The Position of AI in IoT


Ryan Chacon is joined by SymphonyAI CTO Vijay Raghavendra on this episode of the IoT For All Podcast to debate AI’s position within the IoT business. Vijay begins by introducing himself and the corporate earlier than speaking concerning the significance of AI in IoT. He then talks extra particularly about AI’s match into enterprise know-how and the way to begin adopting it. Vijay and Ryan then go extra high-level with conversations round challenges to adoption and the way value impacts the business’s progress earlier than ending the podcast with Vijay letting us know what to search for from SymphonyAI sooner or later.

About Vijay

Vijay Raghavendra is a know-how chief and entrepreneur with in depth expertise main know-how groups in firms starting from startups to Fortune 1. Most not too long ago, Vijay was the CTO at Acuity Manufacturers, an industrial know-how firm. At Acuity, he was accountable for all elements of software program know-how technique and supply, together with edge computing and IoT. Earlier than that, Vijay served as SVP of service provider know-how at Walmart, the place he and his groups have been accountable for all platforms, functions, and algorithms that drove the expertise for Walmart’s retailers and suppliers and a major a part of the client expertise throughout shops and on-line.

Curious about connecting with Vijay? Attain out on Linkedin!

About SymphonyAI

SymphonyAI is constructing the main enterprise AI firm for digital transformation throughout a very powerful and resilient progress industries, together with retail, shopper packaged items, monetary providers, manufacturing, media, and IT service administration. SymphonyAI companies have many main enterprises as purchasers in every of those industries. Since its founding in 2017, SymphonyAI has grown quickly, approaching 2,000 gifted leaders, information scientists, and different professionals. SymphonyAI is a SAIGroup firm backed by a $1 billion dedication from a profitable entrepreneur and philanthropist, Dr. Romesh Wadhwani.

Key Questions and Matters from this Episode:

(01:54) Introduction to Vijay and SymphonyAI

(06:23) Position of AI in IoT

(08:57) How AI suits into enterprise know-how

(14:00) Tips on how to begin adopting AI

(18:27) Challenges to adoption

(22:38) How does value have an effect on adoption

(26:42) What to look out for from SymphonyAI?


Transcript:

– [Voice Over] You might be listening to the IoT For All Media Community.

– [Ryan] Hey, everybody, and welcome to a different episode of the, IoT For Al Podcast, the primary publication and useful resource for the Web of Issues. I’m your host, Ryan Chacon. I do ask in case you are watching this on YouTube to please give this video a like, and subscribe to our channel, in the event you haven’t already accomplished so. And in the event you’re listening to this on a podcast listing, please be at liberty to subscribe, to get the most recent episode as quickly as they’re out. All proper, on at present’s episode, we now have a Vijay Raghavendra, the Chief Know-how Officer at SymphonyAI. They’re an organization that’s constructing a number one EnterpriseAI firm for digital transformation throughout a very powerful and resilient progress industries. Together with retail, shopper package deal items, and plenty of others. Actually good dialog right here. We discuss so much about sort of AI, the position of AI in IoT. We discuss concerning the applied sciences that they’ve constructed, the applied sciences that they work together with regularly, how individuals can get began with adopting AI into their answer. Why vertical particular experience is absolutely necessary, relating to that kind of integration and bringing AI into an answer, is especially an IoT answer. And we additionally discuss so much concerning the challenges that they see from their aspect of issues, because it pertains to bringing options to life. So, all in all nice dialog, a whole lot of worth right here. I believe you’ll take pleasure in it. However, earlier than we get into it Works With, by Silicon Labs has emerged because the go-to developer convention for constructing the talents wanted to create impactful linked units. On September thirteenth by way of the fifteenth, Silicon Labs is bringing collectively influential, know-how manufacturers, ecosystem companions, and builders for 3 days of technical coaching and workshops, keynotes and skilled panels. Works With is dwell on-line and free. Register at workswith.silabs.com workswith.silabs.com And with out additional ado, please take pleasure in this episode of the, IoT For All Podcast. Welcome Vijay to the, IoT For All Podcast. Thanks for being right here this week.

– [Vijay] Thanks so much, Ryan. Nice to be right here.

– [Ryan] Completely. Very enthusiastic about this dialog. I needed to kick it off by having you give a fast introduction about your self, to our viewers, in the event you wouldn’t thoughts.

– [Vijay] Nice. I’m Vijay Raghavendra, I’m the CTO at SymphonyAI. I got here to SymphonyAI about seven months in the past because the CTO and previous to Symphony, I used to be the CTO at an industrial know-how firm referred to as Acuity Manufacturers. Acuity, along with being one of many largest industrial tech participant with the lighting and lighting controls additionally has a linked units play for constructing administration, for location administration methods as effectively. And I spent a while working with Acuity to construct these capabilities out. And previous to Acuity, I spent about seven years at Walmart, a number one numerous elements of engineering and product at Walmart. And I got here to Walmart as by way of an acquisition of an organization the place I used to be a co-founder and CTO that I offered my co-founders and I offered to Walmart.

– [Ryan] Unbelievable. Yeah. Very in depth background expertise. Appears like a fairly enjoyable journey to get to the place you at the moment are.

– [Vijay] It’s been, yeah.

– [Ryan] So let, let me ask you this. So let’s discuss SymphonyAI actual fast. Inform our viewers a bit bit concerning the firm, what the main focus is, the position you all play in IoT, that sort of factor?

– [Vijay] Yeah, so SymphonyAI is an EnterpriseAI firm and our focus is to use AI and machine studying to unravel issues in numerous verticals that we play in. From retail to monetary crime, to industrial to media, IT providers and federal. So, the main focus for us is to allow our clients in every of those verticals to essentially remodel what their companies and clear up actual issues by way of the applying of AI and machine studying. All the work that we do is grounded in our AI platform that we name Eureka. We not solely assist the entire capabilities that you’d count on from any of the AI platforms, however we even have some distinctive capabilities round know-how that we’ve constructed particular algorithms, reminiscent of topological information evaluation. And particularly for every of those verticals. One in all our vital methods wherein we add worth, or we carry worth to our clients is thru the deep vertical experience and our pre-trained fashions and capabilities that we now have throughout these completely different verticals. And particularly coming to the applying of IoT, relying upon the vertical take industrial, for example, we work with some very massive manufacturing corporations and browse information from various completely different sensors. As you may think, in a whole lot of manufacturing facility to then use the info, to determine, to foretell outcomes reminiscent of when a compressor could also be going dangerous. How do you then do preventive upkeep on these gear to do it, to stop a a lot greater downside from occurring downstream? And with that, we usher in the entire capabilities, not simply with all kinds of various sensors and units that we learn information from, however edge computing, digital twins, and deep studying fashions within the cloud.

– [Ryan] Completely. Yeah, incredible overview. Thanks a lot for sort of giving us a bit little bit of context there. I do wanna ask you although, simply from a excessive degree standpoint, after we discuss AI and IoT, they oftentimes at the moment are going extra hand-in-hand than ever earlier than. Inform me concerning the position and the way you view it of an AI firm within the IoT house?

– [Vijay] Yeah, I believe that’s an amazing query. And I believe for the longest time, I actually consider that individuals have at all times believed within the worth of IoT and the potential of IoT. And you’ll see that within the shopper house. And I believe that choice of IoT within the shopper house has, clearly, it’s grow to be mainstream now, however within the enterprise house, we’ve at all times been on the cusp of realizing the worth. And up till not too long ago, I might argue that we hadn’t absolutely realized the worth, however with the entire adjustments which are occurring and have occurred, with the price of {hardware} coming down with the density of the compute in edge units. Getting to a degree the place it turns into actually attention-grabbing for us to do a whole lot of processing on the edge with the flexibility now to embed a TPU, for instance, in an edge gadget. So we are able to run tiny ML fashions on the edge, mix it with working a deep studying fashions or extra refined fashions within the cloud after which pushing the outcomes again. I actually assume we now have the entire underlying capabilities we have to actually carry the ability of AI mixed with IoT to unravel actually attention-grabbing issues, such because the one I discussed just a bit bit earlier. So, I actually consider that AI turns into the conduit for unlocking the worth from IoT, as a result of with out the flexibility for us to do one thing attention-grabbing and helpful with the entire information that you simply’re getting from these units, it turns into clean. And with the entire adjustments within the {hardware} with cloud, with edge, with the development and AI, I actually assume it’s an effective way for us to carry the ability of IoT and clear up actual issues.

– [Ryan] One hundred percent agree. So inform me a bit bit about after we discuss AI, you understand, there’s numerous firms on the market who do AI, say they do AI, there’s numerous options on the market. And oftentimes for the folks that need to carry AI into their answer, they don’t at all times know precisely what the distinction is between firms that play within the house that the choices, what they need to be on the lookout for. So inform me, it’s principally, it’s two questions I’ve. One is to inform me how, what you all do sort of differentiates from different gamers available in the market? And the opposite is how does this sort of know-how actually slot in to the way forward for enterprise know-how as a complete?

– [Vijay] Yeah, so, I believe you hit on a very vital level with the applying of AI and enterprises. I believe there are a variety of research that present that 80 plus p.c of all AI initiatives or AI initiatives in enterprises which are making an attempt to undertake AI fail. And so they fail for various completely different causes. Beginning with actually a lack of expertise of those particular kind of issues there’s making an attempt to unravel for, for which AI and ML are a very good match, not having the precise information or information tradition, and never having the precise possibly mindset or adjustments within the processes that they should do to essentially reap the benefits of this know-how. So, I can preserve going. However the reality is that a whole lot of enterprises battle at present with the applying of this actually attention-grabbing half know-how to unravel issues. So, how will we, or the place will we play and the way will we assist our clients actually get previous this vital problem? As I discussed in my intro, one of many vital locations the place we’ve invested as we’ve constructed out our merchandise, and product providing within the completely different verticals is the deep vertical experience that we’ve constructed over time. So, we’re not a generic AI or ML platform with a number of fashions and we are able to throw it over the fence to our clients and say, “Nice, go have at it.” What we’re centered on due to our experience is with each single vertical, we’re tackling the precise set of issues the place AI and ML are an excellent match that. And the place we are able to go assist clear up these issues in a singular and differentiated method. So take one thing like determining which assortment you need to be carrying in a retail retailer and the way a lot of every assortment you need to be carrying and the place? That may be a very particular downside that each single retailer has to unravel, large, massive, or small. And what we’ve accomplished with our deep experience and experiences, we’ve constructed over time these pre-trained fashions that clear up this downside for retail and retailers and CPGs. And with the partnership that we now have with our clients, we then begin from our pre-train fashions that aren’t simply the fashions and the options, but additionally embed the data of what a service provider at a big retailer does. How do they give thought to what the precise assortment is? What the combo is? We embed that intelligence to then work with our clients, to then optimize these fashions and options to unravel the issues. And we do the identical factor with monetary crime and anti-money laundering, for instance, and so forth. And as in, so doing, we carry some very distinctive IP. I discussed the topological information evaluation. Which is a very distinctive and attention-grabbing method to consider information and discover information in an unsupervised studying method. Which takes very massive dimensional information and permits us to assume, have a look at this information and discover relationships that won’t in any other case be apparent or that standard clustering algorithms might not offer you. So, all of those collectively permits us to essentially differentiate ourselves from others and concentrate on fixing the issues for our clients.

– [Ryan] Yeah, it makes whole sense. One factor you talked about in there that I really needed to observe up and ask you about is you have been speaking about sort of that vertical, particular experience of the area experience that’s tremendous beneficial and sort of the differentiator for you. I do know after we discuss to, let’s say platform firms within the IoT house, that’s a giant factor for them to assist separate themselves out is versus simply having this common platform that may do all of it, or no less than that’s how they promote it. They discovered worth in buying clients with extra of a focused focus primarily based on area expertise that they’ve for fixing a specific downside or specific use circumstances inside an business. So let me ask you when a listener to that is seeking to sort of study extra about getting AI parts concerned of their answer. They’re seeking to undertake AI know-how. How ought to they sort of go about getting began down that course of and why is it so necessary to discover a firm with the vertical particular experience that connects to them to assist simply improve the probability of success?

– – [Vijay] Yeah. Glorious query, once more. My recommendation to firms that need to incorporate AI to unravel issues can be for them to be very clear and spend the time to essentially perceive that the outcomes they’re making an attempt to have an effect on and the precise kind of issues they’re making an attempt to unravel and actually get educated both by way of partnerships or working with firms, reminiscent of ours to basically perceive the kinds of issues for which AI is an efficient match, as a result of it isn’t a panacea for each downside that each firm’s gonna have. So, it’s actually necessary for them to grasp that. The second is, and I can’t emphasize this sufficient, AI or any of those machine studying algorithms simply don’t work, or it means nothing in the event you don’t have a tradition of excellent information and a tradition of fascinated with information as the important thing enabler for the applying of AI. If it’s actually rubbish in and rubbish out. So in the event you don’t have good clear information, and in case you are probably not listening to that as a core basic a part of the way you construct your merchandise and your methods, frankly, nothing else is gonna work.

– [Ryan] Proper. So, I might say I might actually encourage firms to essentially basically deeply perceive each the issue, but additionally then concentrate on the info and guaranteeing that they’re not solely have the precise information, however they’ve a tradition of guaranteeing good clear information as a result of that then turns into an enormous unlock. After which, clearly, specializing in not simply broad enabling platforms, which more and more have gotten a commodity, however working with and partnering with firms that may actually usher in that very particular area experience turns into a key strategy to guaranteeing that you simply’re fixing issues that matter as a result of, finally, the constructing blocks for the way you do carry information from numerous sources, clear the info and remodel the info and the way you construct the fashions themselves, are more and more a commodities. The hot button is gonna be, do you actually perceive the verticals and the domains? So you might be extracting the precise options. You perceive when information or the fashions are drifting. All of these key issues are key issues, I believe are what’s going to make it profitable.

– [Ryan] Completely. Yeah, completely. Let me ask you this slight little pivot right here to a bit completely different space of focus, however while you sort of have a look at the evolution of the know-how, not simply in IoT, but additionally in AI and sort of how they work collectively, what do you assume have been among the greatest challenges to getting the know-how the place it must be? To extend adoption, to sort of, you understand, these expectations or these numbers that we’ve been promised for therefore a few years concerning the progress and adoption of those applied sciences, what do you assume have been the largest possibly roadblocks or pace bumps which have sort of received in the best way to that sort of main as much as the place we at the moment are?

– [Vijay] Yep, I might say, in the event you assume again to the final decade or so, as I discussed a short time again, I believe the promise whether or not it’s with IoT and even broadly with enterprises has at all times been there, however the adoption, and extra importantly, the success from the adoption of this know-how hasn’t fairly stored up with the expectations. And the explanations are, I believe, once more, a basic, possibly lack of expertise of how this know-how works. And as I discussed, the concentrate on information, and I do know I’m harping on this, like fairly a bit however I’m doing it as a result of it’s so necessary. I believe firms, basically, have underestimated the significance of getting an excellent information, however extra importantly, having a tradition of excellent information that’s inherent within the firm. And while you don’t have that, it turns into very tough to comprehend the worth actually at scale. So, I might say that’s possibly one of many greatest basic challenges that I’ve seen. The second is I believe, as we’ve developed, particularly within the final 5 to seven years, the capabilities that we now have from whether or not it’s from cloud frameworks to different open supply frameworks, to various Python libraries, to transformer fashions that at the moment are obtainable, or has basically modified the sport. To the purpose you don’t want a PhD in math and stats and pc science to begin constructing and realizing worth. So, I believe the know-how has additionally developed actually quickly within the final a number of years, that makes it way more attention-grabbing, way more tractable downside to unravel. And let’s face it the final and the largest downside is at all times gonna be for us to seek out good expertise at scale and information science and ML Expertise might be one of many hardest expertise for us to seek out. And that’s the place the flexibility for us to have the ability to leverage a whole lot of these open supply fashions for a citizen information scientist, for instance, to have the ability to use a whole lot of these fashions and options to unravel enterprise issues while not having a staff of information scientists. I believe all of those collectively will assist unlock the worth quicker.

– [Ryan] Yeah. Completely agree. I imply, there’s new applied sciences day by day, proper? You understand, BLE Wideband, Extremely-Wideband. Edge computing’s changing into extra highly effective, the cloud. All very large enablers of what we’re sort of speaking about. How do you assume the associated fee factor elements into the sort of adoption? I imply, clearly value appear to be taking place throughout the board for IoT elements tech. Whether or not connectivity, the {hardware}, or the software program, you identify it. How do you assume that mixed with the evolution and progress of the know-how side is taking part in a job and influencing the long run progress of what we’re making an attempt to construct?

– [Vijay] Yeah. I believe value, particularly with IoT within the enterprise is gonna be a giant issue. Apparently, among the work that I did at my earlier firm, and that was simply having a dialog with one of many firms that was utilizing Extremely-Wideband to do look monitoring, for instance. The size for, in the event you take retail.

– [Vijay] The size at which no less than a big retailer who has a number of areas, the size at which they function, it turns into the price of the {hardware} turns into a really, very materials value, particularly for firms which are working on very small margins to start with. And I believe that’s the place it must be a mixture of value of the {hardware} has to maintain coming down and we now have to way more environment friendly concerning the density of the {hardware} or the beacons. And so forth that we want in very massive areas. The, as you talked about, edge computing and the density of the {hardware}, the ability of the {hardware} on the sting is changing into increasingly amenable for us to do a whole lot of processing on the edge, which then helps us with the egress and ingress cross to the cloud. However, finally, I believe we’re at some extent the place all of those are trending in the precise method. The fee is coming down. The know-how with Extremely-Wideband, BLE, VLC with the NextGen of what’s coming with 5G for the enterprise are all, I believe driving efficiencies and have gotten create enablers for functions that we are able to clear up. And finally, if the functions that we are able to construct on all of those applied sciences, doesn’t ship sufficient worth to justify the worth then clearly it’s gonna fail because it ought to. However my agency perception is we’re at some extent the place we now have all of those constructing blocks. The fee despite among the challenges, for instance, for a big retailer is at some extent the place it is vitally a lot within the ballpark of being very manageable for a retailer. And the worth that they will get from it, I believe, is justifiable and can solely get higher any longer. After which you may apply the identical analogy to varied verticals as effectively.

– [Ryan] Completely agree. Completely agree. Yeah. It’s all superb factors. I imply, the expansion and the brand new applied sciences popping out is a large half. The fee taking place is a giant enabler. The simply developments throughout the board and all the pieces occurring. The extra use circumstances, the extra profitable deployments, the extra area experience that we talked about earlier. Like simply the extra obtainable that data and data is, and applied sciences is for individuals, the extra choices they must construct the precise answer for his or her specific use case. So, as we wrap up right here, I needed to ask sort of wanting ahead from the place we at the moment are popping out of SymphonyAI, and sort of what you all have occurring. What’s the massive subsequent step? Like what ought to we be on lookout for listening to popping out of your man aspect of issues?

– [Vijay] Yeah, so one of many locations that we’re centered on is, as you consider the vertical particular experience and fixing issues in numerous verticals, particularly with the AI and along with the usage of IoT and different units, the best way we’re fascinated with the issues we’re fixing and what’s coming subsequent is absolutely the notion of an AI enabled digital employee who’s actually working in live performance in-hand-in hand with the people within the loop, if you’ll. And actually enabling the people who’re working, whether or not it’s a enterprise analyst, a enterprise skilled, somebody on meeting line, or a retailer supervisor to do their jobs a lot, way more effectively than they will at present with what are possibly fundamental analytics and even some fundamental AI enabled functions. In order that’s the place we consider we’re going to see the actual mainstream, not simply adoption, however a step operate improve within the worth that this know-how can actually drive in with the applying. Which brings collectively IoT and the entire ecosystem round it with edge and the cloud with AI and ML, with the vertical experience. Actually bringing all of these collectively in a method that basically augments and helps the people in a basic method. Which makes it in a seamless basic method, I believe is the unlock.

– [Ryan] Couldn’t agree extra. Yeah, it’s very thrilling stuff. What you all have occurring over on the firm may be very fascinating from the analysis that I’ve accomplished. I hope our viewers takes a while to kinda look into what you’ve occurring. For our viewers on the market who does have questions, might wish to observe up, study a bit extra, what’s the easiest way that they will try this?

– [Vijay] So, our web site symphonyai.com is a superb useful resource. There are hyperlinks there. There’s a whole lot of actually nice content material for the issues we’re fixing in every of the verticals. And there are hyperlinks there for anybody who desires to ping us with any query as effectively. So that will be an amazing place for any of the listeners to ping us.

– [Ryan] Unbelievable. Nicely, thanks a lot on your time. Actually admire it. We don’t have the chance to speak so much about AI recently. So I actually admire you taking the time to try this. I believe our viewers is getting a ton of worth out of this dialog. So thanks once more, and we hopefully like to have you ever again, different members of your staff again to proceed this dialogue and discuss extra about how AI and IoT actually work collectively to take issues ahead.

– [Vijay] Nice. I admire the chance, Ryan. It was nice to speak to you. Thanks.

– [Ryan] Thanks. All proper, everybody. Thanks once more for watching that episode of, IoT For All Podcast. In the event you loved the episode, please click on the thumbs up button. Subscribe to our channel and you should definitely hit the bell notifications so that you get the most recent episodes as quickly because it grow to be obtainable. Apart from that, thanks once more for watching and we’ll see you subsequent time.



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