Podcasts about openvino

business traditional intel editorial director segmentation upleveling meta ai openvino

Play Episode Listen Later Mar 28, 2024 21:07

Across all industries, businesses actively adopt computer vision to improve operations, elevate user experiences, and optimize overall efficiency. Image segmentation stands out as a key approach, enabling various applications such as recognition, localization, semantic understanding, augmented reality, and medical imaging. To make it easier to develop these types of applications, Meta AI released the Segment Anything Model (SAM)—an algorithm for identifying and segmenting any objects in an image without prior training. In this podcast, we look at the evolution of image segmentation, what the launch of Meta AI's Segment Anything model means to the computer vision community, and how developers can leverage OpenVINO™ to optimize for performance. Join us as we explore these ideas with: Paula Ramos, AI Evangelist, Intel Christina Cardoza, Editorial Director, insight.tech Paula answers our questions about The importance of image segmentation to computer vision Traditional challenges building image segmentation solutions What value the Segment Anything Model (SAM) brings Business opportunities for image segmentation and SAMs The power of OpenVINO to image segmentation The future of OpenVINO and Segment Anything Related Content To learn more about image segmentation, read Segment Anything Model — Versatile by Itself and Faster by OpenVINO. For the latest innovations from Intel, follow them on X at @IntelAI and on LinkedIn.

Intel Core Ultra: The Personal AI Processor - Episode 323

Piltch Point (Audio)

Play Episode Listen Later Dec 18, 2023 32:40

One of the recent technological developments is the release of Intel's new Core Ultra CPUs for laptops, which are equipped with a neural processing unit (NPU). These CPUs, also known as Meteor Lake, are a significant advancement as they are the first mainstream Intel chips to have an NPU integrated into them.The NPU's purpose is to handle AI processing more efficiently and quickly than the regular processor can. This opens up possibilities for local generative AI tasks, such as image generation, audio transcription, and music creation, which are typically performed in the cloud. By having the NPU in laptops, these tasks can be completed in a competent amount of time locally, without the need for an internet connection or relying on cloud services.Avram demonstrates the performance difference between using the CPU and the NPU for tasks like image generation and audio transcription. The NPU significantly reduces processing time while also allowing for better multitasking since the CPU and GPU are not being heavily taxed. This power efficiency is particularly beneficial for laptop users, as they may not have access to a powerful graphics card.Avram also mentions the potential drawbacks of relying on cloud services for AI tasks, such as privacy concerns and the need for a stable internet connection. Having the ability to perform these tasks locally with the NPU addresses these issues and provides a more convenient and secure solution.Additionally, he discusses the compatibility of Intel's OpenVINO project with Intel GPUs. While the NPU is not available for all tasks, the use of Intel GPUs can still enhance processing speed compared to using the CPU alone. However, it is important to note that the compatibility and optimization of these tasks may vary depending on the hardware used, and requires an Intel GPU in order to transfer tasks to a GPU (AMD and Nvidia will not work).New chips, benchmarking, performance differenceAvram highlights the discussion around new chips, benchmarking, and performance differences. He has been working on benchmarking and will soon release an article showcasing the performance differences between Intel and AMD chips, as well as the differences with the previous generation.Benchmarking plays a crucial role in evaluating the performance of these new chips. It allows for a direct comparison between different chip models and brands, as well as a comparison with previous generations. By conducting benchmark tests, Avram aims to provide readers with a clear understanding of the performance differences between Intel and AMD chips, as well as how the new chips perform compared to their predecessors.While the software is developed by Intel and focused on In tle hardware, the benchmarking has not always shown that to be the case. When accessing the NPU, which is currently specific to the Intel Core Ultra processors, Intel wins every time. However, when running the tests against the CPU, AMD often comes out ahead. This means that, while the NPU advantages are a clear winner, AMD processors are capable of just as much as Intel when it comes to direct CPU usage.ConclusionOverall, the introduction of Intel Core Ultra CPUs with an NPU represents a significant advancement in laptop technology. It offers users the ability to perform AI tasks locally, improving processing speed, power efficiency, and privacy. As technology continues to evolve, it is crucial to stay informed about these advancements and adapt to new developments that enhance our digital experiences.

ai personal intel nvidia amd cpu gpu benchmarking processor avram intel core personal ai npu intel core ultra openvino meteor lake intel gpu intel gpus

Exploring the Next Generation of Artificial Intelligence: With Intel®

Technically Speaking: An Intel Podcast

Play Episode Listen Later Dec 14, 2023 26:06

Explore the groundbreaking AI innovations unveiled at Intel® Innovation 2023 to learn about the role of AI in solving real-world problems and becoming more accessible to developers. Paula answers our questions about: (1:54) Advancing AI and its role in real-world problem-solving (4:05) Intel's role in making AI easier and more accessible to developers (6:53) The biggest announcements from Intel® Innovation 2023 (10:46) OpenVINO™ and its impact on the Intel partner ecosystem (14:46) How developers can take advantage of the new SDK for Intel® Geti™ (18:22) Empowering women in AI (22:30) The future of AI development and tips for new developers Related Content To learn more about AI trends, read Evangelizing AI: The Key to Accelerating Developers' Success and listen to Personalized AI Shopping Experiences: With FIT:MATCH. For the latest innovations from Intel, follow it on Twitter @intel and on LinkedIn at Intel Corporation.

success ai explore artificial intelligence empowering next generation intel sdks intel corporation openvino intel innovation

[Promo] Saving Crops with AI with Graeme Klass

Daily Dad Jokes

Play Episode Listen Later Oct 26, 2023 36:06 Transcription Available

Hi, this is Graeme Klass producer of the Daily Dad Jokes podcast. You may remember me from the Dad Jokes Explained episodes. You may be wondering why this episode has popped up on your feed. I am hosting a new podcast called “Technically Speaking: An Intel Podcast” which, in its debut season, will be exploring the expanding role of AI. I think you will find it interesting. AI can solve some of today's most complex challenges, and over the years this has become reality even in the agricultural industry. Due to environmental factors and other threats, sustainable farming is becoming more at risk, and by harnessing the power of AI, tools to help local farmers are more accessible on a global scale. In this episode, learn how Rishikesh Amit Nayaka and Niharika Haridas used AI and Intel's OpenVino technology to detect pests, and make farming equitable and successful in India. Additionally, they are joined by Intel's Director of Government Partnerships and Initiatives for Japan and the Asian Pacific, Shweta Khurana, who explains Intel's work with developing the latest voices in AI innovation. Learn more about how Intel is leading the charge in the AI Revolution at Intel.com/stories SASee omnystudio.com/listener for privacy information.

director ai japan saving promo intel crops initiatives graeme ai revolution klass asian pacific openvino daily dad jokes

Saving Crops with AI

Play Episode Listen Later Oct 17, 2023 35:27 Transcription Available

AI can solve some of today's most complex challenges, and over the years this has become reality even in the agricultural industry. Due to environmental factors and other threats, sustainable farming is becoming more at risk, and by harnessing the power of AI, tools to help local farmers are more accessible on a global scale. In this episode, learn how Rishikesh Amit Nayaka and Niharika Haridas used AI and Intel's OpenVino technology to detect pests, and make farming equitable and successful in India. Additionally, they are joined by Intel's Director of Government Partnerships and Initiatives for Japan and the Asian Pacific, Shweta Khurana, who explains Intel's work with developing the latest voices in AI innovation. Learn more about how Intel is leading the charge in the AI Revolution at Intel.com/storiesSee omnystudio.com/listener for privacy information.

George Clopp, Korbyt

Sixteen:Nine

Play Episode Listen Later Sep 18, 2023 31:09

The 16:9 PODCAST IS SPONSORED BY SCREENFEED – DIGITAL SIGNAGE CONTENT What if you could use AI to make digital signage screen content relentlessly relevant? That's the premise and promise of what Korbyt calls Machine Learning Broadcast, new capabilities in the Dallas-based software firm's CMS platform. Using computer vision and machine learning, the idea is that if the platform can get a sense of what's making people stop and watch in a defined environment, then content can be optimized based on that interest. The system finds and schedules content to push to screens based on engagement metrics. How it all technically works is a bit over my shiny head, but I had a good chat with Korbyt CTO George Clopp about what's going on and its implications. We also get into what the future looks like for AI in digital signage. Subscribe from wherever you pick up new podcasts. TRANSCRIPT Geroge, thank you for joining me. We've chatted in the past. For those who don't know Korbyt, can you give me a rundown of what the company's all about? George Clopp: Hi, Dave. It's a pleasure to speak with you again. Yeah, Korbyt is at its root an employee engagement company. So we've got roots in digital signage, but our typical use case is using digital signage at corporate campuses and to communicate to employees, to increase employee engagement as well as to communicate real-time mission-critical stats as well. Is that pretty much the core vertical that you guys chase, workplace? George Clopp: It is. We are heavily into the workplace, meeting rooms as well. We do a lot with retail banks, a little bit into the retail space, but it's primarily corporate campuses. For those who don't know the company, it actually goes back a long way to Symon Communications days, right? You guys were doing workplace communications long before the digital signage industry discovered that. George Clopp: Yeah, exactly right, Dave. It precedes me. I've been here for seven years now. I can't even believe it, but that's how much I enjoy this space and the industry. I enjoy the company so much, but we had Target Vision, Symon Communications, and we've just evolved. I joined at the tail end of 2016 to develop the Korbyt platform, and obviously, we have to meet the needs of the digital signage industry, but we've had a really heavy focus on employee engagement as well. Is it interesting to see all these other companies who have more general offers, find their way into the workplace because they see that as an opportune vertical? George Clopp: Yeah, I view it as exciting. I think it's definitely a macroeconomic trend with the pandemic, post-pandemic, the modern workplace, everything is reimagining and reinventing and re-everything these days. I think it's good. It's a legitimate macro problem that everyone's looking to provide solutions to. So, I'm really excited. I love the industry myself. In some respects, you guys have been doing back-of-house, a lot longer than most companies would have. I mean, you're not just working in the offices, you're working in production areas and so on. George Clopp: That's correct. Heavy in manufacturing and heavy in the contact centers, anytime where you're doing mission-critical real-time data, you're connecting to an ERP (Enterprise Resource Planning), or yard management system, and you want to change or orchestrate the display and the surroundings based on data changing, we've got a deep background in that. Yeah, for contact centers, if I recall, years ago pre-arrival with the company, you were doing low-resolution LED readouts that were just telling people in the contact center about the average wait time on calls and things like that. George Clopp: Exactly, and that's matured over the years and now we're doing that on the desktop and on the mobile device as well. We still have some supply chains and some yard management systems in a warehouse, where we'll do the little blinky boards over the dock doors themselves. We range from the dock doors all the way to your mobile device now. The PR that came out about a new piece of functionality, your marketing talks about a million endpoints, 250 cloud migrations, and 100+ native integrations. A million endpoints, that's like a lot. George Clopp: It is. Yeah, scalability and being able to expand out to touch desktops, normal, typical digital science screens, and mobile endpoints. It's been a real focus on us for the last four or five years. So we're really proud to announce that, and then the back end, like you were talking about those native data integrations, I think that's really what sets us aside from a lot of our competition is making those really hardcore authentications and then that real-time pipe between us and the source systems. I know a lot of other software in our space that we run into, they talk about integrations. A lot of times it's really just a file, they're taking data from a source system. They're putting it into a CSV format or any kind of other format and then they're pulling that in. So that's really where we shine with that real-time data integration. Is that important in terms of a distinction when solutions providers and users are looking at data integration and they see that a CMS says, yeah we do data integration, we can integrate with your platform? It sounds like you're saying there are different tiers of that, and there's real integration and there's just like a baseline. George Clopp: Yeah, exactly. That's the right way to pick up on that day, for sure. When you need to orchestrate and change things in a 911 center or in a manufacturing-type environment and definitely in a contact center, speed is really the key there. So having something on a five-minute loop that's pulling a file, it's just not fast enough. So you need that real-time data, you need that high availability so that something was to break that you've got a backup in place and you can make sure that contact center, that supply chain, that 911 center is rolling smoothly. They're not just getting their data, but they're changing the experience of the data. That's another thing that we do, we pull in stats, but we also augment those stats and do value-added calculations on the stats, and then we trigger on those values to change the screen, or change the mobile device or change the desktop. So if you've got too many calls in the queue or you're running behind on this loading dock here, we'll change the entire experience for you based on that value-added stat that we do. I also assume that when companies talk about integrations, for very logical reasons, they're going to go to the most used platforms out there, whether it's Teams or God knows what. But if you have a hundred plus native integrations you're probably talking about some pretty exotic things that nobody's ever heard of, and if a company went in and said, we can integrate with their systems and they say, what those systems are, their eyebrows are going up, because they're thinking, I have never heard of that. George Clopp: Absolutely, Dave. There are some low-level protocols where we just integrate at a TCP level with a very proprietary protocol, but I would say the bulk of it is more modern, JSON-based RESTful interfaces, for sure and we like to distinguish between data integrations, business application integrations, and SSO integrations, in three categories there. So, like a Power BI or a Tableau or something like that would be more of a business application integration, and when we're talking data integration, we're talking more low level, running SQL against a data store, running web services, running SOAP-based web services, and to that extent. And again, that's why we call it out in our marketing because we do think that's a core differentiator for us. So just to go back to something, when you talk about a million endpoints, you're including desktops.. George Clopp: That's correct. Desktops and mobile devices, basically all of the endpoints that we talk to. Good. Back at the start of summer, you guys introduced something called, Machine Learning Broadcast. What is that? George Clopp: Yeah, fantastic question. We were involved with machine learning, and AI before it was really cool, so this was actually something we developed in 2018. We've been honing the model, and then we re-released it this year. But machine learning is a subset of AI, and we all know AI is a super big buzzword these days and when you peel that onion, there's levels of accuracy involved there, and there's a lot of hype around the world. But the reason why we called the feature machine learning broadcast is really to focus on the ML aspects of it, and it's a great business problem to solve because, at the end of the day, what we're really creating is a recommendation engine. And I think everybody's familiar with the Amazon recommendation engine, Instagram, and other social media platforms that are just, they're recommending content for you. That's essentially what we're doing here. We're using KNN Analysis, which is supervised machine learning to look at content that has some engagement with it, and that engagement could be measured by computer vision on a digital signage screen, it could be measured by interactivity with it on a desktop or interactivity with that content on the mobile device and then behind the scenes, all we're doing is we're finding out second, third, fourth-degree order content, that's related to the content that was engaging and then it's a feedback loop. We go ahead and automatically schedule that content and see how that content is engaged with so it's a self-learning feedback loop there and the whole purpose of it is to find content that's engaging and show more of that content to your employees. Could you give me a real-world kind of example of how that might work? George Clopp: Yeah, absolutely, Dave. Let's say a company's opening up a brand new office in Buenos Aires and for whatever reason, people really gravitate to that content. They look at it on the signage screen, on the fifth-floor break room, they're engaging with it on their desktop, they're looking at it on the mobile device. We learn from that engagement and say, okay, let's go ahead and find similar related content there. Let's find content related to office openings in Buenos Aires, and then let's go ahead and go further out and look at second, third-order tags. So that would be content related to South America as well. And then we automatically play that content, inject it back into the playlist, and our customers have complete control over whether it's automatic and which players actually get this content and which devices get it and then, we learn based on that content. So it's a feedback loop, and you might find in that case that your employees are really more interested in the geographic region than they are in the new office opening. So it's relentlessly relevant. George Clopp: Exactly right, Dave, and solving a real-world business problem because one of the challenges our customers have is, it's really arduous to constantly schedule new relevant content. The first couple of times you do it, you create a scheduled playlist. Yeah, it's okay, but it takes a long time and then, with Attention Deficit Disorder in today's modern world, people grow immune, and they tune out that same content over and over again. So, you need that fresh content injected to keep the employee's attention. I'm guessing that somebody's going to be listening to this and thinking, that's cool, but where on earth do I get, or how do I develop all this content so that I do have this somewhat bottomless hyper-relevant content available? George Clopp: Yeah, fantastic question. Right now, in its current stance with our ML broadcast, you need to have that content in your media library. We're not automatically going out to like copyright-free areas and pulling in content. But with our release coming out next year, it's called our AI employee engagement. With that, we'll automatically be creating and sourcing content for you on your behalf. Yeah, I saw a demo of something like that over in Germany a little while back with another company who, I'm sure you'll be happy if I don't name them, that was all about using what was available through an intranet and an extranet, and other resources to auto-generate content for screens. George Clopp: Yeah, it's opening up the whole world of generative AI. We're actually looking at both. Whether there are generative images, generative video, or generative text. Obviously, in our space, images and videos mean a lot, and there are different systems out there. There's DALI 2, there's stable diffusion. They've all got their strengths and their weaknesses. But we're combining that with templated-based content as well. So automatically generating content that's relevant based off of a text prompt is super useful. But in some cases, it might not be the right content that's generated. So we also will have a mixture of templated content as well. Yeah, I think templates are a big part of that. I've farted around with things like Mid Journey and so on, and you could see how it could go sideways on you really quickly if you left too much up to the machine. George Clopp: Exactly. It gets into that whole thing of prompt engineering. You got to be really good with your prompts, and they've all got issues like generating hands and things of that nature right now. But we want to be on the leading edge of this, use it where it makes sense. An area where we think it really makes a lot of sense, a preview into our AI Employee Engagement, is on mission values and goals. We feel like that's an area where our customers just don't communicate enough to their employees, like, there's cake in the break room, let's recognize employees. That's all part of it, but really just reinforcing, Hey, your goal in the finance department this week is to close your books three days earlier. And so, mix that text in with some great video or some great images that are created in the background using this generative AI. Yeah, I saw something on LinkedIn last night, and I commented on it because I thought it is great that there's a company that's using KPIs and messaging right on the production floor, and the person who posted about it said, this is not very sexy, but it goes to what's needed on the floor for those workers. But the problem was, it looked like hell. It was just black and white, and they were slapping up a whole bunch of Excel charts, like a stock of them and you'd need binoculars to even see them. So it's important to think about the presentation. George Clopp: Yeah, totally agree, Dave. I say this at all my speaking events: content is king, content is queen, and that still rules the day. When we're intermixing real-time data with content, it has to be visually appealing. You can't have 20 different stats on the screen; all of those rules of graphic design, I still think, hold true here. Do you see a day when things like scheduling and trafficking of content are largely automated and handed off to machine learning or some variant of AI? George Clopp: That's exactly what we're trying to build, Dave, with a release next year. With the ability, of course, to intervene, the ability for the communicator to come in and approve the content or really go ahead and bias the content and say, okay, I've got these 30 categories of content I see that I really want to bias, what the content areas could be. “Hey, I'm a new enroll. I'm a new first-time line manager. I'm a new director. I'm a new VP, and there's content associated with that new enroll.” They might want to bias that and increase the weight on it, decrease the weight on it, or take it out altogether. So there's still going to be that human touch involved in the ability to approve content, but the AI itself will take care of making sure that content is fresh and relevant. And the big problem we're solving there is just that, again, attention deficit disorder people have, if they see the same thing on the screen, week after week, they tend to tune out. So how can we think of innovative ways to display KPIs, display goals, display things that are really important to the company and give it a great background, give it a great video so that it gets employees' attention again? We're going to talk about machine learning. You reference AI-driven camera optics. Is that basically a computer vision? George Clopp: It is. Absolutely is, yes. Did you guys write your own, or are you using something like Intel's OpenVINO? George Clopp: Yeah, the two big ones out there, we've used OpenCV, that is, Open Computer Vision, and TensorFlow, and they both have their strengths and weaknesses, but there are higher order problems we're trying to solve here, and not reinvent computer vision so we're using some libraries for that. Is that just part of the mix of doing this sort of thing? Are there other technologies you can use to get a sense of dynamics in a venue? George Clopp: Yeah, I think so. Infrared detectors, pressure sensors that kind of tell you who's in that immediate vicinity. You're basically correlating that to human beings in the vicinity, how many human beings are there, and what was playing on the screen at that time. Yeah, so there are less technological ways to do this and still get some good results. AI is being talked about a lot as you've gone through about its potential to automate presentations. Are there other aspects to a digital signage company, the way your company operates, that you can use AI to help with marketing, help with customer contact, that sort of thing? George Clopp: Yeah, without a doubt. I'm sure you're reading everything. It's revolutionizing all traditional roles, right? Not just engineers writing code. You got a chat with a ChatGPT engineer. With Microsoft's Copilot, it's going to revolutionize the way we all use Excel and Word and PowerPoint and things of that nature. It's definitely revolutionizing marketing. Building product brochures for you automatically, things of that nature, and then, that naturally progresses into, is AI going to take all of our jobs, which I don't think so, going to help us all become more productive. The employees that really change and adopt the AI, I think they're going to be even more valuable than they are today. It's just the employees that just say, I'm not going to do this, and they refuse to allow their cheese to be moved, those are the ones that I think you have to watch out for. There's an increasing number of companies. I just wrote about one today that has gone down the path of headless CMS. The idea that you can leave the final presentation later, the interactive element, whatever it is to software developers at a large company or who works with a large company as a services company and the digital signage CMS is just the infrastructure, the foundational platform that does device management, scheduling, trafficking, all that sort of stuff. Are you seeing that demand in the marketplace? George Clopp: We're seeing the opposite. What you're saying absolutely makes sense, especially with my background and the way we've architected our product with microservices. What we're seeing, especially with our large enterprise customers is, they want a little more white glove service. Taking on the arduous task of piecing everything together, even with a microservices framework, is putting a lot of ownership on them. But that is not to say that there's not a need out there. We just really haven't found it. We've actually gone the opposite direction on our side, which has really served us well because we've gone from zero revenue in the cloud to 2 million. We brought on a new CEO, and we quickly ramped up to 20 million. I think it's working for us so far. Yeah, you're a very different company than maybe prior to you joining RMG Networks, that was a weird little side trip into digital out of home. George Clopp: It was. We see the artifacts and all that, but I think it's a great group of people here now. There's not a leftover where people have bad attitudes or anything like that. So really proud of where the company's been, the talent we've acquired. We've acquired people from all over the industry. Really love working with the current team and cross-functionally, not just engineering and support, which is what I run, but in sales and marketing as well. Yeah, it's interesting when you mentioned you've gone in the opposite direction of headless. I've heard that as well, particularly when you get into, like Fortune 500, Fortune 100 kinds of enterprise-grade customers. They want to outsource digital signage, by and large, in the same way that they've outsourced a lot of IT services. George Clopp: Yeah, absolutely. That's the same trend we're seeing, Dave too. It's a little bit of both, right? Everybody wants their cake and eats it too, right? Like they want you to have the ability to do it, but then when it comes time to actually execute on it, we typically find, Hey, we can help them get faster to market if we help augment their team. How important is security? George Clopp: Oh! It's Huge. We all know that the disaster scenario in digital signage, someone compromises your network and they put up some content images or videos that are not appropriate. Even more so with us being more omni-channel with desktop, mobile devices. We've got a data privacy officer, we're SOC 2 compliant. We do a lot of work in Europe so GDPR comes up a lot as well, data privacy. So I think it's super important. When I think you look at the different offerings out there and the first tier, we look and sound the same. So I think what you got to do with new prospects or new customers, they just got to peel that onion more. What does that really mean? What does it mean that you encrypt your data? Do you do it at rest? Do you do it in transit? Those kinds of things, and I think that's where you can tell the difference between different offerings. And are the people in the first and second meetings with prospective customers different than they were 7 years ago when you started? I'm hearing the IT people who used to come to meetings and sit there with their arms crossed, thinking, dear God, how long is this going to go on? They're now tending to lead these meetings. George Clopp: Yeah, I've seen it in multiple ways. Definitely, IT is still the big persona of the buyer here. But I'm also seeing less and less about speeds and feeds and players and hardware and transmission equipment and scalers and more about the final purpose of what we're trying to do. I'm just starting to see that shift. Seven years ago, I talked to people, and it's the AV integration guy. I don't really care what's on the screen. I just care that it's not dark. I don't want a screen that's down. That's their most important thing, and now I'm seeing that shift a little bit more towards they do care about the content, and they're bringing in more of the HR and the communications group involved and making sure that the platform can grow. I can create content on the platform or I can integrate with Adobe or SharePoint or something along those lines. But I still see it, especially AV/IT as a huge influence in the buying process. Yeah, certainly going back seven, eight years when I was doing some one-to-one consulting with enterprise level customers, that sort of thing, I would go into a first meeting, and I would say, okay, why do you want to do this? And it was always intriguing to see how often people would lean back in their chairs and say, I hadn't really thought about that. They wanted this thing, but as you say, they didn't really know what they were going to do with this thing. George Clopp: Yeah, exactly. And there's a little bit of power in that too. There's power to putting the latest and greatest screen technology in your office and giving you that modern technology look and feel but then just carry it one more step in the maturity direction and start focusing on the content too. Yeah, you can demonstrate innovation by having a big ass screen in your lobby, but if there's nothing useful on there, you're not really demonstrating a lot of innovation. George Clopp: Exactly, and I think there's still room for that super wonderful creative experience that's human-curated that graphic designers make, and they spend a lot of time getting just perfect in those high profile areas, like the lobby of a company, and then there's also opportunity for, new content generation automatically for me so that I don't have to necessarily sit here and handle this thing. So I think we're going to live in a world where both will be applicable. So you mentioned you, you're working on new iterations of AI-driven content. Is that the big kind of roadmap item for your company over the next year? George Clopp: Yes, it really is. Yeah. We've got a huge, large-player ecosystem, all the data integrations, and omni-channel platforms. So where our new development team is focused on is automating the content creation, automating that entire feed, if you will, so that it really takes that arduous process away from our communicator. How many folks do you have in the company now? George Clopp: We're a little under 70 people right now. So still a small company and I love it cause everybody has to wear multiple hats, do multiple roles. You have to bring a lot of energy to the company, and I just love that. I've just grown so fond of it over the last seven years. And is most of the team in the Dallas Fort Worth area, or are you all over the place? George Clopp: Since COVID, we're mainly in Dallas, but since COVID, a lot of us have moved out a little bit. So I'm actually in Colorado. Some of my engineering leads are in the West Coast, some are in Pennsylvania. So we're really practicing what we preach, the hybrid workforce. All right, George, thank you for spending some time with me. It was good to catch up. George Clopp: Yeah, it's fantastic, Dave. Thank you so much for taking time out.

Streamline Retail Checkout with AI-Powered Queue Management

ai future management tools retail intel successfully checkout github operations managers streamline queue ria ai powered editorial director intel corporation openvino

Play Episode Listen Later Jul 20, 2023 23:51

Long wait times and slow checkout lines have become all too familiar in retail stores. With each passing second, customers grow increasingly frustrated, leading to a negative impact on customer satisfaction, store business, and reputation. In today's fast-paced world, shoppers no longer tolerate such experiences. Fortunately, recent advancements in AI have opened doors to developing solutions that can significantly improve store operations and enhance customer journeys. But lack of in-house development resources poses a challenge for many retail stores looking to implement these innovative solutions. In this podcast, we explore the shifting landscape of customer expectations, innovative ways AI is used to address retail challenges, and skills and knowledge necessary to build, deploy, and implement AI across retail stores. Join us as we explore these ideas with: Ria Cheruvu, AI Software Architect and AI Evangelist, Intel Nicole O'Keefe, Senior Product Marketing and Operations Manager, Pathr.ai Christina Cardoza, Editorial Director, insight.tech Ria and Nicole answer our questions about Changing customer expectations and retail challenges How retailers can become more actionable with AI Building, developing, and deploying AI retail applications AI's business value and benefits for retailers Tools necessary for developing AI applications Where developers can get started building solutions Successfully implementing AI solutions in stores Creating an end-to-end retail operations solution Continuing the success of AI in the retail space Related Content To learn more about developing retail technology, read The Future of Retail Technology Is Spatial Intelligence, visit Intel's AI Reference Kits, and join the OpenVINO™ discussion on GitHub to share your experiences. For the latest innovations from Intel and Pathr.ai, follow them on Twitter at @intel and @pathr_ai and LinkedIn at Intel Corporation and Pathr.ai.

Accelerating Developers' AI Success with OpenVINO™

success ai developers intel accelerating editorial director yury openvino

Play Episode Listen Later Jun 1, 2023 33:21

From diagnosing diseases to detecting defects on the production line to providing deeper insights into customer behavior—AI increasingly transforms the way businesses across all industries operate today. But who truly makes these deployments successful is developers creating AI models and solutions capable of providing business value. When AI developers are equipped with the right tools, technology, and knowledge, they have the power to make all kinds of exciting and innovative use cases. In this podcast episode, we discuss how AI is used to improve efficiency, make better decisions, enhance customer experience, and provide a competitive advantage. We also explore tools and technologies that allow developers to successfully build and deploy these AI models and solutions as well as touch on some of the latest capabilities in the OpenVINO™ 2023.0 release. Join us as we explore these ideas with: Yury Gorbachev, OpenVINO architect, Intel Raymond Lo, AI Software Evangelist, Intel Christina Cardoza, Editorial Director, insight.tech Yury and Raymond answer our questions about The evolution of artificial intelligence in recent years How developers benefit from AI advancements Best practices for successful AI deployments The five-year anniversary of the AI toolkit OpenVINO New tools making AI more accessible to business users The future of AI and the role of OpenVINO What developers can expect in OpenVINO 2023.0 Related Content To learn more about AI development, read Development Tools Put AI to Work Across Industries. To learn more about the latest release of OpenVINO, visit https://openvino.ai/. For the latest innovations from Intel, follow them on Twitter and LinkedIn.

Going Deep with Brainpool AI and Intel OpenVINO – Conversations in the Cloud – Episode 288

Intel Conversations in the Cloud

Play Episode Listen Later Jan 6, 2023 13:10

Joining Jake on the podcast today is Kasia Borowska, Co-Founder and Managing Director at Brainpool AI. The duo discuss the...[…]

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Computer Vision and NLP in Practice with ExamRoom.AI - Episode 292

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Play Episode Listen Later Jan 5, 2023 16:03

Deepak MK, Vice President of Data Science at ExamRoom.AI sits in with Jake to discuss the company's primary mission: to provide a highly secure, unified assessment system and fair environment to the candidates who take online remote proctored exams. ExamRoom.AI's research and advancements in AI technology have unleashed leap-forward technological accomplishments, leading to efforts toward making robust online testing a reality. Universities and organizations alike face difficulties in ensuring integrity and security in testing that ExamRoom.AI can address. Using 3rd Generation Intel® Xeon Scalable Processors and OpenVINO helped ExamRoom.AI reduce the occurrence of memory issues and build better machine learning models through its scalability and latency reduction, greatly reducing model training time. Intel's Ice Lake processor speeds up and enhances their systems, helping avoid dreaded Out Of Memory (OOM) errors. Check out their website for more information at ExamRoom.AI

BasicAI Leads Multisensory Training Data Effort with Extreme1 - Episode 291

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Play Episode Listen Later Dec 28, 2022 12:36

On today's episode of Conversations in the Cloud Alex Liu, Chief Technology Officer of BasicAI stops by to talk about the company's efforts at evolving the training data platform. Xtreme1 is the world's first open-source platform for multisensory training data and can rapidly accelerate the processing and management of training data. AI engineers spend a preponderance of their time preparing the training data. Through advanced AI-powered annotation tools, Xtreme1 improves modeling. Capable of handling various time-sensitive online/offline tasks, distributed data analysis computation, model training, evaluation, and inference, Xtreme1 is fully compatible with CPU-only runtime environments. In particular, the model inference has been optimized for Intel Xeon CPU to provide higher throughput. Inference throughput on Intel Xeon 8380 is vastly improved with the help of Intel extension for PyTorch and OpenVINO toolkit. For more information go to www.basic.ai and www.xtreme1.io

Going Deep with Brainpool AI and Intel OpenVINO - CitC Episode 288

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Play Episode Listen Later Dec 16, 2022 13:10

Joining Jake on the podcast today is Kasia Borowska, Co-Founder and Managing Director at Brainpool AI. The duo discuss the most popular applications of AI in business, how they benefit, and the best ways to start implementing solutions. Brainpool AI is an Artificial Intelligence services company that connects a global network of over 600 AI and Machine Learning experts with corporate partners. Intelligent automation helps their clients grow efficiently, reducing operational costs and overhead. The resultant higher quality products and services greatly benefit their customers' clients. Libraries like Intel OpenVino help leverage existing models in creating solutions for business partners. Borowska finds most customers would like to avoid “reinventing the wheel” when it comes to onboarding new AI solutions. Check out their website for more information at brainpool.ai . Their LinkedIn also offers updates and industry trends.

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Qu'est-ce que FakeCatcher, cette IA pour démasquer les deepfakes ?

Choses à Savoir TECH

Play Episode Listen Later Dec 1, 2022 2:21

La lutte contre les deepfakes compte aujourd'hui un nouvel acteur de taille : Intel ! Mi-novembre, le géant américain des semi-conducteurs a présenté FakeCatcher, son intelligence artificielle capable de détecter en temps réel des vidéos truquées.C'est dans un communiqué de presse qu'Intel a dévoilé FakeCatcher, une plateforme dont l'objectif est de devenir, je cite le « premier détecteur de deepfakes en temps réel au monde qui renvoie des résultats en quelques millisecondes » fin de citation. Dans le détail, FakeCatcher a été conçu par Ilke Demir, chercheur chez Intel Labs, et Umur Ciftci, de l'Université de l'État de New York. L'ossature de FakeCatcher est composée de plusieurs outils et logiciels développés par Intel, comme OpenVino, Intel Integrated Performance Primitives et OpenCV. Ainsi, ce nouveau dispositif d'Intel basé sur la technique du deeplearning, apprentissage profond, se distingue des autres technologies de détection des visages par sa capacité à analyser, je cite « des blocs de vision ». En s'appuyant sur l'Open Visual Cloud et les processeurs Intel Xeon Scalable 3e génération, les développeurs ont gagné en vitesse, c'est-à-dire que FakeCatcher peut traiter simultanément jusqu'à 72 flux détectés dans un pixel vidéo. Voilà grossièrement résumé le côté technique de ce nouvel outil.Ceci dit, si vous n'êtes pas familier avec les deepfakes, sachez que ces vidéos sont généralement montées par des personnes mal intentionnées, qui font notamment tenir des propos outranciers à leurs victimes. L'ancien président des États-Unis Barack Obama a notamment servi d'exemple il y a quelques années, tout comme l'opposant à Vladimir Putin, Alexeï Navalny, dont le visage avait été détourné pour servir la communication du gouvernement russe il y a quelques années. D'après le cabinet Gartner, les dépenses des entreprises liées à la cybersécurité s'élèveront à pratiquement 190 milliards de dollars en 2023, soit une hausse de plus de 11 % par rapport à cette année. À noter qu'Intel n'est pas le seul sur le marché des outils de détection de deepfakes. Facebook et Alphabet s'y essayent déjà depuis plusieurs années, quand Microsoft a fait son grand saut en septembre avec le Video Authenticator. Ceci dit, il convient de ne pas diaboliser totalement les deepfakes, étant donné que cela peut aussi servir, notamment au cinéma ou dans les séries pour faire apparaître un acteur décédé ou en rajeunir un autre par exemple. Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

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Qu'est-ce que FakeCatcher, cette IA pour démasquer les deepfakes ?

Choses à Savoir TECH

Play Episode Listen Later Dec 1, 2022 2:51

La lutte contre les deepfakes compte aujourd'hui un nouvel acteur de taille : Intel ! Mi-novembre, le géant américain des semi-conducteurs a présenté FakeCatcher, son intelligence artificielle capable de détecter en temps réel des vidéos truquées. C'est dans un communiqué de presse qu'Intel a dévoilé FakeCatcher, une plateforme dont l'objectif est de devenir, je cite le « premier détecteur de deepfakes en temps réel au monde qui renvoie des résultats en quelques millisecondes » fin de citation. Dans le détail, FakeCatcher a été conçu par Ilke Demir, chercheur chez Intel Labs, et Umur Ciftci, de l'Université de l'État de New York. L'ossature de FakeCatcher est composée de plusieurs outils et logiciels développés par Intel, comme OpenVino, Intel Integrated Performance Primitives et OpenCV. Ainsi, ce nouveau dispositif d'Intel basé sur la technique du deeplearning, apprentissage profond, se distingue des autres technologies de détection des visages par sa capacité à analyser, je cite « des blocs de vision ». En s'appuyant sur l'Open Visual Cloud et les processeurs Intel Xeon Scalable 3e génération, les développeurs ont gagné en vitesse, c'est-à-dire que FakeCatcher peut traiter simultanément jusqu'à 72 flux détectés dans un pixel vidéo. Voilà grossièrement résumé le côté technique de ce nouvel outil. Ceci dit, si vous n'êtes pas familier avec les deepfakes, sachez que ces vidéos sont généralement montées par des personnes mal intentionnées, qui font notamment tenir des propos outranciers à leurs victimes. L'ancien président des États-Unis Barack Obama a notamment servi d'exemple il y a quelques années, tout comme l'opposant à Vladimir Putin, Alexeï Navalny, dont le visage avait été détourné pour servir la communication du gouvernement russe il y a quelques années. D'après le cabinet Gartner, les dépenses des entreprises liées à la cybersécurité s'élèveront à pratiquement 190 milliards de dollars en 2023, soit une hausse de plus de 11 % par rapport à cette année. À noter qu'Intel n'est pas le seul sur le marché des outils de détection de deepfakes. Facebook et Alphabet s'y essayent déjà depuis plusieurs années, quand Microsoft a fait son grand saut en septembre avec le Video Authenticator. Ceci dit, il convient de ne pas diaboliser totalement les deepfakes, étant donné que cela peut aussi servir, notamment au cinéma ou dans les séries pour faire apparaître un acteur décédé ou en rajeunir un autre par exemple. Learn more about your ad choices. Visit megaphone.fm/adchoices

Cloud Native AI Development with Zeblok - CitC Episode 285

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Play Episode Listen Later Nov 17, 2022 20:15

Mouli Narayanan, Founder and CEO at Zeblok, join Jake Smith to discuss Zeblok's Ai-MicroCloud platform and how it streamlines AI delivery by providing a single, cohesive, turnkey, cloud-native AI environment. Mouli shares Zeblok's mission and describes how the Ai-MicroCloud enables enterprises to quickly deliver AI at the edge and integrate AI solutions into mission-critical processes, faster and with lower costs. He expresses how AI deployments at the edge are becoming a main point of data origination and consumption for the enterprise today. Discussing how Zeblok is helping drive this shift and assisting enterprises with needed ISV (independent software vendor) integration to drive their edge AI deployments. Mouli also covers how collaborating with the Intel Disruptor Program has enabled Zeblok to optimize their platform for Intel technologies like OpenVINO and bring greater value to their customers. Lastly, Jake and Mouli discuss the future of AI and how artificial intelligence will drive incredible improvements in productivity in the enterprise. For more information, visit: https://www.zeblok.com/ Follow Jake on Twitter at: https://twitter.com/jakesmithintel

Ryan Loney, Intel: Bringing Deep Learning to Enterprise Applications

Code Comments

Play Episode Listen Later Nov 1, 2022 33:54

There are a lot of publicly available data sets out there. But when it comes to specific enterprise use cases, you're not necessarily going to be able to find one to train your models. To realize the power of AI/ML in enterprise environments, end users need an inference engine to run on their hardware. Ryan Loney takes us through OpenVINO and Anomalib, open toolkits from Intel that do precisely that. He looks specifically at anomaly detection in use cases as varied as medical imaging and manufacturing.Want to read more about Anomalib? Check out the research paper that introduces the deep learning library: https://arxiv.org/abs/2202.08341

intel deep learning ai ml loney enterprise applications openvino

Generating Real-Time Shelf Insights with ParallelDots Computer Vision Platform - CitC Episode 284

Play Episode Listen Later Oct 26, 2022 19:33

Ankit Narayan Singh, Co-Founder & CTO at ParallelDots, joins host Jake Smith to discuss how artificial intelligence and image recognition are transforming the consumer-packaged goods (CPG) and retail industry operations in brick-and-mortar stores. He describes how it's a challenge for retailers to identify and replenish out-of-stock products on shelves quickly and efficiently. Ankit highlights how ParallelDots' ShelfWatch platform analyzes photos captured in stores and uses computer vision models to send real time alerts to retailers allowing them to rapidly analyze and refill any shortages on their shelves. Ankit also illustrates how ParallelDots collaborated closely with Intel leveraging Intel's ecosystem program to optimize their DL models for OpenVINO. This collaboration helped significantly increase their inference throughput performance and also enabled ParallellDots to optimize some of their models to run on CPUs avoiding the need to run on more expensive GPUs. Lastly, Jake and Ankit talk about the digitization of brick-and-mortar stores and how that process is building the stores of the future. Computer Vision and artificial intelligence are exposing more data and greater capabilities for retailers to provide better experiences to their customers while increasing efficiencies. For more information, visit: https://www.paralleldots.com/ Follow Jake on Twitter at: https://twitter.com/jakesmithintel

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No-code Deep Learning Development with DeepEdge - CitC Episode 278

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Play Episode Listen Later Aug 8, 2022 13:34

Anup Mehta, Co-Founder and CEO of DeepEdge, joins host Jake Smith to discuss DeepEdge's vision to enable new edge applications, bringing the power of deep learning and computer vision to the hands of the users. He chats about how DeepEdge's deep learning operations platform supports the entire machine learning lifecycle from on boarding data to deploying edge optimized models to Intel hardware. Anup talks about how the Intel OpenVINO toolkit is seamlessly integrated with the platform for model conversion, optimization, and deployment. He also illustrates how the DeepEdge platform leverages other tools from the OpenVINO toolkit including post optimization toolkit and Neural Network Compression Framework. Anup also highlights how their platform can enable customers to migrate their workloads from a GPU based infrastructure to Intel architecture-based platforms at a fraction of the cost. Lastly, Jake and Anup dive into discussing the future of AI and how it can solve many every-day problems that people face today and how AI can deliver value to everyone in the world. For more information, visit: https://deepedge.ai/ Follow Jake on Twitter at: https://twitter.com/jakesmithintel

Improving Brain Tumor Segmentation at the Edge

Health and Life Sciences at the Edge

Play Episode Listen Later Jul 5, 2022 32:15

Intel's Abhishek Khowala, principal health AI engineer, and Séverine Habert, AI engineering manager, discuss some of the enhancements in brain tumor segmentation for enabling diagnosis.While most brain tumors are benign, early detection is critical for the best treatment options and outcomes. Assessing a diagnosis starts with MRI 2D and 3D imaging. Segmentation of the brain tumor – or separating the tumor from normal brain tissues – is essential to identifying three key factors to allow doctors to move forward:Is the tumor benign or malignant?The approximate tumor size and location.Plan out the treatment options.“We need to segment out the tumor from the rest of the tissues around it,” Khowala says. “For that, there is the unit model. And that architecture works with fewer amounts of data yet provides a clearer segmentation result.”The brain tumor segmentation (BraTS) combined with OpenVINO™ toolkit could optimize MRI results during tumor detection and monitoring. “Since this is something that has to happen worldwide, we need to deploy it at scale,” Khowala explains. Scaling requires overcoming a few challenges. Utilizing OpenVINO erases issues of high-cost GPU required for deploying AI solutions or perceived performance limitations of common frameworks such as PyTorch or TensorFlow. “Brain tumor segmentation is a perfect example of applying the most common architecture and using it for multiple devices from edge to handheld devices,” Habert adds.For optimized AI, the provided data must be robust, which is not an easy task. According to Khowala, Expert radiologists are required to interpret the MRI images to get to the ground truth data. BraTS helps predict results and compare accuracy with provided ground truth results using the Sørensen–Dice coefficient datasets. Once the data is available, modeling can take place and assist medical professionals in their diagnosis.Learn more about brain tumor segmentation solutions by connecting with Abhishek Khowala and Séverine Habert on LinkedIn or visit:https://www.intel.com/content/www/us/en/healthcare-it/healthcare-overview.html.Subscribe to this channel on Apple Podcasts, Spotify, and Google Podcasts to hear more from the Intel Internet of Things Group.

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Simplifying AIoT and Driving Digital Transformation with Intel - CitC Episode 276

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Play Episode Listen Later Jun 24, 2022 13:15

James Cho, VP of Business Development at ThunderSoft, joins host Jake Smith to discuss how Cloud and IoT accelerate digital transformation everywhere – consumer, industrial, automotive, healthcare, government, education - with almost unlimited computing power and connecting every intelligent device to the network. James talks about ThunderSoft's long-term partnership with Intel in engineering collaboration and joint venture to accelerate the digital transformation across a broad set of industry applications. He discusses how ThunderSoft's intelligent medical solution is optimized with OpenVINO on Intel platform. James highlights the Intel compute architecture and developer ecosystem as the catalyst for the strong partnership between Intel and ThunderSoft. James also shares his perspectives on the future of AI where he believes AI technology will bring positive changes to people's lives and enrich people's experiences. And that's where ThunderSoft is focused on innovating. For more information, visit: www.thundersoft.com Follow Jake on Twitter at: https://twitter.com/jakesmithintel

Deploy AI Apps with Intel® OpenVINO™ and Red Hat

Play Episode Listen Later May 12, 2022 40:37

What can artificial intelligence do for your business? Well, for starters, it can transform it into a smart, intelligent, efficient, and constantly improving machine. The real question is: how? There are multiple different ways businesses can improve their operations and bottom line by deploying AI apps. But it's not always straightforward and it requires a lot of skills and knowledge the business often does not have. Thankfully, companies like Red Hat and Intel have worked hard to simplify AI development and make it more accessible to enterprises and developers. In this podcast, we will discuss the growing importance of AI across all industries, what the journey of an AI application looks like from development to development, and what comes next, and the partners and tools that make it all possible. Join us as we explore these ideas with: Audrey Reznik, Senior Principal Software Engineer, Red Hat Ryan Loney, Product Manager for OpenVINO™ Developer Tools, Intel®Christina Cardoza, Associate Editorial Director, insight.tech Audrey and Ryan answer our questions about: The business benefits of AI and ML AI and ML use cases and adoption Challenges to deploying AI applications The recent release of OpenVINO 2022.1 Red Hat's experience with the new OpenVINO capabilities The AI app journey from development to deployment How to get started on an AI journey How OpenVINO can boost AI efforts Related Content To learn more about AI and the latest OpenVINO release, read AI Developers Innovate with Intel® OpenVINO™ 2022.1. For the latest innovations from Intel and Red Hat, follow them on Twitter at @Inteliot and @RedHat, and LinkedIn at Intel-Internet-of-Things and Red-Hat.

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AI Digital Fraud Protection - CitC Episode 271

ai model construct openvino

Play Episode Listen Later Apr 14, 2022 12:18

Mateus Dalponte from Axur joins host Jake Smith to talk about the importance of digital risk protection and how to mitigate the evolving world of digital fraud. Mateus discusses how Axur's Fake Social Removal and Digital Risk Protection platforms can help protect a company's reputation by constantly adapting to today's evolving fraud landscape. He also illustrates how the work Axur has done with Intel utilizing OpenVINO with ONNX for OCR model creation enabled Axur to achieve GPU level performance on Intel processors. Mateus wraps the episode talking about how Axur will continue to analyze and adapt to the future of fraud using AI to combat it. For more information, visit: https://axur.com/en/ Follow Jake on Twitter at: https://twitter.com/jakesmithintel

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Jak przyspieszyć inferencję ? - Adrian Boguszewski - Intel

Nieliniowy

Play Episode Play 49 sec Highlight Listen Later Mar 28, 2022 45:01

Wywiad z Adrianem Boguszewskim - AI evangelist z Intela. Rozmowę prowadził Michał DulembaRozmawiamy m.in o:- czym jest pakiet OpenVINO i do czego służy- na czym polega praca AI evangelist- optymalizacji sieci neuronowych- przetwarzaniu zdjęć lotniczych i satelitarnych- kiedy warto korzystać z Neural Compute Stick 2- warsztatach Google Summer of CodeOpenVINO - repozytoriahttps://github.com/openvinotoolkit/openvino https://github.com/openvinotoolkit/openvino_notebooks https://github.com/openvinotoolkit/openvino_contrib OpenVINO - download i case studieshttps://www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/download.html https://www.intel.com/content/www/us/en/developer/articles/community/sdp-case-studies.html#OpenVINOGoogle Summer of Code https://github.com/openvinotoolkit/openvino/wiki/GoogleSummerOfCode Przetwarzanie zdjęć satelitarnych - Landcover AIhttps://landcover.ai/ https://arxiv.org/abs/2005.02264 https://www.kaggle.com/adrianboguszewski/landcoveraiJak nagrać podcast - książka "Jak zacząć podcast" - Michał DulembaMontaż podcastu - Dobra EdycjaPosłuchaj więcej odcinków na:nieliniowy.pl - podcast o data science, machine learning i sztucznej inteligencjiNapisz do mnie:Michal Dulemba | LinkedInSubskrybuj podcast:Apple PodcastsSpotifyGoogle PodcastsPodcast AddictRSSKorzystam z: Buzzsprout (hosting odcinków):https://www.buzzsprout.com/?referrer_id=1783532Riverside (aplikacja do zdalnego nagrywania):https://www.riverside.fm/?via=dulemba

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AI: Easy construct AI model using ModelZoo N OpenVINO

Learn Scratch SG

Play Episode Listen Later Mar 5, 2022 2:41

This episode is also available as a blog post: AI: Easy construct AI model using ModelZoo N OpenVINO - Karate Coder

Scaling Throughput with AI-driven Insurance Claim Processing

Health and Life Sciences at the Edge

Play Episode Listen Later Feb 8, 2022 18:42

The successful use of AI for insurance claim processing depends on identifying and optimizing the performance of hardware and software tools that increase its efficiency, flexibility, and speed. Vasant Kearney, Ph.D., CTO of Retrace Labs, and Ravi Panchumarthy, Ph.D., Machine Learning Engineer at Intel Corporation spoke about the specific challenges faced by the dental industry when it uses cloud-based AI computing to process claims, and the creative innovations that Intel and Retrace have developed to address those challenges. “The thing that makes AI-driven insurance claim processing challenging is the throughput,” Kearney says. “If you're in a single hospital or small clinic, scalability isn't much of an issue. But once you move into the insurance world - where the volume is much higher - you have to manage spikes in throughput.” The ability of the AI algorithms being used to manage these spikes (scaling performance up or down based on demand) is determined by how much compute has been allocated to solving the problem. This is where the choice of hardware and software becomes critical. Most data scientists are familiar with GPUs and choose them when deploying models in production. But GPUs can be costly and create delays due to the way they handle memory and how they are deployed onto scalable tools. “It's not trivial to share memory between GPUs,” says Kearney. “So, you're limited by the rather low-memory footprint of each GPU. In AWS, you have GPUs in the range of 12 gigabytes. But CPUs can get up into the terabytes.” This means that many more models can be stored on each instance, making CPUs ideal for healthcare where many different models are often needed to make diagnoses. Both Panchumarthy and Kearney are excited about the future of AI-driven cloud computing for the insurance industry. “There is great synergy between cloud computing and cutting-edge hardware and software solutions from Retrace and Intel,” says Panchumarthy. “All of these are helping drive even more intelligent and robust medical AI solutions. It's an exciting place to be.” Learn more about AI deployment solutions by connecting with Vasant Kearney and Ravi Panchumarthy on LinkedIn or visit Intel's AI and Deep Learning Solutions to learn more about AI-driven Solutions: https://www.intel.com/content/www/us/en/artificial-intelligence/overview.htmlTo get started with OpenVINO: https://docs.openvinotoolkit.org/latest/index.htmlLearn more about Retrace: https://retrace.ai/media-and-news/Subscribe to this channel on Apple Podcasts, Spotify, or Google Podcasts to hear more from the Intel Internet of Things Group.

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AI Enabled Machine Vision with Eigen Innovations' Scott Everett

The Robot Industry Podcast

Play Episode Listen Later Feb 2, 2022 30:40

Eigen Innovations is a Fredericton-based technology company that provides software solutions for the Industrial Internet. Eigen has a patented multi-dimensional non-linear software algorithm that leverages "big data" information from industrial equipment and, based on the algorithm's optimization capability, provides control input into the key devices that operate the manufacturing process. The end result is a more efficient manufacturing operation. Scott Everett is the co-founder and CEO of Eigen Innovations Inc., an independent software vendor based in Fredericton, New Brunswick, Canada that delivers advanced AI-enabled machine vision solutions and software for industrial manufacturers. Scott is a PhD candidate at the University of New Brunswick where he graduated with a Masters degree in Mechanical Engineering. Driven by a passion for bringing technology to the factory floor to solve complex and unseen process and quality problems for manufacturers, Scott and his team have designed a machine vision platform that's been successfully adopted by tier 1 automotive suppliers across the globe and that's scaling rapidly with partners like Intel and Amazon Web Services helping to kick open the right doors. How did you get involved/started with Eigen Innovations? Machine vision is a hot space right now, can you define the difference between AI and ML? Vision has suffered thorough robustness and certainly, and you are out to solve this challenge? What makes your approach different? What is OpenVINO toolkit? Let's talk about the data. Where is it? How does quality access it? Who calls you? Industry 4.0 person? Plant Mgr, Quality Professional, CEO? What are the benefits and savings? IS ROI gone? How do you sell your product, through systems integrators? What is the future hold for AI in manufacturing? One of my favorite quotes from our conversation: "If you don't want to make bad parts, just don't make bad parts" To find out more about Eigen Innovations, check them out. If you would like to reach out Scott, here is his LinkedIn. Enjoy the podcast. Regards, Jim BerettaCustomer Attraction Industrial Marketing & The Robot Industry Podcast Thanks to Scott and our partners, A3 The Association for Advancing Automation and PaintedRobot. If you would like to get involved with The Robot Industry Podcast, would like to become a guest or nominate someone, you can find me, Jim Beretta on LinkedIn or send me an email to therobotindustry at gmail dot com, no spaces. Our sponsor for this episode is Ehrhardt Automation builds and commissions turnkey automated solutions for their worldwide clients. With over 80 years of precision manufacturing they understand the complex world of automated manufacturing, project management, supply chain and delivering world-class custom automation on-time and on-budget. Contact one of their sales engineers to see what Ehrhardt can build for you at info@ehrhardtautomation.com Keywords and terms for this podcast: EIgen Innovations, Scott Everett, FLIR, Ehrhardt Automation Systems, #therobotindustrypodcast

AI Automation in the Restaurant Industry - CitC Episode 269

Health and Life Sciences at the Edge

Play Episode Listen Later Jan 6, 2022 16:41

Atif Kureishy, founder and CEO of Vistry, joins host Jake Smith to talk about deploying restaurant automation technology improve quality of service. Atif goes into detail about Vistry's Discrn platform, why the company extended Intel's edge insight for industrial software architecture to optimize workloads, and how his team uses the Intel Distribution of OpenVINO for faster insights and increased performance. For more information visit: https://www.vistry.ai Follow Jake on Twitter at: https://twitter.com/jakesmithintel

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Optimizing Medical Imaging at the Edge

Play Episode Listen Later Jan 4, 2022 18:57

More and more of today's medical imaging devices, such as CT, ultrasound, and MRI scanners, rely on real-time AI inferencing at the edge to make critical medical decisions while patients are being treated. Intel's Deepthi Karkada, a deep-learning software engineer, and Ryan Loney, Product Manager for OpenVINO™ spoke to Hilary Kennedy about recent trends in AI-based medical imaging and how Intel and its partners are helping identify and address the rapidly changing needs of this burgeoning industry.“Real-time medical imaging at the edge is important because it enables healthcare providers to get results from scans, run inferences, and make decisions about medical care at the patient's bedside,” says Looney. “Often these results need to be obtained and processed in two seconds or less.” Computing at the edge is not without its issues, however. Three of the major hurdles Intel and its partners routinely face are: limited memory in low-power devices, binary size, and latency. “Every megabyte counts when you're deploying on low-power medical devices with limited memory,” says Looney. “Analytics need to be run in as close to real-time as possible.“We know that AI and similar techniques are being adopted in the fields of medical imaging,” Karkada said. “These techniques include things like object detection and semantics segmentation. These techniques help radiologists quickly identify issues and result in many benefits. Many of our partners have been leveraging these advancements in these technologies.”“Intel offers a portfolio of hardware solutions targeted for AI inferencing,” Karkada said. “This includes solutions like the Intel Xeon® processors, core processors, and FPGAs, that our partners have been able to leverage. On the software side, our OpenVINO™ Toolkit provides accelerated inferencing solutions. These also take advantage of the hardware features, so they're tightly coupled and integrated.Learn more about AI and edge solutions for medical imaging, and other health and life sciences, by connecting with Deepthi Karkada and Ryan Loney on LinkedIn, or read more about Intel's medical imaging solutions online.Learn how to optimize a CT model using OpenVINO here: https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/110-ct-segmentation-quantize Hear some of our customer success stories here.Subscribe to the “Health and Life Sciences at the Edge” channel on Apple Podcasts, Spotify or Google Podcasts to hear more from the Intel Internet of Things Group.

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Bringing AI to the edge, from the comfort of your living room

The Stack Overflow Podcast

Play Episode Listen Later Dec 17, 2021 24:28

Bill gives an overview of edge computing and why it matters.His team wants to enable developers by democratizing access to AI. OpenVINO is an open-source toolkit for high-performing AI inference.DevCloud lets developers prototype, test, and run their workloads for free on Intel hardware and software. For more on OpenVINO, check out this example we shared that increases image resolution. Of course, we would be remiss if we didn't mention another way Intel is bringing its technology to developers: joining Collectives™ on Stack Overflow.

ai artificial intelligence comfort collective intel iot living room stack overflow edge computing openvino

Bringing AI to the edge, from the comfort of your living room

The Stack Overflow Podcast

Play Episode Listen Later Dec 17, 2021 24:28

Bill gives an overview of edge computing and why it matters.His team wants to enable developers by democratizing access to AI. OpenVINO is an open-source toolkit for high-performing AI inference.DevCloud lets developers prototype, test, and run their workloads for free on Intel hardware and software. For more on OpenVINO, check out this example we shared that increases image resolution. Of course, we would be remiss if we didn't mention another way Intel is bringing its technology to developers: joining Collectives™ on Stack Overflow.

ai artificial intelligence comfort collective intel iot living room stack overflow edge computing openvino

Episodio 57 - La mejor explicación de Blockchain y Token. Entrevista con María Milagros Santamaría, especialista que trabaja en uno de los proyectos más referente del mundo: OpenVino

Estrategia, Negocios y Finanzas

Play Episode Listen Later Dec 16, 2021 46:54

Una entrevista IMPERDIBLE en donde tendremos la mejor explicación de Blockchain y Token. En este episodio, entrevistamos a María Milagros Santamaría, especialista en el tema y que trabaja en uno de los proyectos más referente del mundo: OpenVino, un proyecto espectacular que nos muestra como es posible tokenizar la economía y todos los beneficios y ventajas que esto trae aparejado. María Milagros Santamaría, es Argentina, vive en Lisboa, Portugal y tiene 27 años. Es Abogada Corporativa en especialización en nuevas tecnologías (DLTs, Blockchain, Tokenización, etc.). Graduada en la Universidad de Mendoza (Argentina). Es también Docente, brindando clases en ADEN Business School en forma conjunta con la George Washington University en temas como Mercados Capitales, Planificación Fiscal Internacional y Contratos en la Era Global. Becaria de la Universidad de Buenos Aires e IALAB en el programa multidisciplinario de formación en inteligencia artificial. Es Abogada en Estudio Santamaría Abogados. Trabaja en asesoría legal en One Big Lab. Abogada en OpenVino.

Henrik Andersson, Instorescreen

Sixteen:Nine

Play Episode Listen Later Dec 15, 2021 35:00

The 16:9 PODCAST IS SPONSORED BY SCREENFEED – DIGITAL SIGNAGE CONTENT Retail experts have long spoke about the so-called zero moment of truth - that time in bricks and mortar stores when shoppers are in the aisles and making the decision about which product they're going to pull off the shelf and put in their basket. Getting digital signage into stores, with screens doing messaging when people are in a shopping mindset, has always been a big business driver. But putting screens right in the aisles has been a challenge for a few reasons - the main one being how conventional screens would eat up shelf space. Display manufacturing has advanced to a level now that it's possible to put strips of high resolution LCDs right on the shelf edge without getting in the way - introducing color, motion and the possibility for things like dynamic pricing. But the solution is not just the display. There has to be a whole system behind it, and that's where Instorescreen comes in. The Hong Kong-based company has a solution that actually meets the scaled needs of retailers and brands, so that you can do things like drive as many as 96 ribbon displays - with different content to each - off a single Lenovo PC. I had a good chat with Henrik Andersson, the CEO of Instorescreen. Subscribe to this podcast: iTunes * Google Play * RSS TRANSCRIPT Henrik, Thank you for joining me. We've spoken a few times in the past, but for those who are not familiar with Instorescreen, can you run through what your company does? What are you all about? Henrik Andersson: Yeah, So Instorescreen is a manufacturer of hardware, mostly monitors and technology for digital signage. We are 20 years old and today, an exclusive partner of Lenovo. It's a curious set up in that you're based in Florida, but you're Danish, I believe, and a lot of the company is over in Hong Kong, is that right? Henrik Andersson: Yeah. So our headquarters is in Hong Kong, and I'm very close to Danish. I'm Swedish... Ah okay, you're Nordic. Henrik Andersson: Yeah. So our headquarters is in Hong Kong. We have three manufacturing sites in China and yeah, that's what we are doing today. And is it privately held or are you publicly traded? Henrik Andersson: We are privately owned. One of the things that has struck me about what you do versu and what's historically happened in retail digital signage is, I would say the different waves of signage and retail have involved putting conventional flat panel displays all over stores, which was then followed by doing video walls instead hiving them all together, and the third wave seems to be now that the technology is there to try to put displays right in the aisles, right where consumers are making decisions, as opposed to just being part of the overall look and feel of a store. Is that kind of why you went on it the way you did? Henrik Andersson: Yeah. So the story is that Instorescreen is created to be a supplier that works outside in, instead of inside out. If I explain that very quickly, we come from true OEM manufacturing and we have been listening to the customer to see how we can make the right product for the customer in the right location? That has been the key. Inside out is more like if the customer calls in and you show them what you have, and we didn't want to work that way. So what we have done is that we have created different solutions that are OEM based, but we have based them on a whole, like retail. So for retail, we have been looking to see how we can replace or how we can add screens and technology into the retail environment. Based on that, we created shelf edge displays. We worked through the biggest manufacturer of LCD screens, and we have been working very closely with them to create the right size, length and height. When that's finished, we have a solution that could be on the shelf edge. It can be on the header and so on. The second step here is how are we going to drive them? What is the most intelligent way to drive them? And that's where it comes in with our solution, where we call it inDAISY, it's a data chain technology where we can utilize one 4K computer running up to 96 screens. Second generation that's coming next year, we'll also be able to push power through to the DAISY chain. So we will be able to push both power and data through one single cable. This is the partnership with Lenovo, and with the DAISY chaining, is it one signal to as many as 96 displays, or could it be addressable, like it could be 96 different signals? Henrik Andersson: It's 96 different signals. So each screen will get an ID, and based on that ID, you can have different content, so each screen would have different content. This wouldn't be 96 pieces of video, though, right? It would be images? Henrik Andersson: No, 96 pieces of video. Wow. That would take a pretty serious graphics card. Henrik Andersson: No, not really. Our data chain works as the way that you think about a canvas that's 4K and each ID is taking a spot from that canvas. So for example, if you have the header display that's 1920x360, the first header takes location 0 to 1920 down to 360, that's ID #1, ID #2 starts besides that and takes from 1920 to 3840 and down to 360, and then the shelf chassis starts below and they are taking left-right, left-right, and then by utilizing the Lenovo computer, we could have four 4K outputs so we can get four times that resolution. So with retail in the many years that I've been involved in this space, one of the challenges has been trying to get displays right into where the merchandise is. But the problem has always been that if you put a conventional flat panel display into that space, it's going to eat up merchandising space. It's gonna eat up the shelf space that you want for talking about the product. One of the big drivers here I assume is that this takes up space. That it's a way to not take away from that merchandising space and stockings space? Henrik Andersson: Yeah, we have been working very closely with the manufacturer of the gondolas to figure out how much space we can take without taking up on any merchandise. So we are taking up about one and a half inch to 1.7 inch in height, and then we are following the two foot three foot and four foot lengths. And this is using LCDs? Henrik Andersson: That's LCD, yes. And I gather that the reason you're able to do this now is you can now natively manufacture LCDs at these sizes? Henrik Andersson: Yeah, we don't use any resize. When we started this project like eight years ago, we used a resize to test and see how we can get it to look and how it should work. Today, we are natively producing them. There are benefits of natively producing them. One of the biggest is that you get the same every time. So if you put like 10, 15 of these side by side, you want all of them to have the same backlight. You want all of them to have the same color, of those kinds of features. And the biggest one is probably to get down in price. By utilizing a cut down like a 55 inch down to be making one shelf edge. That's a lot of waste doing that by using native screens. If the volume reaches X, we will be able to be very competitive. We are calculating, we should be able to go way below. A hundred bucks a foot. Yeah, because I remember when these thin ribbon LCDs first came out and I would see them at places like NRF, about six, seven years ago, the salespeople work in the boosts wouldn't even tell me a number in terms of price, because I gather it was ghastly, but that's changed. Henrik Andersson: That's changed a lot. For example, we could have a two foot display today for around 200 bucks. And who is putting that in? Is it the brands or is it the retail owners? Henrik Andersson: It's both. It's both. It has been the latest 4-5 years. It's a lot of brands. It's getting more retailers, and today, it's mostly retailers on end caps. And do they see this as part of their business model, their merchandising model that they'll sell end caps and now it's digital. Henrik Andersson: Yes, and that's information they see that they have, by just using packages, they cannot inform the customer of what the product is doing by utilizing video screens. Now they can inform me what's the benefit with this product and that product they can also do in different flavors. They can tease you by looking at how good this is with their eyes and so on, and one of the key things everybody's talking about right now is dynamic pricing. You will be able to change the pricing very quickly. You're able to change products on the shelves. You will be able to Collect external data. For example, if we say which employee has allergy medicine and so on, we can publish the pollen count onto the shelf fetch in real time. Are these replacements potentially for electronic shelf labels or are they kind of complimentary to them? Henrik Andersson: Today, it's a compliment. I can say that mostly due to the price, but as the price is still getting lower, I think they are direct competition to the ESLs, I think they are, because you have more dynamics on an LCD screen than you have on an ESL. With an ESL, you can do the price and maybe a barcode or something that's maybe two or three colors. That's about it, right? Henrik Andersson: Yeah, here you can have a full color spectrum. You can have movies, you can have touch screen functionality. There are so many things you can do. We can integrate the sensors so you can scan your membership and get your special price. There's so many things that we are investigating right now. What's going to be next? And doing that is contingent at all on the kind of back office systems that our retailer has as to whether they have the data and everything to make that? Henrik Andersson: Here is where we work very closely with a lot of partners that build softwares. So we worked with, for example, Microsoft, Oracle, all of them where they have the backend for the retailers, and then we were working with the digital signage companies, that's how we can get data between those two systems. Is that a challenge at all in terms of working with the different digital signage, CMS options out there that they need to have a platform that can work with this high-end Lenovo box? Henrik Andersson: No, it's not a super high end Lenovo box. It's a computer called P 340. That has an Nvidia board inside before 4K output. So a signage software will work with our solution and most of the times when we talked to a signage company, they found this complicated and it took them 15 minutes and said, oh, this is so easy. So yes the Daisy chain and all of that kind of feature sounds very advanced, but we made all the technology on our board. So the digital signage company doesn't have to think. That technology, they just have to follow publish on our full 4K cameras. I guess they would have to, depending on how their CMS works, maybe introduce some new resolutions that they didn't previously have, like 1920x360 or whatever you were describing? Henrik Andersson: No, they publish 3840x2160 full 4K resolution, and then our data chain board based on the IDs are taking spots from those full 4K canvas. What about LEDs? I have seen some manufacturers at trade shows again, who were showing shelf edge strips that were based on fine pitch LED. Is that a consideration or not the right way to go on this? Henrik Andersson: The problem we have with the LEDs is the heat. We have been investigating working with LEDs because there are benefits where you can easily make new sizes. We have to make a tool and new tooling costs about $1.5 to $2 million to make a new size. So if someone says, we don't want 3 feet, we want 3.2 feet. That's a very expensive thing. But in LEDs, it's doable. But we have power usage, it's almost 10 times more, and then we have the heat. So if we take a whole retail store and we put these LEDs out, it could be that you have to start getting more air conditioning units, basically. I never thought of it that way. Certainly think of all those LEDs, even though we all think of LEDs as being incredibly energy efficient, if you're using thousands of them in a whole store, maybe millions of them, and that's just a lot of little lights to feed. Henrik Andersson: They're made for outside. You could use them if you could spot the installations. I think they're fine. LCD is more energy efficient. The problem that I've seen with the LED versions is simply that to get the resolution, the granularity of the information down to a level that is legible like an ESL or an LCD is you're talking very fine pitch and it adds to the cost. Henrik Andersson: You cannot do it. So if we look at our header display, for example, it's 1920x360 in resolution. That means we have 360 pixels in height. If you go to an LED, you're down to maybe 30- 40 pixels. And the net result of that is the visuals just don't look very good, vright? Henrik Andersson: Yeah, I guess they will have a resolution of 150x30 or 150x40. Right now, our is 1920x360. So it looks like a 1994 desktop monitor? Henrik Andersson:It depends. From a distance, and if you do the content right, it will look quite okay. But if you go down to price tags and QR codes, coupons, things like that, they will never work. And we can do that as well. We can publish coupons and everything to the shelf edge. So maybe down the road 3-5 years after micro LEDs mass manufacturing gets sorted and the yields are up and everything else, maybe that's an option, but certainly not right now? Henrik Andersson: That's something we look into. We have really started looking at that, but it's way too early. What kind of research has been done to measure the impact of a planogram that's just conventional shelf labels and things like that, versus a portion of a planogram that has your digital shelf edge elements to it? Henrik Andersson: Yeah. So what we have seen now is that it's a wow factor. That's one of the things. If you walk in the store and you're making about 80% of your decisions in the store, and if you get a wow factor, you get something that triggers your brain, you will buy that product. On top of that, you have tools and gadgets, things that need to be explained. It would be like powered rails. So we say vitamins, anything that needs to be explained, an energy drink, those kinds of fine benefits. I like telling you that by using this product we give you these benefits. We are seeing between 20% to about 300% based on product. Sustained or just like when it first goes up? Henrik Andersson: It continues. We have some data from pharmaceuticals when they're explaining a product where we have 300-400% uplift, and we have also inside retail on produce and stuff like that. We have a huge growth. Are those brands the ones that have used other types of digital signage, like more conventional, flat panels around a store and maybe I assume it wouldn't have had anywhere near the impact, just because it wouldn't be as close to the product? Henrik Andersson: That has been a thing. They have advertised on digital signage screens in retail, but most of the time they are too far away from the product. So due to the impulse of buying. The further away you are from the physical product, the less sales are you going to make. One of the things that you were telling is your solution in tandem with Lenovo, your partner, you're doing in-store analytics as well? Henrik Andersson: Yeah, we have a solution that we are introducing at the NRF which we call smart vision. It's a full analytics platform utilizing Lenovo servers and multiple cameras to collect data from the retail environment. This is also applicable not only to retail we're doing even in transportation, education, fast food. It's about collecting data on how many people are happy walking in, or sad walking out, where they're walking. We can see the paths of walking. We can see where most people are spending most time, and how long they are standing in front of that product. We can also trigger things. We can see for example, that there has been a spell of a drink in aisle six, and we need to call the janitor to get that clean up. We are also working on things to see if they are putting things in their pocket, or they're putting things in the cart. We can see if someone is acting violent or has a tendency, if something could happen. This is what we work on. We'd like machine learning together with Intel to figure out what kind of information we want. So you're using Intel's OpenVINO? Henrik Andersson: Yes, we are using OpenVINO as the base. Retail analytics using computer vision has been around for 15 years, maybe even longer. So that part is not new. What's distinct about what you do versus some of the more familiar ones that are already known in digital signage? Henrik Andersson: It's probably our dashboard, an easy way to get an overview and also the flexibility to pick the things you want. We are trying to do the same here as we do with the screen work outside in, instead of inside out, we don't tell the customers that this is the data that we think you should have. We are asking them what data do you want to make your business better. Most of that is basically to combine multiple cameras, to get the whole view. Instead of having one camera inside of, by one header display by using this, we can see the moving paths in the store. We can see, for example, during X hours a day, we have this many visitors, but we only have this many cashiers open. Then they can move things around in the store to create something more streamlined. You want green lines across the whole store. You don't want to, like some aisles are more visited and otherized. You want all of them to move like a typical Ikea. Where you want to go, you have to go with the whole store, even if you want to get the thing at the end of the story. Yes, you do and it's not my favorite way to shop, but... Henrik Andersson: That's the way to create impulses on the way to the thing that you're intended to buy. Look at the carts at Ikea. You buy so many things on the way to the exit that you'd never planned to buy. The reference case that I'm familiar with for your company, is a seat to table store down in south Florida? Is that still your biggest deployment for this, or, where have you put your screens in? Henrik Andersson: That's the biggest single-store deployment. We are deploying in multiple stores, but often as a single end cap or category, and there will be a lot of announcements next year of full grocery stores that are getting this installed. More than just an end cap, but if it takes you to tape, for an example, we have about 200 screens in that store, including shell fetches, header, square screens. So that is an Intel Lenovo and initial screen show, and everybody's welcome to come down and look at it. So that's your living lab, or you can walk people through and go here's what's possible. Henrik Andersson: Yeah. So that's where we test everything from the analytics to the screens to do dynamic pricings, everything is tested there and that's better than having it in our own office. Lenovo is one of those very large computing companies that has been on the edge of digital signage and some of these companies like HP and so on, they're in they're out. You don't really know what they do, but it sounds like Lenovo has made a concerted investment of capital and people into the space. Henrik Andersson: Yes, Lenovo has grown a lot in the OEM division. I think when I started working with Lenovo OEM, there were about five guys. Now they're up to 50-60. And just working specifically with you or are they active in other areas as well? Henrik Andersson: Basically, it's the whole thing. If you're working outside in instead of inside out, trying to figure out solutions for each individual company. It could involve computers only or it could involve computers and monitors. One of the things we did in 2020-21 was a full line of monitors with anti-microbial coding on them. So they are like killing viruses and bacterias. But one of the key things as well is that the whole chassis is aluminum. So it's 95% sustainable. And is that an ask that you get from retail now? Henrik Andersson: Mostly Europe, because they don't want anything that has plastic in them anymore. That'll be a big change if it starts to happen here. Henrik Andersson: So if you go to a grocery store in Sweden, for example, you have to pay 50 cents for a plastic bag. That's what it cost. If you want to bring the groceries home, you have to pay 50 cents for the plastic bag. Yeah. That's starting to happen here in Canada as well. And I'm constantly buying more bags cause I forgot to bring the ones I have in the car. Henrik Andersson: Every Swedish guy has a car full of such bags. What do you see happening in the next couple of years with the kind of work that you do? Do you imagine there are going to be other companies developing copycat solutions? For instance, I was in Taiwan when we still could travel about two and a half years ago, and I know that AUO, which is a huge LCD manufacturer, has a whole feature wall of odd shaped ribbon displays and things like that, so it seems like this would be accessible to more accompanies now. Henrik Andersson: Yeah. So AUO is one of our partners. So if we look at a couple of their sites that they have, we have been part of their engineering process. We are being part of developing the size, the functionality, the backlight, all those kinds of things. So AUO is one we have HKC, we have BUE, we work with all of them. Will be the products similar to our products on the market. Yes, there will be. We are trying to be innovative. We are trying to make it easy. Most of our competitors are basically working as if each screen is an individual screen. They're using an Android board put in there and by using an Android board inside, you will be able to push one content to that screen. The problem you're going to face is if we put multiple screens up, for example, you have a limitation of how many units can be connected to a WiFi network. You would have a limitation of power plugs. You need so many power plugs to have power to each display. Think about the digital signage licenses. Now, this is nothing but fun for the signage company, if you have 3000 screens in a store and each screen has a built in a hundred players, that 3000 licenses. And also about servicing them, it should be easier to take one away, put one back, you know what a computer is, you have something that needs to be updated in one location, not 3000 locations. So in other words, you could source something like what Instorescreen has off of Alibaba or wherever you want to go. But the simple question that you would ask or somebody smart would ask or somebody else who's smart would ask is will it scale? And it just doesn't, as you just described. Henrik Andersson: No it doesn't, and to get it with the, know what we are able to today to have very smart servicing options. We have longtime warranties. We have technical people on 24x7 call. It's a disaster if a retail store shelf edge goes black. For example, we need to fix that very quickly and not call an Alibaba contact and you get a new screen in three weeks. Yeah. That doesn't work so well. All right. This was great. If people want to learn more about your company, where do they go online? Henrik Andersson: They can contact Lenovo OEM or go to lenovo.com or they can go to instorescreen.com. All right. Perfect. Thanks for your time. Henrik Andersson: Thank you very much.

Using AI for Digital Risk Protection - CitC Episode 262

conversations ai data cloud intel using ai computing jake smith zerofox digital risk openvino citc

Play Episode Listen Later Nov 11, 2021 15:09

James Carnall from ZeroFOX joins host Jake Smith to talk about AI-powered digital risk protection across the internet, including text, images and video, to identify threats ranging from deep fakes and fraud to potential cyberattacks. James explains why the ZeroFOX team worked directly with Intel for over a year to optimize their processes, such as improving inference performance with OpenVINO. James and Jake talk about how the rising volume of disinformation can have a negative financial impact on companies of all kinds and explain the limitations of relying on biometrics to thwart theft. For more information, visit: https://builders.intel.com/docs/aibuilders/zerofox-uses-intel-ai-technologies-to-protect-businesses-against-targeted-social-and-digital-attacks.pdf Follow Jake on Twitter at: https://twitter.com/jakesmithintel

AI-Assisted Annotation – Conversations in the Cloud – Episode 260

Intel Conversations in the Cloud

Play Episode Listen Later Oct 28, 2021

Helen Wang from Magic Data joins host Jake Smith to talk about the company's work in automatic speech recognition (ASR), text-to-speech (TTS), and natural language processing (NLP). Helen discusses the scalable capabilities Magic Data offers customers worldwide and goes into detail about how Intel engineers worked with Magic Data developers to optimize OpenVINO (often associated […]

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AI-Assisted Annotation - CitC Episode 260

Intel – Connected Social Media

Play Episode Listen Later Oct 28, 2021 11:29

Helen Wang from Magic Data joins host Jake Smith to talk about the company's work in automatic speech recognition (ASR), text-to-speech (TTS), and natural language processing (NLP). Helen discusses the scalable capabilities Magic Data offers customers worldwide and goes into detail about how Intel engineers worked with Magic Data developers to optimize OpenVINO—often associated with visual processing—for the company's language processing solutions. She also talks about the benefits of MagicHub: an open-source community with over 40 datasets available in dozens of languages to assist AI developers in model training. For more information, visit: https://magichub.com/ Follow Jake on Twitter at: https://twitter.com/jakesmithintel

conversations ai data cloud intel nlp computing assisted tts asr annotations jake smith openvino citc

AI-Assisted Annotation – Conversations in the Cloud – Episode 260

Play Episode Listen Later Oct 28, 2021

Helen Wang from Magic Data joins host Jake Smith to talk about the company's work in automatic speech recognition (ASR), text-to-speech (TTS), and natural language processing (NLP). Helen discusses the scalable capabilities Magic Data offers customers worldwide and goes into detail about how Intel engineers worked with Magic Data developers to optimize OpenVINO (often associated […]

conversations technology news data cloud computers practices intel nlp centers storage computing assisted data centers tts asr annotations sdi jake smith openvino

AI-Assisted Annotation – Conversations in the Cloud – Episode 260

Connected Social Media

Play Episode Listen Later Oct 28, 2021

Helen Wang from Magic Data joins host Jake Smith to talk about the company's work in automatic speech recognition (ASR), text-to-speech (TTS), and natural language processing (NLP). Helen discusses the scalable capabilities Magic Data offers customers worldwide and goes into detail about how Intel engineers worked with Magic Data developers to optimize OpenVINO (often associated […]

The Future of Robotic Process Automation - CitC Episode 257

conversations data cloud intel bots robotics computing robotic process automation jake smith robotic process automation rpa openvino citc

Play Episode Listen Later Sep 23, 2021 8:40

Soundar Rajan from Perpetuuiti Technosoft Services joins host Jake Smith to talk about software automation solutions for IT and business operations. Soundar goes into detail about Robotic Process Automation (RPA) with the company's Av3ar platform—a human-like AI+RPA platform of intelligent BoTs (or iBoTs) which can absorb, deconstruct, and use information as a human would to resolve problems. He also explains how OpenVINO is helping the company create new solutions and increase customer performance. More information available at: https://ptechnosoft.com/ Follow Jake on Twitter at: https://twitter.com/jakesmithintel

Embedded Executive: Raymond Lo, OpenVINO Evangelist, Intel

Embedded Executive

Play Episode Listen Later Aug 13, 2021 3:37

AI Day is right around the corner (on September 9). One of the sessions will cover how you actually build an AI platform. And to put our money where our mouth is, 16 lucky registrants will be selected randomly to receive a Topaz i7 platform from Simply NUC. In the session titled Hands-On Experience to Building Your First AI Solution Within an Hour, led by Raymond Lo, you will learn how to get an AI inference running lickety split using OpenVINO. Get more insight directly from Raymond in this week's Embedded Executives podcast.

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Using AI to Forecast Fashion in India - CitC Episode 245

director conversations data fashion product engineering cloud intel forecast using ai computing data centers gpus jake smith intel cpus sharath openvino citc

Play Episode Listen Later Jun 10, 2021 10:51

Sharath Puranik, Director of Product & Engineering at Stylumia, talks with host Jake Smith about how Stylumia leverages machine learning to improve product assortments, optimize inventory management, and offer a consumer-driven forecast to reduce waste in the fashion and lifestyle industry. Sharath explains why Stylumia became a part of the Intel AI Builders programs, which provided the support that allowed the company to transfer the majority of their models off more expensive and costly GPUs to more scalable Intel CPU architecture with the OpenVINO framework. Follow Stylumia on Twitter at: https://twitter.com/stylumia Follow Jake on Twitter at: https://twitter.com/jakesmithintel

Machine Vision Around the World - CitC Episode 242

Play Episode Listen Later May 25, 2021 20:03

Accubits’s Shameer Thaha joins host Jake Smith to talk about machine vision and predictive analytics. Shameer explains the use cases for the company’s Emotyx platform, such as real-time crowd analytics, people detection, counting, tracking, emotion detection, health care and more. Shameer goes into detail about the optimizations of the Intel Distribution of OpenVINO, using a single CPU system without GPU support at the edge, and some of Accubits’s projects around the world. Follow Shameer on Twitter at: https://twitter.com/shameerthaha Follow Jake on Twitter at: https://twitter.com/jakesmithintel

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Why is Open RAN So Important to the Mobile Industry? - CitC Episode 241

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Play Episode Listen Later May 20, 2021 11:42

TietoEVRY’s Mats Eriksson talks with host Jake Smith about the transformation of the mobile industry with Open RAN (Radio Access Networks) technology that aims to standardize networking industry interfaces and support interoperation between different vendors' equipment. Mats discusses the services TietoEVRY provides, the FlexRAN offerings with Intel, and optimizations with OpenNESS and OpenVINO. Mats explains why Amara's law might apply to the mobile industry and what that means for the global market. For more information about TietoEVRY’s vision for Open RAN, visit: https://www.tietoevry.com/openran Follow TietoEVRY on Twitter at: https://twitter.com/TietoEVRY Follow Jake on Twitter at: https://twitter.com/jakesmithintel

Hot AI Trends for 2021

ai artificial intel fish fry openvino

Play Episode Listen Later Jan 4, 2021 37:18

What’s next for AI and its cousins, deep learning (DL) and machine learning (ML)? Join us for a look ahead in the conversation between Ray Lo, an OpenVINO evangelist at Intel, and Kenton Williston, Editor-in-Chief of insight.tech. We explore up-and-coming applications like natural language processing (NLP), ways developers can strengthen their skill in AI, ML, and DL, and tips for creating ethical AI applications.

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AI for Everything!

Amelia's Weekly Fish Fry

Play Episode Listen Later Nov 20, 2020 15:29

Artificial intelligence and machine learning take center stage in this week’s Fish Fry podcast. First, we take a closer look at how a new algorithm called ART (Automated Recommendation Tool) is ushering in a new age of enlightenment in the world of synthetic biology. We investigate how this revolutionary new algorithm was tested and what it means for the future of bioengineered cells. Aaron Tersteeg (Intel) also joins us this week to discuss Intel’s OpenVINO tool kit. Aaron and I chat about the biggest AI inferencing challenges facing us today, the details of the OpenVINO “write once, deploy anywhere” approach, and what you should keep in mind when starting a new AI project.

Using AI Sense to Stay Safe During a Pandemic – Conversations in the Cloud – Episode 214

Connected Social Media

Play Episode Listen Later Nov 19, 2020

In this Intel Conversations in the Cloud audio podcast: Alok Mishra, founder of Wesense, joins host Jake Smith to talk about how the company, in partnership with Wipro, developed Clearhealth—a safety compliance product for COVID-19 in India that combines touch-free attendance, temperature checks, sanitization compliance, and mask protection compliance for offices and retail locations. The two talk about the importance of technology helping solve emerging problems and how Wesense improved inference time using Intel optimized TensorFlow, Intel Distribution of OpenVINO, and Intel Distribution for Python. Follow Wesense on Twitter: twitter.com/wesenseai Follow Jake on Twitter: twitter.com/jakesmithintel

covid-19 conversations ai social marketing technology pandemic media brand microsoft podcasting security podcasters engagement corporate cloud seo sense intel blogging sem python using ai stay safe computing data centers syndication tensorflow wipro jake smith openvino intel conversations intel distribution

Using AI Sense to Stay Safe During a Pandemic – Conversations in the Cloud – Episode 214

Intel Conversations in the Cloud

Play Episode Listen Later Nov 19, 2020

In this Intel Conversations in the Cloud audio podcast: Alok Mishra, founder of Wesense, joins host Jake Smith to talk about how the company, in partnership with Wipro, developed Clearhealth—a safety compliance product for COVID-19 in India that combines touch-free attendance, temperature checks, sanitization compliance, and mask protection compliance for offices and retail locations. The two talk about the importance of technology helping solve emerging problems and how Wesense improved inference time using Intel optimized TensorFlow, Intel Distribution of OpenVINO, and Intel Distribution for Python. Follow Wesense on Twitter: twitter.com/wesenseai Follow Jake on Twitter: twitter.com/jakesmithintel

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Using AI Sense to Stay Safe During a Pandemic - CitC Episode 214

conversations ai internet data artificial intelligence intel platforms mri internet of things deep learning edge computing crowell intel corporation ge healthcare global lead federated learning marketing global openvino

Play Episode Listen Later Nov 19, 2020 14:06

Alok Mishra, founder of Wesense, joins host Jake Smith to talk about how the company, in partnership with Wipro, developed Clearhealth—a safety compliance product for COVID-19 in India that combines touch-free attendance, temperature checks, sanitization compliance, and mask protection compliance for offices and retail locations. The two talk about the importance of technology helping solve emerging problems and how Wesense improved inference time using Intel optimized TensorFlow, Intel Distribution of OpenVINO, and Intel Distribution for Python. Follow Wesense on Twitter: https://twitter.com/wesenseai Follow Jake on Twitter: https://twitter.com/jakesmithintel

covid-19 conversations pandemic data cloud sense intel python using ai stay safe computing data centers tensorflow wipro jake smith openvino citc intel distribution

5. AI's Role in Cyber Security

Cyber Security Inside

Play Episode Listen Later Nov 4, 2020 24:53

On today's show our guest is Bob O'Donnell. Bob is President and Founder and Chief Analyst at TECHnalysis Research. He's widely regarded as an expert in the technology market research field and his original research and advice is used by executives and large technology firms all over the world. I'd like to introduce my co-host Camille Morhardt. So hi, Camille, how are you doing today? Camille Morhardt: Hey Tom. I'm doing great. Tom Garrison: So what's on your mind today? Camille Morhardt: Well, I know this sounds like a big topic. I was going to say artificial intelligence and compute. Tom Garrison: Wow. Camille Morhardt: But I wanted to start with something a little bit smaller: end devices. So when I think about the evolution of AI, the smartphone, particularly, with its built-in camera kind of gave deep learning such a boost. And then when I think about when I know what I'm going to do, and I need to sit down and get something done, I still go to my PC. So, what I'm wondering is when I think of the development of AI, it's kind of through the smartphone as this end device. And then of course, servers on the backend for centralized learning models. And then when I think about the future, I tend to think IOT, preventive, maintenance and exciting things like that. But what about this basic workhorse that is the PC? What's happening with respect to artificial intelligence and the PC Tom Garrison: Yeah, there's a lot to unpack there. In general, there's some pretty cool things about AI. Some of them sound boring, but they're, they're actually pretty game-changing and one of them sort of boring sounding ones is using AI to basically guess what you're about to do on the PC. So if, for example, you're working away in Microsoft Word, and you've been going at it for a while typing, and then you pause for a moment and you start to move the mouse up, chances are you're, you're either going to be clicking on Save, or you're going to be clicking on Print or something like that. And using AI based on your, the things that you do--without even thinking about it--you can use AI to guess what you're about to do, and then make those actions something that's basically one click away or something that's just right there on the screen. And it's kind of invisible to the user, but it gets us out of having to remember “which dropdown box do I have to click on this and then that.” And you know, like if in Excel, I don't know how many times in Excel I have tried to find the dang “wrap text,” little check box. Those are all things where AI can watch your behavior over time and learn your behavior and then sort of present the things that you're likely to do in a very easy to find mechanism. Camille Morhardt: Okay. So you're talking about, you know, basic sort of workload, help my life get better kind of a thing. So what about on the security front? Is there anything that we're seeing there? Tom Garrison: Yeah. So the first one was just one sort of simple example. And then on the AI side for security what's being looked at now is around using AI to see is the machine operating in a way that it doesn't normally operate. So knowing enough about the way you use your device, to be able to say, “huh, now I, the PC, and operating in a way I don't normally operate” and flagging that. Doing that in a way that doesn't induce a lot of false positives (or obviously false negatives too) but false positives are a real problem for security, because if you are sort of Chicken Little, and you're always raising your hand saying, “Oh, there's a problem! Oh, there's a problem!,” then pretty soon people start ignoring you. And so the, the promise of AI is to be able to do that and see these anomalous behaviors that you should flag. Camille Morhardt: I would like to learn a little bit more about that and find out what other people in the industry are seeing. Tom Garrison: Yeah. I think that's probably a great podcast right there. What, what do you say we narrow in on that topic? Camille Morhardt: Yeah, I like it. Tom Garrison: All right, let's go for it. Okay on today's show our guest is Bob O'Donnell. Bob is President and Founder and Chief Analyst at TECHnalysis Research. He’s widely regarded as an expert in the technology market research field and his original research and advice is used by executives and large technology firms all over the world. So Bob, you are the perfect guest for us today. So thank you and welcome to the show. Bob O’Donnell: Thanks for having me. Tom Garrison: So our topic today is around Artificial Intelligence. And I wonder if you could just spend a moment and talk a little bit about your background and this topic around AI. Bob O’Donnell: Sure. So I have been a tech industry analyst for a little over 20 years. And prior to that, I was in the music technology business--so writing and reading and playing with musical equipment (because I'm a musician for fun, as well). But so I've been following tech industry trends for a long time. And as we've seen the evolution of computing, we've seen the development of more sophisticated software tools along with more sophisticated silicon and those worlds kind of really coming together in a very interesting way with Artificial Intelligence. The idea being that you could start to see the ability to do things above and beyond what basic software would allow and enable, and then unique means of solving problems and then silicon being designed to accelerate that, cause it turns out not all, everything would just be accelerated by a CPU. But long story short is as I've tracked these trends in devices and core technologies and software in the cloud, AI has all of a sudden become this huge issue. And I've done some independent research studies on it, I did a survey of AI use in the enterprise. I've done research on AI and consumer applications gaming and so it's just an area that I've looked at quite closely, because there's so much interest in fascination with it. Of course there's so many different variations on it between machine learning and the different flavors of AI. And it gets very confusing very quickly, certainly, but at the end of the day, it's about being able to extend some of the core, basic types of software tools that we've created in ways that we may not have thought of before. And it's also a way, frankly, from another perspective, it's a way to make sense of data in a manner with which we haven't thought about it before. So it's a combination of how do you create these algorithms? how do you interpret this data? and how do you put that all together into something that goes above and beyond what we've traditionally done? And it's a fascinating field, obviously, that has lots of implications all over the place. Tom Garrison: Yeah, no, this is, this is a great, and, and I wonder through the research that you've done--and I understand you've got a white paper coming out as well--for the listeners here, what are some of the key sort of “ahas” or takeaways from your research? Bob O’Donnell: Initially all the excitement, frankly, and all the action in AI was happening on smartphones, right? It was all about smartphones. A lot of it was we heard about computational photography, the ability to enhance image quality and do, uh, very clever processing in ways above and beyond what you could do with the traditional Photoshop filter types of things. And then we saw audio processing, as well, as some other things. But the PC was a little late to the game. And now what we're starting to see--and what my research is on--is about AI usage on PCs. We're starting to see PCs be part of the equation. We're seeing a lot of adoption of AI in various PC applications. 90% of PC developers that we surveyed are working on some sort of AI machine learning or deep learning type of effort--either by integrating into a function within their application or building entirely new applications based on that. So that's huge, right? That's a huge amount of focus being placed there. And at the same time, we've also seen of course, a lot of effort around both companies like Intel, as well as NVIDIA and others to build algorithms and software development kits that can leverage that and to build acceleration into some of the chips that they're creating. So, I mean, everybody is really focused on trying to bring some of that magic that we saw with smartphones a couple of years back to the PC, because there's a lot of interesting applications, especially nowadays when we're all using our PCs a heck of a lot more. Camille Morhardt: Hey Bob, what is kind of one of the major use cases that people are actually doing with AI on a PC? Bob O’Donnell: There's a number of things. So we are seeing some of the same kinds of things we saw in smartphones. We're seeing some of the filters, you know, for image filtering and audio filtering, especially now with video conferencing, noise reduction in the background is a huge deal, right? Because we've all had dogs and kids and, you know, loud noises happening in the background. The other thing we've seen, actually, is workflow automation, processes totally radically different kind of thing, but using tools to leverage how data workflows are happening or process workflows. All those kinds of tools that are run on PCs are also changing.Also a lot on security and threat protection. We're seeing more and more automated tools to look for security threats. You know, a lot of what AI does at a simplistic level is it Looks for patterns, right? You teach it a bunch of patterns--a lot of these AI algorithms--and then from that, it can determine other patterns. That's a classic, deep learning application. It was initially, you know, it was show 50 pictures of, uh, of, of dogs and then show some more pictures that they haven't been trained on and decide if it's a dog or not. Well, take that a million times further, here's a signature or here's an application that's functioning in an unusual way on a PC, could that potentially be a security threat? And so you'll see a lot of AI based tools around security and threat protection also being used. Camille Morhardt: Who's owning those models, then? If we're doing AI on the PC and looking for threat protection, in particular, I guess maybe, you know, is that the IT department who's owning the takeaways from that? or are there managed service providers that are collecting that? Bob O’Donnell: I think we're seeing all of the above. Obviously in a lot of corporate environments, and even in our extended corporate view of the world with a work from home, IT shops will install, obviously, a number of security tools--there's the traditional MacAfee, Symantec types of things. There's obviously what Microsoft has done with Defender. But there's more advanced other technologies we've seen from Cylance and some of these other companies--some of whom have been purchased by some of the big PC vendors. But there's a number of tools being deployed, sometimes by corporate IT, sometimes by individuals because, you know, the boundaries between personal and work of course have completely been obliterated during the pandemic. And so you have people working on personal PCs and they're installing those kinds of tools there. But you also, in fact, have service providers, uh, who are involved with this at a corporate level. You've got people who provide a managed security type services that are watching what goes in and out, past the firewall. Again, things are very different now because whereas everything used to be behind the firewall, now, literally everything is outside the firewall and that's changed the dynamic of what the things you have to look for, the types of threats. So there's all kinds of services being offered from a variety of vendors. You're seeing it as well in network equipment, from the large networking companies. So folks who are in charge of the network at many organizations as a part of IT they might be monitoring. Um, so it's being approached and attacked on many different levels with AI being applied to almost all of these different security applications. Tom Garrison: So do you see Bob then that the AI is basically just being integrated into many of the sort of existing products that are out there? And it just makes their products better? Bob O’Donnell: It is. It's a good question, Tom. And yeah, I mean the bottom line is a lot of what's happening is not necessarily that the entire-- I mentioned that some people are trying to do entirely new apps with AI. But the vast majority of what's happening is they're taking a function or two, and they're integrating AI into that. Or they're building a couple of special new features and capabilities leveraging AI models or deep learning or what have you. So that's typically the way that we're seeing, developers on the PC, as well as other platforms do that, right? We saw the same thing on smartphones. There were always photo apps and camera apps on smartphones, but they just got a little bit smarter through the integration of some of these technologies. And frankly, in the case of smartphones, Qualcomm had a bunch of software development kits and APIs and things like that, along with Android and the two worked together to create a suite of tools that developers could use. Now, we're seeing the same thing with Intel doing that with OpenVINO on the PC side, as well as Microsoft. So there's a lot of efforts. And then of course there's, you know, and then special instructions being integrated into the latest generation of CPU's again from Intel as well as from AMD. So lots of different parties working together to bring AI more to the mainstream. Tom Garrison: We're certainly doing a lot of work in the hardware side, making sure that our platforms are, uh, highly performant doing AI type workloads. I wonder, from your perspective, is there anything that really has caught your imagination? Cause I'm envisioning now our listeners are listening to this podcast saying how is AI gonna impact my business? Bob O’Donnell: Well, I think it's going to happen across a number of areas. Sort of a big picture one is around analytics. You know, we've talked about analytics and big data in the corporate world for, I dunno, 10, 15 years. It seems like forever. And the reality is that a lot of the initial analytics efforts, frankly, were not very successful. They were trying to dive into big chunks of data and try and discover patterns and, and they really weren't particularly successful in doing so. The beauty of AI is you're unleashing algorithms onto these huge datasets and they are finding more success. So I think anything that involves traditional analytics types of applications, where you're searching for patterns in data--and that can happen across any industry and we're seeing that all kinds of places. We're also happening, see it happening in IOT tape type applications. If it's in manufacturing, you know, predictive analytics where you can not only be, you know, searching for data, but you can see patterns start to emerge of sensor data that might make you say, ”Oh, I think that piece of equipment is going to fail. We've got to deal with that.” We're starting to see that as well on PCs, right? I mean, it was back from the old days of smart hard drives, right, where you have these sort of basic tools built into the hard drive, they would try and be able to warn you, “Hey, I think we're in trouble here.” Now we've got the same kinds of things happening on other components, right?--whether it be memory or other elements of a PC. So we're seeing those, that predictive analytics happening. The other big area, frankly, than I think most people are starting to see is in basic office productivity. So now, for example, if you use your, either Office 365 or G Suite, or is now Google calls it Google Workspaces, you've got these tools, the editing applications that give you content recommendations, right? They'll say, “Hey, not only is it a spell checker, it's a grammar checker. Now it's even a content type of checker. Here's some suggested content for you.” One of the things I love in PowerPoint is a feature called Designer and Designer is an AI powered function that will create layouts for you. If you don't have your own in-house art department who designs all your slides, you've got to create your own. And even if you have a preset template that a lot of companies have, you still want to jazz it up and create some varieties and do some cool things with images. And the beauty of Designer is it can take some images and come up with some suggested layouts that look awesome and require very little effort on your part. We're seeing things like the ability in video conferencing applications to track someone if someone's walking around, uh, or they're swaying, the camera can track the person and keep them centered in the frame. Uh, so all kinds of subtle-- and that we've also seen things like, you know, A little creepy, but you know, they raise your eyes up so it makes you look like you're actually looking at the person instead of looking down. Cause you know, a lot of times your camera's above your screen, so you really looking up, but sometimes you're looking down at the people you're talking to. And so it's a little weird. So it literally just tweaks the position of where your eyeballs are looking to make it feel like someone's actually looking at you as they're talking to them in a Zoom call. So like I said, all kinds of different real world applications that I think pretty much everyone has started to see and there's creeping their way into the mainstream. Camille Morhardt: Okay. So you've used the word “creepy” and “creeping” a couple of times. So I'm going to run with that just a little bit. What are we worried at all about privacy when we've got all of this kinds of tracking and voice, and now content suggestions? I won't even go there? Bob O’Donnell: Yes. Look, people are a little worried about it, right? Analytics, one of the, one of the analytics that people are doing is personal analytics, as in it's tracking everything I do and then making suggestions on what I want, right? We've seen this with advertising. We see this with all kinds of things and so yes, there is obviously some concern with that. The beauty of what's happening is we are now getting the intelligence and the compute power to do what's called Inferencing, locally. So, you know, the idea you've got training and inference when it comes to AI training is when you take a whole bunch of data and you create these algorithms by essentially training it what to look for, what to think of that's classic machine and deep learning types of algorithms. Then you apply those and you do inference by taking input and comparing it essentially to the algorithm and figuring it out. Now in the past, you used to have to do that inference in the cloud, meaning everything you did had to be sent to the cloud, to someone else's data center and the data was processed there. By doing it locally--even though that sounds like sort of an arbitrary distinction--it's huge because it means all of a sudden, all of that inference work looking at my own data or your own data who's ever owned data happens on the local device. So all of a sudden that means my data isn't necessarily being shared out to the entire world and that makes a big difference to people, as well. They want the benefits of smart suggestions and content suggestions, all this kind of stuff. But, you know, they don't necessarily want their entire life out there, for the world to analyze. That's what I'm referring to there. But it's an excellent question and something that we do have to be aware of whenever it comes to AI. Camille Morhardt: So just to clarify, you're saying, for example, if we're going to work on removing background noise in my audio on a video call, you can make a suggested edit to the algorithm and then send that back to the model, as opposed to sending, say, my raw audio file, which would include the specifics of my conversation? Bob O’Donnell: That's exactly right. And so, first of all, they can do the analysis of that audio file, locally. But what they can also do is they can maybe come across a variation that occurred in your particular situation or someone else's particular situation, upload that data, in turn, refine the algorithm, and then that algorithm in turn gets re-downloaded onto your system. So it's a constantly iterating type of process. That's the ideal. We're not always, we're not quite there yet in all cases, but that's the concept is that you can get the benefits of AI, you can even get the benefits of an upgraded algorithm, without having to share too much of your own personal data. Tom Garrison: We're starting a new segment. So you're the very first one of a brand new segment that we're doing in our podcast now. And it's basically what have you learned lately that you want to share with the podcast? Something cool, interesting. Could be something related to technology or it could be something in entertainment or something else you found intriguing and, I think, maybe our listeners might learn something from it as a result. Bob O’Donnell: Well, I have two things and they're radically different, but I'm going to throw them out there anyway. So recently one of my personal musical heroes passed away and that was Eddie Van Halen. I discovered Van Halen--I'm showing my age here--but at a young age and he has always been an amazing rockstar and just such an icon to me. An interesting factoid that came out after his death that I never knew is that he was part Indonesian. He was actually part Asian. And he actually suffered a great deal of bigotry for being Asian. I never ever knew that. So that was an interesting little factoid, about Eddie van Halen, The other thing, and it's again, totally unrelated, one of the things I've been doing with a little extra time during the pandemic is I-- I'm a car guy and I have a few car Lego sets and I've discovered that there are lighting sets. You can put lights into your Legos. And so you can turn on the lights on your legos. It's super cool. It's a totally nerdy geeky thing that not everybody's going to appreciate, but if you're into stuff like that, there are lighting sets. Super cool!, Tom Garrison: I, you know, I, I didn't know either of those two, but, uh, the Lego one that is a, that is intriguing. (laughs) Camille, any, uh, items you want to add? Camille Morhardt: Okay, well, what I learned this last week, probably anybody who spends time by the ocean already knows, but, uh, I learned that the best time to boogie board is not exactly at low tide, which I had previously thought, but it's right after low tide when all the water is pushing you on shore, as opposed to dragging you out with that rip. Bob O’Donnell: That would be an important thing to learn! (laughs) Camille Morhardt: (laughs) Trial and error. Bob O’Donnell: What about you Tom? Tom Garrison: I am going to go into the world of entertainment. I'm always a big fan of these shows that I can just binge watch. And my son turned me on to a new show called “The Boys.” And let me just first tell everybody out there, do not watch this show with kids around. It is completely, completely inappropriate for kids. But it's a world where there are superheroes, but they're self-interested superheroes. They're not like the Superman or Batman that we grew up with that are all about the public good. These people are in it for themselves. And, anyway, it's, uh, it's a fascinating to me. It was a fascinating kind of re-think about the whole superhero genre thing. I think it's very well done. There's two full seasons. Now you can get on it. But anyway, Bob, thank you again for taking the time stopping by, sharing what you know about AI. It was really interesting. And I appreciate your time. Bob O’Donnell: Well, thanks, Tom. And thanks Camille, thank you so much for having me. I really enjoyed the conversation. Tom Garrison: All right. And for all of our listeners, we look forward to sharing with you the next podcast, which will come out in two more weeks and we'll see you then Subscribe and stay tuned for the next episode of Cyber Security Inside. Follow at @tommgarrison on Twitter to continue the conversation. Thank you for listening. .

Conversations With Dez - with Alexis Crowell, IOT Marketing Global Lead, Data Platforms Group, Intel

Conversations with Dez

Play Episode Listen Later Sep 21, 2020 31:58

I caught up with with Alexis Crowell, IOT Marketing Global Lead for Data Platforms Group at Intel Corporation, to talk about the latest news, trends, insights and offerings from Intel in the Internet of Things, Artificial Intelligence, and Edge market sectors globally. Our conversation kicks off with Alexis sharing some fun anecdotes and insights into her early life, her academic and working career path, and how she came to be with Intel and her amazing role. Alexis then gives us an amazing 30,000 foot view outline of what Intel is seeing regarding current macro trends around AI at the Edge, with some of the current macro trends regarding AI at the Edge. In particular we delve into some of the challenges Alexis sees as being the next frontier of enterprise transformation, how Data-driven experiences – AI from data centers, to software, to outer edges of the networks, and how Data and compute closest to the point of interaction will transform data driven decision making, and some of the challenges around bridging people, business and things for enhanced experiences, and what it takes to offer improved automation and cost savings. We then delve into work Intel are doing currently and Alexis offers us a view of some of the trends across various markets regarding adoption, challenges and opportunities with AI at the Edge. Specifically we discuss enterprise adoption and the need for Edge Computing, the need for actionable insights. We also discuss challenges presented by issues such as network bottlenecks, latency, and the mounting issues raised by increasing demand for bandwidth and ever increasing network demands as devices continue to generate increasingly vast volumes of data, increasing needs for full end-to-end infrastructure and designs, comprehensive security, data regulation, and overall cohesive management of all of these environments and systems / networks / platforms and more. Alexis walks us through Intel’s customer approach as far as how organisations should go about turning data into actionable insights, some of the challenges around turning data into action, how Intel's Gen 3 Intel Movidius VPUs and Intel Scalable Processor platforms are helping with these challenges - where solutions like OpenVINO are helping. We also discuss the latest news around Intel AI Builders, and Intel Selection Solutions for AI, about Federated Learning, and Alexis shares a recent related customer story around GE Healthcare and work they are doing with medical data, imaging and analytics to process data from MRI machines, and where Deep Learning is playing part in this success story. We wrap up with Alexis sharing her thoughts and advice around what decision makers be considering in their approach to leveraging “AI at the Edge” over the next 12 to 18 months. Tune in now for all of these amazing topics and more. This podcast was made in partnership with Intel. For more information please visit: - Intel IoT Solutions web portal: https://bit.ly/2EjyP1i - Intel Xeon® Scalable processors: http://intel.ly/2wNTV3Q - Intel Atom® P processors: intel.ly/3aNHDqS - 5G Technology Overview: intel.ly/39NfMHb #sponsored #intelinfluencer .

TWiET 409: IoT It! - Moving IoT from hobby to the enterprise

This Week in Enterprise Tech (Video LO)

Play Episode Listen Later Sep 5, 2020 72:23

Apple to delay privacy change threatening Facebook, mobile ad marketDHS partners with industry to offer cybersecurity aidFeds can't ask Google for every phone in a 100-meter radius, court saysEFF on the Digital Services Act: Put Users in ControlMost IoT hardware easy to crackiOS 13.7 launches with Exposure Notification ExpressCOVID Tracing framework privacy busted by BluetoothPay at the pump with AlexaWorking smarter, not harder for cybersecurity teamsAlexis Crowell, Intel's IoT Marketing Global Lead talks about IoT opportunities for enterprise and what is OpenVINO? Hosts: Louis Maresca, Brian Chee, and Curt Franklin Guest: Alexis Crowell Download or subscribe to this show at https://twit.tv/shows/this-week-in-enterprise-tech. Sponsors: WWT.COM/TWIT itpro.tv/enterprise use code ENTERPRISE30 canary.tools/twit - use code: TWIT

google apple moving hobbies cybersecurity intel enterprise iot bluetooth gas station eff twit contactless payments openvino sponsors wwt brian chee

TWiET 409: IoT It! - Moving IoT from hobby to the enterprise

This Week in Enterprise Tech (Video HD)

Play Episode Listen Later Sep 5, 2020 72:23

Apple to delay privacy change threatening Facebook, mobile ad marketDHS partners with industry to offer cybersecurity aidFeds can't ask Google for every phone in a 100-meter radius, court saysEFF on the Digital Services Act: Put Users in ControlMost IoT hardware easy to crackiOS 13.7 launches with Exposure Notification ExpressCOVID Tracing framework privacy busted by BluetoothPay at the pump with AlexaWorking smarter, not harder for cybersecurity teamsAlexis Crowell, Intel's IoT Marketing Global Lead talks about IoT opportunities for enterprise and what is OpenVINO? Hosts: Louis Maresca, Brian Chee, and Curt Franklin Guest: Alexis Crowell Download or subscribe to this show at https://twit.tv/shows/this-week-in-enterprise-tech. Sponsors: WWT.COM/TWIT itpro.tv/enterprise use code ENTERPRISE30 canary.tools/twit - use code: TWIT

google apple moving hobbies cybersecurity intel enterprise iot bluetooth gas station eff twit contactless payments openvino sponsors wwt brian chee

TWiET 409: IoT It! - Moving IoT from hobby to the enterprise

This Week in Enterprise Tech (MP3)

Play Episode Listen Later Sep 5, 2020 72:23

Apple to delay privacy change threatening Facebook, mobile ad marketDHS partners with industry to offer cybersecurity aidFeds can't ask Google for every phone in a 100-meter radius, court saysEFF on the Digital Services Act: Put Users in ControlMost IoT hardware easy to crackiOS 13.7 launches with Exposure Notification ExpressCOVID Tracing framework privacy busted by BluetoothPay at the pump with AlexaWorking smarter, not harder for cybersecurity teamsAlexis Crowell, Intel's IoT Marketing Global Lead talks about IoT opportunities for enterprise and what is OpenVINO? Hosts: Louis Maresca, Brian Chee, and Curt Franklin Guest: Alexis Crowell Download or subscribe to this show at https://twit.tv/shows/this-week-in-enterprise-tech. Sponsors: WWT.COM/TWIT itpro.tv/enterprise use code ENTERPRISE30 canary.tools/twit - use code: TWIT

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This Week in Enterprise Tech 409: IoT It!

All TWiT.tv Shows (MP3)

Play Episode Listen Later Sep 5, 2020 72:23

Apple to delay privacy change threatening Facebook, mobile ad marketDHS partners with industry to offer cybersecurity aidFeds can't ask Google for every phone in a 100-meter radius, court saysEFF on the Digital Services Act: Put Users in ControlMost IoT hardware easy to crackiOS 13.7 launches with Exposure Notification ExpressCOVID Tracing framework privacy busted by BluetoothPay at the pump with AlexaWorking smarter, not harder for cybersecurity teamsAlexis Crowell, Intel's IoT Marketing Global Lead talks about IoT opportunities for enterprise and what is OpenVINO? Hosts: Louis Maresca, Brian Chee, and Curt Franklin Guest: Alexis Crowell Download or subscribe to this show at https://twit.tv/shows/this-week-in-enterprise-tech. Sponsors: WWT.COM/TWIT itpro.tv/enterprise use code ENTERPRISE30 canary.tools/twit - use code: TWIT

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TWiET 409: IoT It! - Moving IoT from hobby to the enterprise

This Week in Enterprise Tech (Video HI)

Play Episode Listen Later Sep 5, 2020 72:23

Apple to delay privacy change threatening Facebook, mobile ad marketDHS partners with industry to offer cybersecurity aidFeds can't ask Google for every phone in a 100-meter radius, court saysEFF on the Digital Services Act: Put Users in ControlMost IoT hardware easy to crackiOS 13.7 launches with Exposure Notification ExpressCOVID Tracing framework privacy busted by BluetoothPay at the pump with AlexaWorking smarter, not harder for cybersecurity teamsAlexis Crowell, Intel's IoT Marketing Global Lead talks about IoT opportunities for enterprise and what is OpenVINO? Hosts: Louis Maresca, Brian Chee, and Curt Franklin Guest: Alexis Crowell Download or subscribe to this show at https://twit.tv/shows/this-week-in-enterprise-tech. Sponsors: WWT.COM/TWIT itpro.tv/enterprise use code ENTERPRISE30 canary.tools/twit - use code: TWIT

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This Week in Enterprise Tech 409: IoT It!

All TWiT.tv Shows (Video HD)

Play Episode Listen Later Sep 5, 2020 72:23

Apple to delay privacy change threatening Facebook, mobile ad marketDHS partners with industry to offer cybersecurity aidFeds can't ask Google for every phone in a 100-meter radius, court saysEFF on the Digital Services Act: Put Users in ControlMost IoT hardware easy to crackiOS 13.7 launches with Exposure Notification ExpressCOVID Tracing framework privacy busted by BluetoothPay at the pump with AlexaWorking smarter, not harder for cybersecurity teamsAlexis Crowell, Intel's IoT Marketing Global Lead talks about IoT opportunities for enterprise and what is OpenVINO? Hosts: Louis Maresca, Brian Chee, and Curt Franklin Guest: Alexis Crowell Download or subscribe to this show at https://twit.tv/shows/this-week-in-enterprise-tech. Sponsors: WWT.COM/TWIT itpro.tv/enterprise use code ENTERPRISE30 canary.tools/twit - use code: TWIT

google apple cybersecurity intel enterprise iot bluetooth gas station eff twit contactless payments enterprise tech openvino sponsors wwt brian chee

This Week in Enterprise Tech 409: IoT It!

All TWiT.tv Shows (Video HI)

Play Episode Listen Later Sep 5, 2020 72:23

Apple to delay privacy change threatening Facebook, mobile ad marketDHS partners with industry to offer cybersecurity aidFeds can't ask Google for every phone in a 100-meter radius, court saysEFF on the Digital Services Act: Put Users in ControlMost IoT hardware easy to crackiOS 13.7 launches with Exposure Notification ExpressCOVID Tracing framework privacy busted by BluetoothPay at the pump with AlexaWorking smarter, not harder for cybersecurity teamsAlexis Crowell, Intel's IoT Marketing Global Lead talks about IoT opportunities for enterprise and what is OpenVINO? Hosts: Louis Maresca, Brian Chee, and Curt Franklin Guest: Alexis Crowell Download or subscribe to this show at https://twit.tv/shows/this-week-in-enterprise-tech. Sponsors: WWT.COM/TWIT itpro.tv/enterprise use code ENTERPRISE30 canary.tools/twit - use code: TWIT

google apple cybersecurity intel enterprise iot bluetooth gas station eff twit contactless payments enterprise tech openvino sponsors wwt brian chee

This Week in Enterprise Tech 409: IoT It!

All TWiT.tv Shows (Video LO)

Play Episode Listen Later Sep 5, 2020 72:23

Apple to delay privacy change threatening Facebook, mobile ad marketDHS partners with industry to offer cybersecurity aidFeds can't ask Google for every phone in a 100-meter radius, court saysEFF on the Digital Services Act: Put Users in ControlMost IoT hardware easy to crackiOS 13.7 launches with Exposure Notification ExpressCOVID Tracing framework privacy busted by BluetoothPay at the pump with AlexaWorking smarter, not harder for cybersecurity teamsAlexis Crowell, Intel's IoT Marketing Global Lead talks about IoT opportunities for enterprise and what is OpenVINO? Hosts: Louis Maresca, Brian Chee, and Curt Franklin Guest: Alexis Crowell Download or subscribe to this show at https://twit.tv/shows/this-week-in-enterprise-tech. Sponsors: WWT.COM/TWIT itpro.tv/enterprise use code ENTERPRISE30 canary.tools/twit - use code: TWIT

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Streamline Deep-Learning Integration into Defect Classification

Intel IT

Play Episode Listen Later Jul 14, 2020

IT Best Practices: Intel factories are using the Intel Distribution of OpenVINO toolkit to streamline deep-learning integration with the factories’ computer vision automatic defect-classification systems. Intel factories have been using computer vision for over a decade to automate defect detection and classification. The factories use TensorFlow as the core open source library to help develop […] The post Streamline Deep-Learning Integration into Defect Classification first appeared on Connected Social Media.

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Streamline Deep-Learning Integration into Defect Classification

Intel – Connected Social Media

Play Episode Listen Later Jul 14, 2020

IT Best Practices: Intel factories are using the Intel Distribution of OpenVINO toolkit to streamline deep-learning integration with the factories’ computer vision automatic defect-classification systems. Intel factories have been using computer vision for over a decade to automate defect detection and classification. The factories use TensorFlow as the core open source library to help develop […] The post Streamline Deep-Learning Integration into Defect Classification first appeared on Connected Social Media.

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Streamline Deep-Learning Integration into Defect Classification

Connected Social Media

Play Episode Listen Later Jul 14, 2020

IT Best Practices: Intel factories are using the Intel Distribution of OpenVINO toolkit to streamline deep-learning integration with the factories’ computer vision automatic defect-classification systems. Intel factories have been using computer vision for over a decade to automate defect detection and classification. The factories use TensorFlow as the core open source library to help develop […] The post Streamline Deep-Learning Integration into Defect Classification first appeared on Connected Social Media.

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Enabling the Advancement of Edge Services and Applications - Intel® Chip Chat episode 693

The Six Five with Patrick Moorhead and Daniel Newman

Play Episode Listen Later Mar 26, 2020 14:30

Jeni Panhorst, Vice President and General Manager for the Network and Edge Platforms Division at Intel, joins Chip Chat to update on Intel's hardware and software infrastructure for the enablement of edge services. Panhorst has responsibility for all of Intel's products and platforms for network and network edge infrastructure, partnering deeply with customers to deliver the capabilities that will define the network of tomorrow. In this interview, Panhorst and host Allyson Klein highlight key technologies advancing the development of edge services, beginning with Intel Atom® P5900, a new 10nm System on a Chip (SoC) for 5G radio access networks (RAN). As Panhorst shares, 2020 is expected to see significant growth in 5G deployments. This new SoC delivers on customers' needs for high performance for packet processing and base station workloads and integrates seamlessly with other Intel network infrastructure products for end-to-end network solutions. Panhorst also speaks to up-the-stack Intel software investments that make it easier to more rapidly develop and deploy differentiated edge services and applications. Panhorst highlights OpenNESS, Open Network Edge Services Software, an open source reference toolkit that serves as an "easy button" for deploying innovative edge services, and CERA, the Converged Edge Reference Architecture, which brings together OpenNESS and OpenVINO™ toolkit to accelerate development. For more information on Intel's unmatched portfolio of solutions for 5G and edge infrastructure, please visit https://networkbuilders.intel.com, OpenNESS.org, and follow Jeni on Twitter at https://twitter.com/jeni_p. Notices & Disclaimers Intel technologies may require enabled hardware, software or service activation. No product or component can be absolutely secure. Your costs and results may vary. © Intel Corporation. Intel, the Intel logo, and other Intel marks are trademarks of Intel Corporation or its subsidiaries. Other names and brands may be claimed as the property of others.

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How Intel Is Using New Technology to Better Handle Data

Play Episode Listen Later Feb 25, 2020 27:31

In the latest episode of The Six Five, Daniel Newman and Patrick Moorhead welcome Lisa Spelman, VP and GM of Intel Xeon Processors and Memory. Early in the conversation, Lisa makes the important point that while many people still think of processors when they think of Intel, this company is doing much more than that. In fact, lately Intel has been focusing a lot on different, improved ways to move, store, and process data using everything from AI and 5G to edge computing and the cloud in general. More specifically, Lisa explained how AI is driving disruptive innovation across the data centric landscape in multiple ways. She mentioned that Intel professionals don’t see AI as a singular workload, but as a pervasive element that will be part of every workload, consumer and business alike. This disruption includes a huge transformation of enterprise workloads, as over 75% of applications are expected to integrate AI in the next 2 years. And at Intel, they see the AI opportunity exceeding $24 billion by 2024! As you might imagine, multiple types of compute will be necessary in the near future. Lisa explained that Intel offers the four key types of compute that analysts agree will usher in the next era of AI: CPUs, GPUs, FPGAs, and domain-specific architectures like Intel® Movidius™ VPUs and forthcoming Intel Habana ASICs. Combined with its decades of software expertise, the resources Intel has are among the most substantial in the industry. After all, its strategy has a foundation of Xeon with built-in AI acceleration. And with Deep Learning Boost, the 2nd Gen Xeon Scalable is using INT8 adoption in inference applications to drive a 14x improvement in less than 2 years. Basically, Intel is extending its unique server processor leadership for built-in AI acceleration with upcoming 3rd-Gen Intel Xeon Scalable processors with the integration of new extensions for Intel DL Boost called Bfloat16. This will increase deep learning training performance by up to 60% compared to the previous processor generation. And Intel just recently took another step in bolstering its position in AI by acquiring Habana. Another topic of discussion for Lisa was 5G technology, which has been accelerating to market lately. She’s seen investment in 5G RAN far outpace what was projected under a year ago, which is good because it’s definitely ground-breaking new technology that is raising the ceiling in data creation and delivery. Of course, many of the new services enabled by 5G will require redistribution of data processing, and readying all the infrastructure from the data center to the core network to the edge is also required to unlock 5G’s full potential. But so far, Intel has been collaborating with the world’s 5G leaders to design the world’s first standard, high-volume silicon foundation for radio access networks! The company even just announced the Intel Atom P5900, which was designed for 5G’s high-bandwidth, low-latency capabilities and combines compute, connectivity and acceleration technologies into a single SOC package. And it’s not stopping there, as Intel is also delivering a platform foundation that includes custom silicon solutions, from FPAGs to ASICs. This enables 5G infrastructure built to the customers’ desired TTM, cost, power, volume, performance and flexibility. Lisa went on to explain Intel’s work on the edge, as well. In fact, she mentioned that one of the largest growth drivers is at the edge, as it complements the increase in data creation and consumption at the endpoints due to the bandwidth and latencies offered by 5G. Capacity is shifting to the edge due to latency, bandwidth, security, and connectivity. Of course, edge computing comes with some challenges, such as bringing services to it, activating intelligence and automation in the network, and enabling virtualized networks. But Intel is intent on offering a range of solutions that pair HW (Atom, Xeon, FPGA, accelerators, memory, and connectivity) with edge-targeted open source SW, such as OpenVINO, OpenNESS, Open Visual Cloud. And that brings us to the last topic of conversation here, the cloud. In particular, Lisa stated that the foundation of growth is rooted in cloud computing. Built on IA and Intel innovation, such as Intel VT, the cloud is now fueling the modernization of on prem enterprise data centers. Lisa and her team at Intel have seen a trend that’s worth noting, which is the impact of digital services toward the growth of cloud. For instance, there’s been definite growth in digital consumer services, like retail (e-commerce), advertising, and media content. And they’re mostly being driven in two ways. One is the continued digitization of those consumer services, and the other is the continued user engagement in those services and platforms. But the wide-spanning diversity of those services requires a solutions approach to gain a performance advantage. If you want to know more about how Intel is continually improving how to handle data, head to the website to learn about its latest advancements with 5G and other technologies discussed here. And be sure to check out the next episode of The Six Five to keep hearing our analysis on the tech industry’s biggest stories!

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FOA 190: The World's First Open Source Winery

Farm & Rural Ag Network

Play Episode Listen Later Jan 29, 2020 30:52

Mike Barrow is the Project Lead at OpenVino, a company that aims to create the first-ever open-source, transparent winery, and wine-based cryptocurrency under the Costaflores label. Costaflores is a boutique organic winery based in Argentina. As suggested, OpenVino will rely on blockchain technology to engage in a new and innovative way of selling wine products. With over 30 years of experience in IT, data science, and cloud services, Mike aims to disrupt the wine world with a business that converts consumers into shareholders. Mike joins me today to share how OpenVino will innovate the way we consume wine through blockchain tech. He shares his passion for wine, what inspired him to start OpenVino, and why he chose to make the company open-source. He explains their data collecting strategies and how consumers can benefit from buying their cryptocurrency. Mike also describes how wine is priced and why quality is second to story. “The quality of the wine is not dictated by the quality parameter as much as the story behind it.” - Mike Barrow This Week on The Future of Agriculture Podcast: How an open-source winery works and how you can profit from it. Why it's difficult to sell wine regardless of price. The questions that led him to start an open-source winery. The data he needs to collect and how he makes sure his customers understand it. How blockchain fits into their business strategy. A quick recap of what blockchain is and how it works. Determining the best price for their wine products. Why they chose to tokenize their wine production. Resource: Episode 110: How Carbon Trading Can Benefit Farmers with Aldyen Donnelly of Nori Episode 189 - Farmers Building Their Own Open Source Technology Connect with Mike Barrow Costaflores OpenVino LinkedIn We Are a Part of a Bigger Family! The Future of Agriculture Podcast is now part of the Farm and Rural Ag Network. Listen to more ag-related podcasts by subscribing on iTunes or on the Farm and Rural Ag Network Website today. Join the Conversation! To get your most pressing ag questions answered and share your perspective on various topics we’ve discussed on the Future of Agriculture podcast, head over to SpeakPipe.com/FutureofAg and leave a recorded message! Share the Ag-Love! Thanks for joining us on the Future of Agriculture Podcast – your spot for valuable information, content, and interviews with industry leaders throughout the agricultural space! If you enjoyed this week’s episode, please subscribe on iTunes and leave your honest feedback. Don’t forget to share it with your friends on your favorite social media spots! Learn more about AgGrad by visiting: Future of Agriculture Website AgGrad Website AgGrad on Twitter AgGrad on Facebook AgGrad on LinkedIn AgGrad on Instagram

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FOA 190: The World's First Open Source Winery

Future of Agriculture

Play Episode Listen Later Jan 29, 2020 30:52

Mike Barrow is the Project Lead at OpenVino, a company that aims to create the first-ever open-source, transparent winery, and wine-based cryptocurrency under the Costaflores label. Costaflores is a boutique organic winery based in Argentina. As suggested, OpenVino will rely on blockchain technology to engage in a new and innovative way of selling wine products. With over 30 years of experience in IT, data science, and cloud services, Mike aims to disrupt the wine world with a business that converts consumers into shareholders. Mike joins me today to share how OpenVino will innovate the way we consume wine through blockchain tech. He shares his passion for wine, what inspired him to start OpenVino, and why he chose to make the company open-source. He explains their data collecting strategies and how consumers can benefit from buying their cryptocurrency. Mike also describes how wine is priced and why quality is second to story. “The quality of the wine is not dictated by the quality parameter as much as the story behind it.” - Mike Barrow This Week on The Future of Agriculture Podcast: How an open-source winery works and how you can profit from it. Why it's difficult to sell wine regardless of price. The questions that led him to start an open-source winery. The data he needs to collect and how he makes sure his customers understand it. How blockchain fits into their business strategy. A quick recap of what blockchain is and how it works. Determining the best price for their wine products. Why they chose to tokenize their wine production. Resource: Episode 110: How Carbon Trading Can Benefit Farmers with Aldyen Donnelly of Nori Episode 189 - Farmers Building Their Own Open Source Technology Connect with Mike Barrow Costaflores OpenVino LinkedIn We Are a Part of a Bigger Family! The Future of Agriculture Podcast is now part of the Farm and Rural Ag Network. Listen to more ag-related podcasts by subscribing on iTunes or on the Farm and Rural Ag Network Website today. Join the Conversation! To get your most pressing ag questions answered and share your perspective on various topics we’ve discussed on the Future of Agriculture podcast, head over to SpeakPipe.com/FutureofAg and leave a recorded message! Share the Ag-Love! Thanks for joining us on the Future of Agriculture Podcast – your spot for valuable information, content, and interviews with industry leaders throughout the agricultural space! If you enjoyed this week’s episode, please subscribe on iTunes and leave your honest feedback. Don’t forget to share it with your friends on your favorite social media spots! Learn more about AgGrad by visiting: Future of Agriculture Website AgGrad Website AgGrad on Twitter AgGrad on Facebook AgGrad on LinkedIn AgGrad on Instagram

conversations future argentina agriculture resource open source wineries speakpipe project lead world's first agriculture podcast openvino aggrad aldyen donnelly rural ag network rural ag network website

HCL Optimized Edge Analytics using Intel Distribution of OpenVINO toolkit – Intel on AI – Episode 43

Intel – Connected Social Media

Play Episode Listen Later Jan 8, 2020

In this Intel on AI podcast episode: The process of diagnosing a patient with chest abnormality is done by radiologists and doctors with a lot of experience and expertise. This involves looking for the presence of foreign bodies, infiltrates, and other information to determine the type of infection so that proper medication can be suggested […]

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HCL Optimized Edge Analytics using Intel Distribution of OpenVINO toolkit – Intel on AI – Episode 43

Play Episode Listen Later Jan 8, 2020

In this Intel on AI podcast episode: The process of diagnosing a patient with chest abnormality is done by radiologists and doctors with a lot of experience and expertise. This involves looking for the presence of foreign bodies, infiltrates, and other information to determine the type of infection so that proper medication can be suggested […]

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IoT Dev Chat: The Insight.tech Podcast

Play Episode Listen Later Oct 4, 2019 23:02

Industrial environments are tough on vision hardware. To ensure reliability, you must design for low power. But what does that mean for performance and cost? Find out in this conversation between Johnny Chen, Solutions Architect at OnLogic, and Kenton Williston, Editor-in-Chief of insight.tech

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Real-Time Motion Capture Technology with wrnch AI and Intel OpenVINO – Intel on AI – Episode 28

Play Episode Listen Later Sep 6, 2019

In this Intel on AI podcast episode: Today athletes are always looking for new ways to analyze and improve their performance through video analysis and sports enthusiasts love to experience sports in new and innovative ways, but 3D capture technology can be difficult to program and expensive to access. Paul Kruszewski, the CEO and Founder […]

Wipro Pipe Sleuth and Optimized Inference with Intel OpenVINO Toolkit – Intel on AI – Episode 27

Play Episode Listen Later Aug 29, 2019

In this Intel on AI podcast episode: Regular inspection of underground water and sewage pipelines is essential in the water utility industry to prioritize maintenance tasks and avoid pipe leakage, breakage, and blockage, which might result in property damage or safety hazards. Traditional inspection with videos being captured by a remotely operated rover and then […]

808 Radio #124 / Baltra / CMM Radio – 10/8/2019

808 Radio CMM

Play Episode Listen Later Aug 11, 2019 120:03

En las profundidades de agosto nos cruzamos con la música de Legowelt volviendo a utilizar el seudónimo de Gladio, el nuevo álbum de Baltra, o la delicadeza de Carla Del Forno entre muchas otras cosas. La Lista II: Felipe Gordon - Sick Ass Chords [Quintessentials] Afrodeutsche – And! [Skam] Rasmus Faber - Do My Best [Farplane Records] Andhim - Windows 85 [Superfriends] Free Range - Relax It's Just Eggs [Osàre! Editions] Tocadisco - Comatose [Toca45 Recordings] Gladio - Wild Horses [L.I.E.S.] DJ Bogdan - Love Inna Basement (Midnite XTC) Broken English Club - Vermin [L.I.E.S.] Versalife - Monospaced [20/20 Vision] Carla dal Forno - Took a Long Time [Callista Records] Lauer - Topo Chico [DGTL] Abrial - Wind Shear [Ritualism] Disco de la semana: 'Ted' de Baltra, publicado por 96 And Forever. Baltra - Flashback Baltra - Opal Drip Baltra - Bankrolls Baltra - Forever Alone Leyenda: ‘Hi- Tech Jazz’ de Galaxy 2 Galaxy (Mad Mike), publicada por UR en 1993. Generador de Ideas (#GdI808): Vinos y criptomonedas. Con Mike Barrow, de Openvino. La Lista II: Octo Octa - Spin Girl, Let's Activate! [T4T LUV NRG] DJ Haram - Gemini Rising [Hyperdub] Floating Points - Coorabell [Ninja Tune] Jumping Back Slash – Untitled Darknezz [Club Yeke] Jas Shaw & Fort Romeau - Voices (no.III) [Cin Cin] Martyn - Rhythm Ritual [Ostgut Ton] Edu Imbernon & Los Suruba – Balear [Last Night On Air] Developer - Purgatorio [Developer Archive] Kaczmarek – 2. Z [Kaczmarek] Rhyw - Lurk Late [Seilscheibenpfeiler Schallplatten Berlin]

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Vispera Visual Intelligence for Retail with Intel OpenVINO Toolkit – Intel on AI – Episode 24

Play Episode Listen Later Aug 7, 2019

In this Intel on AI podcast episode: Millions of dollars are lost by retailers worldwide each year as a result of out of stock products, overstocking, and shrinkage. Out of stock products also incur other costs, such as the reduced impact of in-store promotions and the time employees use dealing with customer requests about missing […]

Logic Supply Powers IoT at the Edge – Intel® Chip Chat episode 664

Play Episode Listen Later Jul 11, 2019 10:58

Not all advanced computing takes place in data centers. Maxx Garrison, product manager with Logic Supply, talked with Chip Chat about how the Internet of Things (IoT) is evolving and advantages that come with moving compute power to the edge with help from Intel technology. Logic Supply’s sealed systems turn up in demanding settings where contamination is a concern – farms, factories, hospitals, emergency vehicles – close to users and environmental data. As applications get smarter, data is coming from a variety of sources, and the amount is increasing. Sending it to the cloud can be expensive, and transmission can be a liability in decision-critical situations that demand low latency. The ability to gather, analyze, and deliver information quickly makes computing at the edge vital, and also opens complex use cases, like sensor fusion, where visual, thermal, and vibration data from local and remote sensors are combined and run through models. Sensor fusion with edge AI could expand what systems can do autonomously. Garrison sees data, sensors, and inputs continuing to increase, with systems advancing to meet the growing demand for intelligent compute at the edge. Logic Supply’s goal is to make input easy and, whatever the application, scale up seamlessly without rewriting or retraining models. They’re already getting close with the Intel® Distribution of OpenVINO™ toolkit, and they’re adding compute-intensive capabilities to their entire line of edge products, from entry-level devices to the high end, which features 2nd Generation Intel® Xeon® Scalable processors. For more about Logic Supply, visit https://www.logicsupply.com/ or twitter.com/LogicSupply For more about Intel products and technologies, visit https://intel.com. Intel technologies’ features and benefits depend on system configuration and may require enabled hardware, software or service activation. Performance varies depending on system configuration. No computer system can be absolutely secure. Check with your system manufacturer or retailer or learn more at intel.com. Intel, the Intel logo, OpenVINO, and Xeon are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries. *Other names and brands may be claimed as the property of others. © Intel Corporation

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SubtlePET Pushing Medical Imaging Limit with Intel Distribution of OpenVINO – Intel on AI – Episode 16

Play Episode Listen Later Jun 17, 2019

In this Intel on AI podcast episode: Tens of Millions of patients every year spend countless hours and billions of dollars on medical scans. Also, medical scans like PET (positron emission technology) or MRI (magnetic resonance imaging) scans can take a long time to conduct and can be very uncomfortable for patients. Enhao Gong, Founder […]

AI at the Edge – Intel® Chip Chat episode 659

Play Episode Listen Later Jun 6, 2019 11:18

This is the moment for AI at the edge. That’s the view of Fabrizio Del Maffeo, Vice President and Managing Director for AAEON Technology Europe. He spoke with Chip Chat about AI trends his company sees emerging worldwide. A leading manufacturer of advanced industrial and embedded computing platforms, AAEON brought intelligence to industrial controls. Today, it supports artificial intelligence and sponsors UP Bridge The Gap*, a user community for established companies starting to use AI. There’s more data and more video at the edge than ever before, says Del Maffeo, and it must be processed at the edge rather than in the cloud because of security, privacy, and bandwidth limitations. Algorithms running in the cloud must run on completely different architectures at the edge. AAEON has embraced Intel technology, particularly the Intel® Distribution of OpenVINO™ toolkit for porting code between platforms, something vital for customers moving from low-cost industrial architecture to high-performance Intel® Xeon® Scalable Processors, including the 2nd Generation family. While porting algorithms from cloud to edge is not yet plug-and-play, Del Maffeo foresees stronger integration between tools at the edge, including tools for cloud, machine learning, and deep learning – like TensorFlow* and CAFFE*. To learn more about AAEON visit aaeon.com. For information about UP Bridge The Gap, go to up-board.org. Intel technologies’ features and benefits depend on system configuration and may require enabled hardware, software or service activation. Performance varies depending on system configuration. No computer system can be absolutely secure. Check with your system manufacturer or retailer or learn more at intel.com. Intel, the Intel logo, OpenVINO, and Xeon are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries. *Other names and brands may be claimed as the property of others. © Intel Corporation

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Accelerating AI Deployments with the Edge to Cloud Intel AI Portfolio – Intel® Chip Chat episode 648

Play Episode Listen Later Apr 17, 2019 11:16

Wei Li, Vice President of Intel® Architecture, Graphics and Software, and General Manager of Machine Learning and Translation at Intel, joins Chip Chat to share Intel’s overarching strategy and vision for the future of AI and outline the company’s edge to cloud AI portfolio. Wei discusses how Intel architecture enables consistency across different platforms without having to overhaul systems. He also highlights increased inference performance with the 2nd Generation Intel® Xeon® Scalable processor with Intel® Deep Learning Boost (Intel DL Boost) technology, introduced at Intel Data-Centric Innovation Day. Intel DL Boost speeds inference up to 14x [1] by combining what used to be done in three instructions into one instruction and also allowing lower precision (int8) across multiple frameworks such as TensorFlow*, PyTorch*, Caffe* and Apache MXNet*. He also touches on the work Intel has done on the software side with projects like the OpenVINO™ toolkit – which accelerates DNN workloads and optimizes deep learning solutions across various hardware platforms. Finally, Wei outlines future AI integrations in Intel Xeon Scalable processors, like support for bfloat16. For more on Intel AI and the wide range of offerings and products, please visit www.intel.ai. [1] 2nd Generation Intel Xeon Scalable processors with Intel Deep Learning Boost provide up to 14x faster inference in comparison to 1st Generation Intel Xeon Scalable processors in July 2017, for details see https://www.intel.ai/2ndgenxeonscalable/. Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more information go to www.intel.com/benchmarks. Performance results are based on testing or projections as of 7/11/2017 to 4/1/2019 and may not reflect all publicly available security updates. See configuration disclosure for details. No product can be absolutely secure. Results have been estimated or simulated using internal Intel analysis or architecture simulation or modeling, and provided to you for informational purposes. Any differences in your system hardware, software or configuration may affect your actual performance. Intel’s compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice (Notice Revision #20110804). The benchmark results may need to be revised as additional testing is conducted. The results depend on the specific platform configurations and workloads utilized in the testing, and may not be applicable to any particular user’s components, computer system or workloads. The results are not necessarily representative of other benchmarks and other benchmark results may show greater or lesser impact from mitigations.

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Accelerating AI Inference with Microsoft Azure* Machine Learning - Intel® Chip Chat episode 626

Play Episode Listen Later Dec 20, 2018 7:45

Dr. Henry Jerez, Principal Group Product and Program Manager for Azure* Machine Learning Inferencing and Infrastructure at Microsoft, joins Chip Chat to discuss accelerating AI inference in Microsoft Azure. Dr. Jerez leads the team responsible for creating assets that help data scientists manage their AI models and deployments, both in the cloud and at the edge, and works closely with Intel to deliver the fastest-possible inference performance for Microsoft's customers. At Ignite 2018, Microsoft demoed an Azure Machine Learning model running atop the OpenVINO toolkit and Intel® architecture for highly-performant inference at the edge. This capability will soon be incorporated into Azure Machine Learning. Microsoft additionally announced at Ignite a refreshed public preview of Azure Machine Learning that now provides a unified platform and SDK for data scientists, IT professionals, and developers. For more on Microsoft Azure Machine Learning, please visit http://aka.ms/azureml-docs. Intel technologies' features and benefits depend on system configuration and may require enabled hardware, software or service activation. Performance varies depending on system configuration. No product or component can be absolutely secure. Check with your system manufacturer or retailer or learn more at intel.com. Intel and the Intel logo are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries. *Other names and brands may be claimed as the property of others. © Intel Corporation

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Diving Into the Visual Cloud

SMACtalk

Play Episode Listen Later Sep 13, 2018 17:41

In this Intel-sponsored episode of SMACTalk, Daniel Newman leads a show focused on the visual cloud. Joining Daniel is Lynn Comp, Vice President of Data Center Group and General Manager of the Visual Cloud Division Network Platform Group at Intel. During the show, they discuss what Intel is doing in the realm of the visual cloud and what we can expect in the future. Lynn focuses her time on helping cloud services be transformed. She talked about the visual cloud including visual workloads that are processed on the cloud and consumed remotely, resulting in horizontal make-up. She mentioned that a lot of enterprises want their subcontractors to be able to view their 3D models, but not the whole model itself. So, remote access is critical for intellectual property. Lynn mentions that individuals aged 18 to 49 tune into YouTube more often than they do TV. This is a worldwide trend that is exciting and pushing the visual cloud forward through the delivery of things like Comcast and other similar broadcasters. Lynn discussed how video marketing is becoming more and more common, especially for small to medium-sized businesses. The best way to work with this tech is to learn what the most effective solution might be for the network that they have. With the visual cloud, there is no single design point. Instead, there are multiple points, creating a better hook to increase conversions. The visual cloud gives developers more opportunities in their business models, workload placement and the user experience as a whole. Lynn explained what Intel’s strategy is for the visual cloud. Intel is taking a “software acceleration” approach, being in the market with software such as the Media Server Studio and Web RTC, which is a way to conduct streaming. Continuing on this acceleration, they will soon be open-sourcing DLDT or the Deep Learning Deployment Toolkit and OpenVino to help unleash innovation and make it easy for solution providers to find the right solution and deciding where to put it. Will they need to place it in the cloud or the edge? She also shared that Intel will also be opening up access to Scalable Video Technology and working with Google and others in the industry. By open-sourcing these capabilities, Intel believes they can unleash even more innovation. Lynn further explained that it doesn’t matter how optimized your solution is, if you don’t have the ability to move between the different design points. With Intel, you should have access to the same software that is scalable across all solution points. Instead of broadcasters needing to rip and replace their infrastructure, they can upgrade their hardware seamlessly through software. Lynn discussed how the whole broadcasting industry is making the switch from black box equipment to software-based architectures to be cloud ready. As the cloud makes 5G possible, it also leaves space for flexibility with the software to find visual cloud workloads. Daniel wrapped up the show by asking what the real outcome will be in investing in the visual cloud. Lynn explained that to some extent, everyone has the opportunity to be a creator. They can show their passions and talents to a wide audience using YouTube and other broadcasting tools. It isn’t just a passive experience anymore. We’ve unleashed the user’s creativity to create channels, broadcasts and communities that didn’t exist in the past.

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Accelerating FPGA Deep Learning for Intel OpenVINO - Intel® Chip Chat episode 587