightened as they've ever been in our lifetime. But you have to go back 50 to 100 years to look the Industrial Revolution and look at how things have changed. I really implanted themselves as an industrial elite industrialized nation, and a leader in that and how they took that away from other nations who have their own industry and have their own manufacturing, but then realized that they didn't need to do it. So they dependent on countries like the US to do that. And unfortunately, as we've evolved in the United States, we've seen the same thing, where we become dependent upon other regions globally, to support some of the manufacturing that we could do on shore in the US, my gut feeling says, based off of the dynamics that are going on today, there will be more requirements where manufacturing is done regionally. So this isn't just a US thing, this could be a global dynamic for each country to be able to have their own manufacturing skill sets, and be able to sell be self sufficient in the environments that they're in.


Justin Grammens  7:16  

Totally makes sense. Yeah. Yeah, for sure. There's probably not a one size fits all. Yeah, exactly. Now, when it comes to brain ship, and maybe we can talk a little bit about like AI, like, I know, you guys create, basically advanced neural networking processors. Yeah, this is really cool stuff. Yeah, sounds fascinating. I want to know more about it,


Rob Telson  7:35  

You just press the go button on Rob, and I'm gonna sit and talk for a little bit now. But yeah, so what we do, which is really unique in the business, you know, when you look at AI, as of today, most AI is actually processed, not on a device, it's processed in the cloud. And then it goes back to the device. And I like to use, you know, let's use home personal assistance or your phone when you talk to your phone and ask it for directions. And you've ever had that experience where it tells you, I'm busy right now, or I can't answer that, and I don't get right. Basically, what it's telling you is I can't get this information to the cloud back to the device in milliseconds. So give me a second, I'll figure it out. And as technology evolves, warm, more demand is going to be put on devices at what we call the edge. These could be battery operated devices, such as a handheld device, or even a vehicle that's battery operated in the future. It could be industrialized machinery and applications, where there's a lot going on in and around it, it can be medical devices, either in a facility plugged into a wall or out very remote and third world countries where they don't have the electricity to work with. And so all of this ability to drive intelligence into these devices, is going to require the ability to do all the processing of the information on the device without being dependent upon the cloud. So as I said earlier, all of the information that's driven today is driven from device to the cloud back to the device. What makes friendship very unique is that we have the ability to do all this on the device without depending on the cloud. So we're going to be processing on the device. The other major addition or major differentiator that we have is that the way we're architected, we're using right off the bat at least 50% less power consumption to do so. Which means we're not dependent upon a lot of processing power in order to process the information, which allows us to be in these edge based devices, puts us in a very unique position. The third thing that we do that others don't do, and this is where it gets exciting, is that we do on ship learning. So now we're learning on the device. We're processing on the device, and we're consuming at least 50% less power than other architectures. exist today. So all this functionality in a very efficient manner is where brain chips can start really changing the world in regards to what you can do with your devices. And the most common talking point right now is in electric vehicles. And it's the common talking point, because basically, it's a dramatic shift from the traditional vehicle as of today to the amount of compute power that's going into that vehicle. But the drive isn't that the vehicles becoming more like a just a computer on wheels. The drive is I'm really scared to drive 300 plus miles, or 500 plus kilometers, because what if I lose my charge? What if my battery dies, and I'm out in the middle of nowhere. And that's where the differentiating technologies and the architectures that were based on which is neuromorphic architecture for AI is really going to drive things in a very unique way. Because now you can extend your charge, you get 1000 kilometers on a charge, maybe you can get 1000 miles on a charge. Now we're really getting excited when it comes to technology. And brain chips leading the way with what we've we've developed, which is our chip is called Akida. And as I just highlighted, we're based off of neuromorphic architecture. And that neuromorphic architecture means that we're processing our information, very similar to how a human brain works. And so you think about the human brain, there's a lot of energy that can be consumed with the way we process information. But the brain is designed not to consume energy. It's designed to process and focus on certain aspects of information at a time, whether that be vision, smell, taste, touch, whatever it is, it knows it's going to consume some energy over here, and then consume some energy over there, while the traditional AI engine as of today has to process all of this data and information at the same time. And because we're neuromorphic, we're processing where it needs to focus at the time and uses a process energy. And that makes us extremely efficient, still meeting the performance requirements that some of these semiconductors are going to need to meet to accomplish what they want to accomplish in the future.


Justin Grammens  12:18  

Fascinating. Yeah, really, really cool. Thanks for that rundown with regards to sort of how you differentiate yourself. You know, it's funny that you mentioned about all you know, having to go to the cloud. So I'll share a personal story, right, so my two little kids and they have a Lexus in their room. And we use them as alarms, right? So they have to, you know, the Alexa goes off, and very often just based on where they are on their house, they're a little bit further away from the Wi Fi hotspot. And so the alarm will go off in the morning, and there'll be yelling, you know, they're eight and 10 years old, they'll still say, Alexa, you know, stop alarm, and it won't stop. And the reason it won't stop is for that exact reason what you're talking about is it actually is not connected to the internet. They haven't actually built that switch in there yet, or enough intelligence in the Alexa to understand like, you know, you told me to stop, but I need to talk to the cloud even do something as basic as that.


Rob Telson  13:05  

Yeah, exactly. You know, that's where it gets really tricky. See, I have the opposite. I have fun with the Alexa, one of my teenagers has the Alexa. And you know, when if he's sleeping in went a little bit further on the weekend that I want him to sleep in. I can stand directly on No, just down the hallway, although his door is closed, and I can say, Alexa, tell me a story about Peter the rabbit. And all of a sudden, I'll hear Alexa, go, let me tell you the story of Peter the rabbit and my son, Dad, what are you doing? I was walking away with a smile on my face. Yeah, that's good. That's good. I use it to my advantage. So this, these are the things that we're very excited about. Because technology has gotten to a point where there's some really great things that we can do, as I said before, whether it be in the consumer applications, whether it be in transportation, whether it be for beneficial AI is what we focus on to give health care in a variety of different areas. So it's actually a point where there is a shift going on in brain chips going to be a part of that.


Justin Grammens  14:06  

Yeah, for sure. You know, you mentioned brains, there's actually a book called 1000 brains that I would suggest reading, if you haven't already, you know, we'll have liner notes and stuff like that in this podcast. So I'll have links to your website and your your profile. But it does talk a lot about sort of this idea of of what they know today with regards to how the human brain works. And you know, a lot of it is prediction models is is really what they're sort of coming down to, as you reach out and grab this glass of coffee that I have in front of me, for example, you know, your brain starts to anticipate, okay, I'm going to be touching this soon. But you know, efficiency is always key to per your point. So I think it's really cool how you guys have have really taken this idea of creating an architecture that again, I mean, energy is going to be the key to success here probably going forward, especially with remote applications. What are some particular applications are you guys in the agricultural space where you're, you know, sensing crops and stuff like that, or, I don't know, maybe, maybe fill me in a little bit more on some of these sort of like remote Lopa. Our usage cases that you see your chips ending up in?


Rob Telson  15:03  

Justin, it's a great question. I want to say we're everywhere, the amount of interest level in our technology and what we're doing. It's extremely broad. We've had some success, for example, with, with NASA and helping them in regards to get into orbit and being able to capture images and so on, using extreme low power devices, such as Akida, to other success, lied in the vehicle, and working with a German automotive manufacturer and having them utilize our technology to prove out their electric vehicle goals. And they, you know, announced that at CES, and we see that there's a great path that are for the future of between the two companies, as long as we continue to deliver on what they're, they're looking to what they're expecting us to deliver on, and other vehicle manufacturers as well, all the way to consumer electronics and applications in the consumer space, and medical devices. From that end, we've had a lot of interest in other areas, as you mentioned, like agriculture, and so on. The difference is the unique thing is, you know, as with any business, you have to focus on the areas where you can generate revenue. And so time to money is always a critical component to when we're talking to companies, what we're trying to accomplish, as well as, Wow, that's a really cool idea. And so you have to be able to balance, what are really cool ideas that will actually come to fruition, and applications that you can successfully leverage your technology and be able to communicate to the world that your company is a success. So you have this balance. And one of the unique things for brain ship is, you know, we funded our company, we took it public, and we are publicly traded on the Australian Stock Exchange, and also in the US, as well as I believe on the exchange in Germany. So we have a very strong following, and a lot of shareholders that are extremely passionate about the success of this company. And so we have requirements to go out and achieve success in the short term. But we also have to strategically put the right engagements in place for the long term as well.


Justin Grammens  17:07  

Yeah, so you're so you're dealing with say I have a company, I have an idea, you know, I want to build a smart coffee cup, for example, let's say some widget or something. And then I approach you guys and say, Hey, like how can I buy your hardware, but you guys must have some software and a software application stack on top of it as well like how much you guys then are engaged.


Rob Telson  17:26  

So our main focus it to be very straightforward. I'm going to take this sideways and bring it back. It's all gonna make sense in a second, our main focus is on licensing intellectual property. So basically, what we're trying to do is take our Akida technology, license it as IP to be designed into an SOC around a broader system. And we've had some success doing that we've engaged with Renesas, we've also engaged with a partner in Japan called megachips, who is an ASIC design house and has had a lot of success with Japanese customers in that space. And so we're building that business out, in order to drive the software dynamic of it, companies develop their AI models and their networks and convolutional neural networks or CNN, and those CNN can be built off of TensorFlow, they can build be built off of pytorch, or whatever. And so what we do is we have a software development flow that takes companies that develop their own cn ns. And then we optimize it into what's called a spiking neural network environment. So because we're functioning like the brain, the brain functions in spikes. So these are called SN ns. And so we have that whole software development stack. It's called meta TF, post TensorFlow. And we launched it in April of 2021. So just about a year ago, and since then, we've had over 5000, unique users start working with meta TF, but it's, it allows companies to take what they've already developed, they don't have to do anything different. It optimizes their networks, and an SDN environment gets them the highest level of accuracy. And if they're not getting the accuracy they want, there are steps to go back. We process it, we optimize it. And again, that's all automated. So we have that development flow in place. Now I bring all this up, because you asked two questions, you brought up the the idea of I want to do a smart coffee cup, I've come up with a great idea. You guys look like you have a really cool technology. How do I do that? We get a lot of that. Okay, and now that he is, you know, in the semiconductor space and building out systems, there's a lot of different components to build out a complete system. And we're only a small piece of that. So that's why we partner with companies like megachips to enable them to build out a complete SOC to support a customer in their environment, because you have some companies on the low end that need that support. You have other companies on the high end that have all the infrastructure, and all they're looking for is the IP and design it in so It's a very broad ecosystem. And I personally do a podcast on a monthly basis for brain shift. But what we do is I try to focus on the ecosystem and all the different components that are involved in the ecosystem, because I want people to understand it is kind of fragmented, there's a lot of different players that need to be involved in this. And that, you know, he who ties out his ecosystem, and has all the partnerships and all the relationships is the one that is going to end up winning at the end of the day, because it goes back to trust and meet able to solve the customer's problems.


Justin Grammens  20:37  

Yeah, for sure. I mean, what are you talking about things being fragmented, I actually just interviewed a guy yesterday for the podcast, and we were sort of lamenting how I've been in the in the IoT space for more than a decade here probably before was even called IoT. And, you know, you've got now 1000s of companies, everything from you know, low level chip design, you got fab houses, all the way up to people that are working just on pure applications, and API's and stuff like that. So, you know, in some ways, maybe the reason as to why the Internet of Things I believe, has been kind of like next year is going to take off next year, it's going to take off because you have this fragmentation going on, I feel I can just hurting everybody together, it can be very difficult, right? Everyone has their own wants and needs.


Rob Telson  21:18  

Yeah, in all fairness, it is taking, it's not, you know, zero to 1000 mph in one day, it's ramping up, it's getting widely accepted what we just talked about Alexa, for example, perfect example, it's built out. The really cool thing is, what's next. And I think, you know, in the next five years, our environments in our homes, are going to have so much intelligence built into it. For those that want that it's going to be there's gonna be some really cool applications.


Justin Grammens  21:50  

Yeah, for sure. I just don't know, if it's on the scale of the 100 billion devices by 2024, are they you know, just a lot of these things, they were they were predicting, you know, they were they were predicting just some some pretty insane numbers. And you're right, Alexa has been huge. I mean, if you if you package it up, and something as simple as that, you know, basically a smart speaker and give it to somebody in their home and they start using it, they will start finding uses for it. Right, I think what's been a little bit slow to come, I feel like is, you know, you mentioned some of the industrial applications. And and those, you know, there are companies that have bought in and they're in it, and they're really sort of pioneers, and they're charging them with the way forward. And there's and I talked to a lot of companies that are really sort of dipping their toe in this and they don't really know why they're doing it, or what is the value. But I think at the end of the day, and and I'll bring it back to a positive note is is the more intelligence you can put at the edge, the more power you can do. And so I kind of believe that this whole sort of tiny ml, all the work that you guys are doing, all the intelligence at the edge is going to start unlocking a lot of these scenarios that maybe weren't able to be done even, you know, as recent as three to five years ago.


Rob Telson  22:52  

Totally agree. And you know, I'll give you, as you're saying that, I'll give you five examples. If I can make it five. As we go through this, let's take medical devices, for example, the ability to take an image of, let's say, some type of lesion or something to that extent, that didn't exist before. And being able to capture that lesion, learn it on a portable device. And then notice that there are now 100 people in a community, a small community that are getting these lesions and recognize what that is and say, Okay, I understand what that is. This technology that's being driven by companies like brain ship that will be integrated into devices will help us get there quicker. And the ability to detect viruses such as COVID, through breathalyzers, and other aspects, or blood markers, and so on in a portable world, where we don't have to get in lines at large arenas, or whatever are to get tested, or something to that extent, and then being able to use those same devices to detect the flu, or something to that extent, I think, is massive, and we're on the path to do that. The ability to walk into your home and your kitchen every morning, and say good morning towards the kitchen and your coffeemaker turns on and starts making you a double espresso. Right, that's more of a luxury than a need. But at the end of the day, people will pay for that. The ability for your refrigerator to recognize something is rotten by smell. And when refrigerators more and more frigerators are gonna have panels on those panels tell you your milk spoiled or your broccoli is rotten. It's been in there for three weeks, whatever it is, you know, the ability for an industrial environment to have vibration detect. And so you know, there's a defection with a machine that costs a half a million dollars before it breaks down and stops the whole production line. All of these things can happen today. In all of these things are in the process of happening. When they go to market when they go to volume, they, you know, a lot of has to be executed upon from that. And I didn't even get into the good stuff we didn't we talked about vehicles or drones or flying taxis or all the stuff that's coming our way.


Justin Grammens  25:17  

Yeah, for sure. How do you think this is more of a philosophical question, but I do like to ask people this, when they're on the show is, you know, how do you think this affects then the future of work, I think about drones, for example, you know, you could have drones go out and do a lot of inspection, a lot of maintenance, right? They're actually, you know, flying and taking a look at, but we'd like wind turbines. And that was something that a human would have to do and climb up and take a look at this stuff. They're flying drones out there and out to do it. And they're taking all sorts of imagery, and they can on device probably do a lot of the stuff that we're talking about. So yeah, how do you think do you guys think much about that? I think, do you think it's a net positive net negative net neutral,


Rob Telson  25:51  

I think it's been neutral, I don't think it's going to change the amount of people that are working in might change the role of what they do. We're doing some stuff in our office with drone technology right now. And we're tinkering on some pretty cool stuff, it's still going to take someone to operate the drone to have the drone do what it wants to do, for example. So although let's use wind turbines, for example, you're not going to need to have a guy who risked his life on a daily basis by climbing up a giant wind turbine to do inspection and detection. Now, he's going to be operating flying devices fly up there, capture images of the ball bearings or the main engine area, and then be able to recognize where they need to spend their time fixing turbines. And again, this is a complete hypothetical, right? But for the purpose of our in the same thing can be go all the way down to an automotive environment, and being able to look at in gyms or components within an automobile, and be able to determine wear and tear. And instead of having a mechanic, get beneath the chassis, to do something, there's going to be all the diagnostics that they can do. Within then they're doing some of that today, but all the diagnostics capture those images, apply it into a system where it can recognize image a looks very similar to this issue over here. So I do think that it's going to be a net neutral, it's not going to replace the amount of activity that we do in the workforce, we will leverage these technologies for that. And there will be areas where YouTube apply AI, and it can, you know, be 90% accurate. But we still find in a lot of the exercises that we do. There's a human element to a lot of what we do that you can't take away.


Justin Grammens  27:42  

A great well said for sure. You mentioned some of the applications that you guys do. I mean, tell tell me a little bit more about that. I mean, are you guys just sort of maybe when you talk to customers, or you just you know, you're coming up with some sort of like a testbed or some sort of example applications be like have you thought about, you know, here, here's some neat ways in which you can use brain ship, as I guess, have a little lab or a little place where you test out some of these ideas.


Rob Telson  28:01  

You know, we moved to a larger facility at the beginning of the year. And for the first time, we've got a lab and a demo room, and separate from each other. So we're building a ton of stuff out, the team comes to me with ideas that you get it for the listeners, you can go to our YouTube channel at branch at EAC. And we have a ton of our media, we have demos that are professionally done. And we have demos that that aren't professionally done. And you can see that the evolution of the company and how we're going about doing things. But we're doing some fun stuff right now. And one of the things that we talk about that really makes us unique is that we want to be as close to the sensor as possible. And the sensors are what gather that data, that information. And what our AI engine does, or what Akita does is it takes all that sensor data, and it breaks it down and processes the necessary information in a very efficient manner. So one of the things that we focus on are the five senses and those five senses our vision. And that's a lot of AI is about vision today, hearing very similar to what we talked about with Alexa. And a lot of AI is applied to hearing. But the future of AI is really comes down to smell, taste and vibration, the technology that can manage all that and manage all that on a single working device. That's one of the things that brain chips doing right now is we're demonstrating that by going to look at some of our media and content, you can see that we're doing vibration detection, you can see that we're doing tactile analysis, you can see that we've got a smell or olfactory and taste we're, we're demonstrated wine tasting so you can taste the difference between two different types of wine and we just came out with one more words we're demonstrating beer tasting, but you know, we use beer is for fun, and it's pretty cool. We all can relate to that. But the reality is we're not really tasting the difference between two beers. we're analyzing compounds I should say and When you think of compounds, you think of glucose, sodium, pH, alcohol, and whatever the compounds are, those compounds could determine the well being of a city based off of the water, or the gas in the air, and so on. So what we're trying to really focus on is with Akita in our technology, what you can do is you can start applying our AI to be as close to the sensors as possible, and processes information. And so we have all that, and we're continuing to learn, as I mentioned before, do more demonstrations and test out technologies, which will allow us to start showing a lot more in the near future. So from that end, what I get really excited about is, over the past two years, we really haven't had the opportunity to be present and public and a lot of environments like trade shows, and where you can really weigh yourself, measure yourself from competitors and other new technologies that are being introduced. And we go to these shows, and we're the only ones that can do on chip learning. We're the only ones that are showing gesture, we're the only ones that are recognizing different facial features. And you know, then we're demonstrating vibration analysis or high speed detection of objects and images. And that's where it gets really cool. It's like we're doing all this now it's proven in silicon. And you know, now it's just kind of building out the technology, finding the right engagements with the right partners, and doing it in a very efficient and effective way.


Justin Grammens  31:29  

Yeah, absolutely. That's great. And you talk about sensing compounds. I mean, that is one of the ways that cities know if there's a COVID outbreak happening, right? They're actually testing wastewater for these compounds, which is, which is fascinating, right? So that's all I mean, it's yeah, it's, it's awesome. And I, you know, the other thing, I think is very cool is that you guys are actually doing on chip learning, right? That's the big thing. And Tiny ml was always or has been, send the data to the cloud retrain, send it back down again.


Rob Telson  31:57  

Yeah, it's the one thing that companies haven't been able to get their finger to the pulse on. First of all, finding machine learning guys, is really tough. There's a lot of AI guys out there. The second thing is building out the networks for what you want to apply the intelligence to, is even tougher. And so it's takes guys time to either find a public network, and then tweak it to what they want to do, or develop their own customized, that could take months to years to do to get it right. So the fact that we're saying, Alright, take a network, whether it's your own, or whether it's one that we're, you know, like mobile that v1. And now let's capture some smells, or let's capture some vibrations are Let's capture some facial recognition. And you don't have to do any retraining. You don't have to get any additional ml learning going on. Or to get the AI you can allow them to work on other programs and projects. That's where it gets exciting. And it's the companies that can leverage that type of technology, put it into their products, and really build on that for scalability and flexibility purposes.


Justin Grammens  33:08  

So any sort of like a turnkey solution, I guess is what people really they want to get get some sort of a rapid prototype done, they can utilize your stuff for that.


Rob Telson  33:16  

Yes, absolutely. And that's what I think something we get really excited about is the way that we're architected the way that we've produced the product with the software development flow that we have in place. It's all there.


Justin Grammens  33:30  

Yeah, awesome. One of the things I kind of ask is, if people are wanting to get into this field, or what like what what are some of the shows that you're attending? I guess what are you mentioned your podcasts? I'll be sure to put a put a link out to that. But what are what are some good sources of information as people are? are getting into this space?


Rob Telson  33:46  

Yeah, so anyone interested I mean, there's, there's two points to this. It's, hey, I'm interested in learning more about AI. And then there's, hey, I'm interested in learning more about brain ship as a company. And then from an AI standpoint, there's, there's a whole show circuit that can be very broad, and we're very specific in nature. And so for example, you and I were just, we spent some time here, and we referenced tiny ml. And Tiny ML is a show that takes place not only in the US, but also it takes place in different geographies. I know they have a big one in Asia as well. I think that's in the summertime. And our goal is to be there as well as long as we're allowed to be there. But what we're seeing is, you know, tiny ML is really focused on tiny ml tiny machine learning small technology embedded into other devices. And how do we build on that, as you mentioned, IoT from that, but there are computer vision, there's embedded vision there is the AI world there's a ton of different AI environments for those interested in just learned about AI. And then you mentioned that there's other meetup groups and so on like that and and we'd love to educate and be a part of that and learn as well. In regards to brain ship, I do send most people to our YouTube at branch Inc because that's really where Our content is, but our website at brain ship.com is also a really good place to go. And then if you want a specific conversation, contact us at sales at brain ship.com. And, and our team will take a look at the question and I can get involved, if you reference me to send more talk to Rob, we'd love to have a conversation with you and see what he had to say we come up with great ideas. And even if we can't support you, with your idea, we can at least point you in the right direction of who can support you with an idea that you might have, because this, this is a very Greenfield environment, it is really wide open. And if I'm gonna use the in the US, you know, we'll talk about baseball, for example, if we're talking baseball, we're in the first inning, I mean, of the whole AI revolution, per se. And that's what makes it exciting. There's, there's a lot of going on here. And it's, it might feel like it's moving fast to some of us, but it's when we look back five years from now we're gonna Wow, it started to move really fast.


Justin Grammens  35:59  

Yeah, for sure, for sure. Now, I've always been on sort of the cutting edge, sort of like the the next the next technology wave, sometimes in a good way, sometimes a little bit too early. But I do also realize that Yeah, I mean, as I've been in this IOT space, kind of in this AI ml space for a number of years here, just the rest of the industry now is sort of like really starting to adopt and come in as a big wave sort of behind me, or behind us, I guess, in some ways, and that you're right, you're seeing a lot of these applications now come to fruition. And some of it is sort of this, this idea that now we actually have the hardware to be able to do the, the inference at the edge. And now we can train on chip, and now we can run 50% of the power, a lot of these things just weren't able to be done. So it's a great sort of convergence, I think of sensors from from IoT, you know, machine learning from TensorFlow, you know, smarts that you guys are doing with regards to really low power consumption to really make these devices now be able to sort of really act like a human in some ways, right? actually be able to do intelligence, smart things and, and be able to, you know, raise alerts, you know, turn motors on and off, you know, send messages, you know, whatever it is, but you know, drive the car, you know, whatever it is, so, it's a fun time.


Rob Telson  37:06  

Absolutely, uh, one of the things I didn't bring up, we started using this term a few months ago, a lot more freely than we have in the past. And that is a Iot, right? That's applying the intelligence to the IoT devices. And so you're gonna start seeing that pickup in the world that we live in, you know, the, our whole objective is, is really make sensors really efficient, really smart. In very tiny ML type of environments.


Justin Grammens  37:34  

Absolutely. Well, cool. Rob. Yeah. You mentioned how people can reach out to you, I guess, you know, sales@friendship.com, right. And like I say, I'll put links to your guys's website and your LinkedIn page and stuff, that's probably another good place to connect with you as well. Is there any other topics or? Or things that maybe you would want to share that I missed today?


Rob Telson  37:53  

No, I think we're good. I just think that, you know, for those that have a real distinct interest in AI, and you know, I wanted to just remind everyone that you know, it is moving at a very fast pace, and there's a lot going on out there and hold on, hold on for for the ride because here we go. And, and for those that are new, and they want to learn more, like Justin mentioned, not only with with his podcasts or other podcasts that are out there, keep learning be a sponge, and it will all start to make sense over time.


Justin Grammens  38:24  

I love it. Yep, for sure. For sure. Yeah. The things that I tell people is learn teach lead. So learn something new, teach it to somebody else, and then you can become a leader within your organization. You know, whatever it is, but everyone should have an open mind. Well, great, Rob, I definitely appreciate the time today. Thanks so much for being on the show.


Rob Telson  38:40  

Hey, Justin, thank you very much for your time and look forward to future conversations.


AI Announcer  38:46  

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