Skip to main content


Everything AI at embedded world 2021

Dr. Sally Eaves IoT Chat

A conversation with Dr. Sally Eaves @sallyeaves

With embedded world 2021 going all-digital, attending the world’s premier IoT event is easier than ever. And it’s one of the year’s best opportunities to get up to speed on the latest in AI and advanced programming techniques. You won’t want to miss this chance to discover the trends that will define the year.

In this podcast, multitalented IoT and AI expert Dr. Sally Eaves joins Editor-in-Chief Kenton Williston to preview the show, pick out must-see conference sessions, and highlight key trends attendees should look for at the event. We explain:

  • Why AI will play a critical role at embedded world 2021
  • How new tools are changing the way IoT applications are created
  • How developers and engineers can get the most out of the event

Related Content

To learn more about embedded technologies, read Q&A: Everything at embedded world 2021.

Apple Podcasts  Spotify  Google Podcasts  


Kenton Williston: Welcome to the IoT Chat podcast, where we talk about the trends that matter to developers, engineers, and system architects. Today we’ll be talking about the upcoming embedded world 2021 show, which of course has now gone all virtual. Kind of sad and disappointed myself not to be going this year, because I love taking a flight out to Germany every year around this time. But the great thing about it is now it’s going to be easier than ever for folks to attend. And so, on that point, I’ve invited our guest, Dr. Sally Eaves, to join me to talk a little bit about what’s going to be coming up in the show, where it fits in the broader context for the industry, and how attendees can get the most out of their time. So, Sally, welcome so much to the show.

Sally Eaves: Oh, thank you so much. Pleasure to be here. Really looking forward to our conversation today.

Kenton Williston: Excellent. And can you tell our listeners a little bit about yourself?

Sally Eaves: Yeah, absolutely. So, I’m CEO of Aspirational Futures, which basically looks at enhancing inclusion in technology, and also around education as well. I’m a CTO by background, and I’m now a senior policy advisor for the Global Foundation of Cyber Studies and Research. I do a lot around emergent technology advisory, and I’m also a professor around that area as well. So, really active around cloud computing, cybersecurity, IoT, IIoT, AI, blockchain, 5G, etc., but also the cultural aspects of that, and the people factors around sustainability and social impact too.

Kenton Williston: All things that people are very much focused on these days, I think. Very relevant to what is coming this year to embedded world. So, on that point, I think two of the big trends that I am looking at for this year’s show really center around, of course, the longer-standing trend of Embedded transforming into Internet of Things, or IoT, technology. And I think that what really distinguishes those two is a combination of the connectivity. Of course, you can’t have an Internet of Things without having an internet.

And then I think also the intelligence, and I think what’s becoming particularly prominent, and building on that IoT migration trend, is a greater and greater emphasis on AI. It seems to be part of just about everything that is happening this year. So, I’m wondering, from your point of view, Sally, what you see as the megatrends for 2021 as they relate to the Internet of Things and AI, and just generally what’s happening in this commercial-technology space.

Sally Eaves: Yeah, absolutely. I think it’s really exciting times. There’s a great deal of convergence. And you mentioned two of the key factors there, with IoT and industrial IoT alongside AI and machine learning. Absolutely. But I’d also add 5G into the mix there as well, as that becomes more and more mainstream. A lot of the advantages that brings—particularly, for example, building low-latency applications—I think that’s going to really have an influence as we move to the latter side of this year as well. So I’m excited to see what happens there.

I think, just generally, the latest predictions are something like 41 billion connected devices by 2025, and the whole market around embedded software is set to increase to something like 130 billion by two years later—so, 2027. So we’ve got a huge demand for this area. So we need to look at not just the technology, but the skill sets alongside that. And maybe some of the challenge trends I see as well. So I think one would be security and, in particular, safeguarding critical data within industrial and embedded IoT, and also thinking more, maybe, on the network side of things around timeliness. I think that’s so, so vital for industrial automation, AR, VR, and also robotics use cases as well.

So, things like time-sensitive networking, which I know is one of the sessions at the upcoming event as well. I think it’s one to look out for as well. So, really exciting times, and AI specifically—things to make it easier for developers so they can really maximize their time. So I think there’s some interesting things we can explore there in depth as well.

Kenton Williston: Yeah, absolutely. I feel like you’ve almost read my mind there on several points. So, one thing for sure I should mention up front here is that listeners can visit the blog page for this podcast, and they will find there links to a whole bunch of different demos and Q&A sessions that folks can attend to learn more about all of the technologies we’ll be discussing today. And that’s very much inclusive of one of the first things you mentioned—that a lot of things are converging together. I had already mentioned there’s AI plus IoT; you talked about 5G, security, and I absolutely agree.

This, of course, is nothing new, to say that applications keep becoming more and more complicated. It’s almost trite to say that. But I think there’s a truth to that that is different from how things used to be complicated in the past—that the kinds of complexity people are dealing with is quite a bit different than in the past. And bringing all of these different technologies together, I think, really has a meaningful impact on what kinds of applications you can even consider.

And one of the demos that I’m really looking forward to seeing on this point is, there’s a really cool, what IEI—one of Intel’s partners—has called their AIoT kit, which as its name suggests combines AI plus IoT to get AIoT. And of course it brings together the AI and IoT sides of things, but it also brings together with that the 5G technology that they were mentioning, which I do agree is going to be a very important part of where the application space is headed this year.

To another point that you made about the challenges and the complexity—I’m wondering, from your point of view, what developers and engineers should be on the lookout for that will help them actually put together these increasingly complex, multifaceted sorts of applications that folks are trying to build in 2021.

Sally Eaves: Yeah, absolutely. I love the sound of that demo, by the way. I’ll definitely be looking at that. That looks fantastic. I think, for me, you really touched on it around convergence. So, for me, it’s—we’ve got this increased sophistication that’s offered by convergence, but at the same time it’s this juxtaposition around complexity. So it’s about making it simpler but not simple, for another way of putting it. So, I think one thing definitely to look out for—which I think is going to really help, and I’ve just been part of an incubation program along this very basis—are the 5G elements. So I think that’s really exciting in terms of speed and the new possibilities that’s going to create.

So, 5G and Edge computing together—connecting more devices, more efficient processing of data. And agility—I think the key word probably for 2021 as your workloads are fluctuating. Distributed Edge computing is going to give that flexibility to scale on demand, to deploy your applications to any Edge location. So that’s really exciting, and conserving memory and power, and, because apps are being processed at the Edge, you’re reducing bandwidth as well. So, looking out around opportunities for that, I’m seeing some very interesting collaborations in that space.

So, definitely would shout out for that for developers to have a look at. But on top of that there’s a range of tools supporting alternative software-development paradigms, and they’re becoming more available. Using graphical programming methods or domain-specific languages. So that’s an exciting area. It’s very much model-based software development, but also in particular—and we’ve touched on it a little bit already—but opportunities for almost, like, all-in-one Edge development offerings. So you’re integrating software and hardware with pre-trained AI models and comprehensive tools. So it’s all around that help, that seamless help, for developers to take care of that baseline to a certain extent, to give you more time to do the actual innovation and agile development.

So that’s really exciting. Anything that’s going to help you with—or active prototyping, experimentation, get up and go and running quickly—those are the things to look out for. And I’ve seen a lot of things in the agenda coming up that really touch on that in depth. So I’m really excited to see where that goes.

Kenton Williston: Yeah, I’m seeing much the same. And I mentioned already that there’s this IEI kit that they’ll be demoing that brings together a number of things. And another one that really struck me from this angle is there is one from a company called Vecow that brings together some AI pre-trained models, like you were describing, as well as the ROS—that is the Robot Operating System platform—and I think this is a really good example of the sort of thing that you were laying out as the path forward.

You need to have pretty robust platforms that have got a lot of the basics done for you. And more than that, I think, shared platforms, whether they be open source or at least open APIs. I mean, I’m thinking, for example, like the way the big cloud players like Microsoft and AWS have these APIs you can leverage. I think using the standard methodologies and approaches to design your IoT devices is going to be increasingly important, just because you’re trying to combine so many complicated technologies in one single device, in one single software package.

So, again, the one that was really interesting in this regard was this demo that Vecow will be showing that’s kind of like a one-stop shop for everything you need to create an intelligent robot. So—think an autonomous robot that might be running around a warehouse floor, or something like that, would be a good example of where this would be really useful.

Sally Eaves: Absolutely. No, I spotted that as well. I think that looks excellent and really reducing time consumption, and particularly around challenges of integration of various software stacks as well. I think it’s so strong on that, but also things, maybe, around stable and reliable version management as well. I think that’s an excellent example.

Kenton Williston: Yeah, absolutely. Absolutely. So, and in fact, some of the links we’ll be providing on our site will be to exactly those sorts of things. I briefly touched on the way that folks are increasingly doing development in a fashion that resembles what you would see in the IT world. So, doing things in containers, developing in the cloud, and pushing to the Edge, make it a lot easier to—to your point—maintain versioning, make it a lot easier to maintain visibility across distributed systems, make it a lot easier to—as I was saying earlier—take a bunch of standardized things and package them together in a platform that everybody else is already using, so you don’t have to figure it all out for yourself.

Sally Eaves: Absolutely. Absolutely. I couldn’t agree more.

Kenton Williston: And there’s even a really interesting session that’s talking about some of what Intel’s doing. It’s got a whole new web presence that it’s launched within the last year called the Edge Software Hub, which I think is a pretty interesting effort to bring together all of these commonplace technologies. And it’s not just for the things like the AI or the robot operating systems, but even things like the connectivity—pre-packaged modules for 5G connectivity—that allow you to easily configure the open network Edge services software—or OpenNESS platform—on that Edge device.

So, I think all these kinds of approaches, where you’re almost more like building things out of Legos, as it were—again, this is the sort of thing that I think everybody has been talking about for a long, long time. And I think there’s nothing new conceptually about this, but I think, just given all the many different things, and—to your point about the agility and how quickly folks are wanting to, not only deploy IoT designs but be able to update them—I think it’s just more important than ever.

Sally Eaves: Yeah, I think the example you gave just now about the Edge Software Hub is such a strong one, because you’re right, you’ve got that pillar, that pre-optimized pillar of deployment-ready software packages, which is fantastic. But, equally, you’ve got the ability to customize as well, so it’s that best-of-both-worlds approach. So, it’s so strong on the actualization side of things, and what you mentioned there about continuous integration, continuous deployment—I come from a telco background; I’ve just been doing some work specifically on this area, and I think it’s so, so strong for that granular changeability, which I think is fantastic to move into the IoT space. So, absolutely. I think that’s absolutely the way we need to be going.

Kenton Williston: Yeah. And I think one point that I can’t overemphasize is, I think when I’m thinking back to the past years and—I have to say, I have so, so loved going to this show. Nuremberg is just such a beautiful city. I really love the old town. The last time I went, in fact, we stayed in the old part of the city, right on the river. We were on the bottom floor of the building that was who knows how many hundreds of years old, and there are all these ducks swimming about, and I could just about reach out and touch them. And, oh, so lovely. I really miss that.

Sally Eaves: Oh, me too. Me too. I’m used to remote working, but I’m used to mobile remote working, if you see what it means? So that’s—

Kenton Williston: Exactly. Yes.

Sally Eaves: But, yeah, absolutely. I really miss the socialization aspect of events and things, but I must admit I’m really impressed by how the agenda for this has been curated. There’s a real strong attention to detail there, and opportunities to build that network connection and match people together. So I really like what’s been done in terms of curating the event.

Kenton Williston: Yep, absolutely. Absolutely. And the thought that got me on our little rabbit trail here was thinking back to previous years. A lot of these trends, like I’ve been saying, are kind of longer term, but I think something that has changed here is just how pervasive the AI element is in just about every single space that we’re looking at. And there’s some really fun and interesting examples. I’m finding AI cropping up in places that I wouldn’t even expect, despite the fact that I’m constantly in this space thinking about IoT applications. It still surprises and delights me to find out where and how it’s being deployed.

So, I saw a couple of examples from ADLINK, where they’re going to be demonstrating how they use AI to inspect contact lenses. And as a guy who’s just going out to get their latest prescription, I really appreciate that. Someone is making sure those are very well made. And even things like palletization of items for shipping, and automating that process, and automating the tracking of things within a pallet. It’s just—no matter what kind of application, big or small, it’s like AI has a way to help out it seems like just about everywhere.

Sally Eaves: Absolutely. I couldn’t agree more. And supply chain. I think one of the things that’s come to the fore so much over the pandemic—and in some cases the fragility around that—and embedding a transparent audit trail. I’ve seen some really interesting things with AI and blockchain coming together. And, again, we were talking about actualization earlier. I think in blockchain, in particular, it’s something that has been associated with particular use case studies more than others, but it’s shown the real art of the possible now, and really tangible, actionable case studies. So that marriage, for want of a better word, between AI and blockchain I think is one to watch as well. It’s been really heightened. I think trust has been built over this process. So pharmaceuticals, for example, would be a classic example of that.

Kenton Williston: Yes, absolutely. Absolutely. Another thing, too, that I think is worth adding to the mix here—speaking of the trust—there’s also the safety element of things. So, as exciting as it is to see this amazing intelligence being applied in all these amazing creative ways, there’s also a lot of, I think, caution that we should exercise as technical professionals about how we’re deploying these technologies.

And, I think, particularly as we’re increasingly automating systems and making them hands off. So here in the States, for example, there was just a story where someone had accessed a water treatment plant and increased the amount of lye that was going into the water, which normally would just handle the acidity and get it to a reasonable pH balance, and they had increased it to—it was either 100- or 1,000-fold the desired amount. And it was just a coincidence that someone happened to be in the plant looking at a screen while someone was in there maliciously mucking about, that they caught that. And that sort of thing is scary, right? And I think reasonably so.

So, I think for all of us to be thinking about putting the safeguards around this amazing technology is also a very important consideration going forward. And one thing that comes to mind for me there as an example is Intel and its latest hardware platforms: the—what’s been known as Elkhart Lake, now as the—Atom 6000 Series incorporates some functional safety technology to help in the physical world keep things safe. And I think that’s very, very important. And there’s a really great demo from NEXCOM showing exactly how that works, and how you can deploy that in all kinds of different applications to keep things from causing harm.

Sally Eaves: Absolutely. No, I think that’s one of the absolute key issues of the entire year. And I think in certain sectors around manufacturing, operational technology, health, education—there’s been such an increase, I think it’s around 300% increase around identity attacks over the past year, as one example. But I think we’ve also seen where, for example, there’s been continual investment in infrastructure, but maybe less so around patching and around refreshes. So that’s created an area of security vulnerability as well. So, so much lookout there, so that sounds a really, really excellent investment and advance. So it’s great to hear that.

Kenton Williston: Another thing that comes to mind for me is, I know that ethical AI is something you’re passionate about. And I think, just on a personal level, it’s something I care about as well. So, I’m based in Oakland, California myself, which is known as a hotspot for, let’s say, socially progressive sorts of movements. And there has been just recently here, in the past week or so, some movement among the activists in this community to stop the Oakland Police Department from using automated license plate recognition—which I’ll leave whether that’s a good idea or not for the listener to decide—but I appreciate very much the ethical challenges there.

I mean certainly these kinds of technologies have been abused already, and there’s potential for abuse for sure. Facial recognition has also been, I think, a really, really hot and hotly debated topic. And I know we’ve been talking about software packages that can help with AI. And Intel, I think, has done a really fantastic job with its OpenVINO platform, pre-packaging a lot of commonplace AI workloads together. And they took the step of actually removing any of the facial recognition elements from those packages, just to really say, “Hey, let’s take a pause here and think about how these technologies can be best deployed. And see what we can do to address issues of things like racial profiling, and the differences in how well these things perform depending on your gender and ethnicity, and so forth.” So I’d love to hear some of your thoughts on these issues.

Sally Eaves: Absolutely. And one thing I’d also applaud there is Intel have done some really good work about building an ethical AI toolkit, and they’ve got some really great examples there, and it’s backed up by research with Stanford and other places as well. So, really, really impressed by that, because I think leadership in this area is so, so important. And I think one of the things that’s also impressed me over recent months is a bit of a change in the narrative around this.

So, in the past when we talked about AI there had been quite a lot of headlines that were quite scary. It would focus on—if a research report came out—it would focus more around words like “destruction” and “elimination” around certain types of jobs. But what we’ve been able to see over the pandemic experience is some fantastic examples of collaboration. So, one of those that springs to mind for me would be the HPC Consortium—so, the High Performance Computing Consortium—of which Intel is a member.

And it’s a great example of leading tech companies coming together—partnering up with research and academia and governments across the world as well—and really coming together, and that ethos of tech-for-good collaboration—basically to bring computing capacity, to bring computing power together to look at how we can better fight COVID-19. So, I think that’s a great example of turning the narrative on AI as something for good. And to support that further, to build that momentum of greater trust around AI—I think for me it’s ethical development and aspects like the explainability of AI which I think is really, really important. I’ve seen a lot of work—and I contribute to some of this myself with some of my research—about value frameworks to build common understanding, common language, common commitments about the development of AI, but I also think this comes down to education.

People have to be empowered to be able to ask the right types of questions, and we need to get better diversity of teams into who’s building AI as well. And that goes beyond aspects like gender, to all sorts of different characteristics—but diversity of experience, it matters so, so much. And every piece of research going and, you know, our practical experience as well—the teams that are diverse are happier, they’re more creative, they’re more satisfied, and you get so much more innovation and you reduce the risk of implicit bias as well. So that has to be the way to go forward.

There’s been a lot of research by groups such as Endelman—they benchmark trust, for example, over at least 17 years now—and even before the pandemic it was a low ebb across all sectors, even around charity, for example, as well. So there’s always been a lot of work to do here, but I believe that the positive things we’ve seen coming out over the last year—let’s harness that. Let’s build a contagion of change around these types of subjects. I’m really, really super passionate about social impact and around inclusion. I think we can really build on what we’ve seen here, and some of the collaborations and the movement forward, and really make this a change for good.

On the technology side, I’ve also seen some developments, for example, helping end users have a better understanding about why a specific result’s been generated, helping developers be able to more easily debug and tune and optimize their models. So we’ve always had a trade-off between accuracy and explainability in driving model selection—particularly obviously in highly regulated environments as well. So seeing enhancements around interoperability, and with bias and explainability tools across all stages and model development, I think is hugely important. And things like shapely values—the ethos of that around visibility and transparency into model decision-making is so, so important. I think it can help shorten the path to success for us all.

Kenton Williston: Yeah, absolutely. And obviously—even from my own personal experience I have found the diversity of folks that I work with on this program to be really wonderful in terms of opening my eyes to all kinds of possibilities, and just having people come from such different perspectives. Currently I’ve been saying, as much as I am really deeply immersed in this world, there’s just so many things that constantly surprise me nonetheless. And I think having this diversity of perspective is just incredibly valuable for that.

Sally Eaves: Absolutely, absolutely. It’s enriching in every aspect, isn’t it? It really is, and the foundation of Aspirational Futures I mentioned at the top, that’s what we specialize in a lot—really democratizing access into tech careers, which I think is so, so important for the future and building those skills and skills confidence as well.

Kenton Williston: Absolutely. And so I want to just mention in passing—all of these different factors—I think there’s some really good examples of how they can be applied. So, there’s a demo from a company called EverFocus that is offering an in-transit network video recorder box that incorporates analytics—both forward-looking onto the road to see what’s happening in traffic and help the driver perform at their best, and to help the folks who are routing all the transit vehicles understand what the situation is on the ground. As well as inward-facing to understand what’s happening inside the transit vehicles and help make sure everything is secure and everyone is doing just fine. And of course these days lots of new concerns—like making sure everyone’s masked up.

So, I think this is a really good example of, you could take some of these things that are potentially problematic, like the forward-looking cameras potentially doing some things that you may or may not like—to recognize people and cars and such on the road—as well as the inward-looking, recognizing people in the vehicle. I mean, there’s potential for misuse there, but there’s also potential for really amazing benefit in terms of keeping people safe and healthy, and cities running efficiently and minimizing their carbon footprint. So it’s all about how you deploy it. And I like this EverFocus demo as a kind of example of how to do it the right way.

Sally Eaves: Absolutely. That sounds fantastic. And I think enabling all voices to be heard in that as well. There’s a great example coming out of Helsinki at the moment, which is very much like that demo you were describing there, but ensuring, for example, different voices—so, citizens inputting to the development of their city. So, the example you were saying there about the city development environment and mobility—I think we’re seeing some great things. So what you were just describing there, I think, would be a great fit for that use case.

Kenton Williston: Yeah, absolutely. Absolutely. So, to just kind of wrap a bow around all of this, again, for me as I look forward to this show—and I should mention, too, for our audience that you and I will be live Tweeting some of the sessions. So, absolutely—let me try saying that again. So I should mention, of course, that you and I will be live Tweeting some of these sessions, and I absolutely invite our listeners to come join us on Twitter—follow along as we explore what’s happening as it goes down.

Sally Eaves: Absolutely.

Kenton Williston: Yeah, absolutely. So, on the whole, I’m very excited to see for myself where things are going as the industry gets more complicated, more sophisticated. But I think, for me, there’s an overriding theme here that I opened with, of bringing together so many different technologies that have been in development, on the horizon—whether it’s AI, whether it’s 5G, whether it’s safety and security—bringing so many of these things together in ways that I think really are noteworthy, and notably different than what I saw last year at this time. How about you? What are you looking forward to?

Sally Eaves: Absolutely, absolutely. As I said earlier, I think there’s a real acceleration in innovation, and around the actualization. The speed of change has been unlike things we’ve seen before, absolutely. So, I think there is a real step change this year vis-a-vis the one before. So I think that’s really, really exciting.

One of the sessions I’m going to definitely be looking at is Peter Fang—who’s talking about bridging Orchestrator and hard, real-time workload consolidation. I think that’s a really interesting one—with Edge computing, smart factories. It’s really pushing that demand for consolidation orchestration across mixed and critical workflows. So that’s definitely a session I’ll be looking at in detail.

But there’s so many. It really is a kind of smorgasbord really, isn’t it? Fourteen sessions on Internet of Things, platforms and applications—just fits into a lot we’ve been talking about in our conversation today. But I think what I like about this is it’s five days long—you can really pick and mix this, tailor it to your particular organization and also what you want to learn about. There’s so many opportunities to really dive in deep and ask questions.

I also like the matching application they’ve put together as well. So you can really tailor it. It feels like a proper personalized experience. So that’s really exciting because, if you can’t be there in person, then making an event feel like a true interactive experience matters so much. And I think there’s been a real effort around that curation. So I love to see that.

Kenton Williston: Fabulous. Well—should our listeners be coming to this podcast after the fact, where can they find you online?

Sally Eaves: That’s a great question. Well, I think the one to go for, number one, would be @sallyeaves on Twitter, but I’m on all major channels, basically. But Twitter is the easiest starting point. But LinkedIn, my own website, etc., as well. And I’ll share details after the podcast.

Kenton Williston: Lovely. All right. Well, that just leaves me to thank you for joining us today. Really appreciate all your insights.

Sally Eaves: Absolute pleasure. Thank you so much. And really looking forward to the event.

All right, we’ll see you there.

The preceding transcript is provided to ensure accessibility and is intended to accurately capture an informal conversation. The transcript may contain improper uses of trademarked terms and as such should not be used for any other purposes. For more information, please see the Intel® trademark information.

About the Author

Kenton Williston is an Editorial Consultant to and previously served as the Editor-in-Chief of the publication as well as the editor of its predecessor publication, the Embedded Innovator magazine. Kenton received his B.S. in Electrical Engineering in 2000 and has been writing about embedded computing and IoT ever since.

Profile Photo of Kenton Williston