By now, almost everyone has heard of generative AI and its potential to revolutionize many industries. But does the hype align with the reality? As businesses search for ways to harness its power and gain a significant competitive edge, there are many questions: Which current generative AI opportunities can businesses start to take advantage of today? And what limitations do we still need to overcome? In this podcast, we dive into key benefits as well as challenges of building generative AI business solutions. We also talk about how to successfully build and deploy solutions that can help businesses take their efforts to the next level. Join us as we explore these ideas with: Teresa Tung, Cloud First Chief Technologists, Accenture Ramtin Davanlou, AI & Analytics Principle Director, Accenture Waleed Kadous, Chief Scientist, Anyscale Christina Cardoza, Editorial Director, insight.tech Teresa, Ramtin, and Waleed answer our questions about: The rise of and interest in generative AI Considerations for deploying generative AI solutions Taking generative AI out of the experimentation phase Biggest opportunities and use cases for generative AI The importance of partnerships and collaboration What’s next for generative AI Final thoughts and key takeaways Related Content For the latest innovations from Accenture and Anyscale, follow them on: Twitter: @Accenture_US and @anyscalecompute LinkedIn: Accenture and Anyscale

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.

Shopping for a new wardrobe is an experience that should be enjoyable and stress-free. But with the range of choices available thanks to modern fashion, it can easily turn into a tedious chore of navigating the maze of sizing discrepancies among different stores and brands. Imagine if you could just step into the fitting room and have a selection of perfectly fitting garments already waiting for you. Thanks to the advent of AI and 3D technology, this vision is becoming a reality. The future? A personalized AI shopping experience. This podcast explores innovative ways that AI transforms the fitting room, both online and in-store, by providing shoppers with personalized recommendations tailored to their unique body measurements and preferences. This custom approach not only enhances customer satisfaction but also drives sales and conversion rates. Join us as we delve into the future of retail fitting rooms, where AI serves as the catalyst for an immersive, personalized, and seamless shopping experience. Join us as we explore these ideas with: Hillary Littleton, Head of Marketing, FIT:MATCH Christina Cardoza, Editorial Director, insight.tech Hillary answers our questions about Current AI trends in the retail space (2:47) Retail challenges for providing quality shopping experiences (4:31) AI helping advance retail technology (6:31) Benefits of improving the fitting-room experience (8:48) Implementing new retail technology online and in-store (11:13) Value of partnerships when creating innovative retail solutions (14:45) Future of retail technology (15:31) How AI can optimize the shopping experience (17:06) Related Content To learn more about personalized AI shopping experiences, read Phygital Experiences Help Fashion Retail Shine. For the latest innovations from FIT:MATCH, follow them on Twitter at FIT:MATCH.ai and LinkedIn at FIT:MATCH.ai.

When you have easy access to services like healthcare, it’s easy to take them for granted. But rural areas all over the globe struggle to secure quality healthcare services. Due to a shortage of healthcare professionals and resources, extensive travel distances, and infrastructure limitations, many rural communities find themselves in an unfortunate position. But it doesn’t have to be this way. Digital health solutions have made significant progress in recent years, allowing rural areas to overcome these challenges and ensure patients receive top-tier healthcare regardless of their location. In this podcast, we discuss the many benefits of digital health solutions for rural communities, as well as some of the challenges that need to be addressed to ensure the accessibility and effectiveness of these technologies. We also hear from experts about how digital health is used around the world to reshape the healthcare landscape. Join us as we explore these ideas with: Leonardo Melo, Co-Owner, Diagnext Jason Miao, Oversea Business Director, imedtac Moji Ghodoussi, VP of Business Innovation & Partnerships, Teladoc Health Christina Cardoza, Editorial Director, insight.tech Leonardo, Jason, and Moji answer our questions about: The struggle to bring quality healthcare to different regions How digital healthcare solutions have evolved over the past few years Challenges hospitals and healthcare providers face in rural areas Breaking down barriers with new tools and technologies Types of infrastructure necessary for virtual healthcare How to successfully deploy digital health solutions Lessons learned from end users and customers The value of partnerships for rural healthcare Healthcare opportunities still on the horizon Related Content To learn more about virtual care and digital health solutions, read Telemedicine Solutions: Closing Healthcare’s Digital Divide, IoMT Technology Automates Vital Signs Measurement, and Teladoc Charts the Future of Telehealth.

IoT has permeated nearly every industry as businesses seek better access and insights into data and operations. But not all IoT devices are well suited for the rugged and sometimes harsh environments they are needed in—both outdoor and indoor. For example, a business that wants to deploy an IoT device in the field to monitor assets and detect anomalies must consider factors like the range of weather conditions and temperatures that the device may encounter. Fortunately, recent advancements in technology have made it easier to develop ruggedized industrial IoT devices that can reliably and efficiently operate in harsh environments. In this podcast, we will explore the recent advancements that have made rugged IoT a reality, the types of environmental concerns and risks that these devices must withstand, and the best approach for implementing rugged IoT devices in the field. Join us as we explore these ideas with: Jason Lu, Product Manager, ASUS David Zhu-Grant, Senior Product Manager, OnLogic Chad Hutchinson, Vice President of Engineering, Crystal Group Christina Cardoza, Editorial Director, insight.tech Jason, David, and Chad answer our questions about: The importance of rugged IoT Deployment challenges for harsh, outdoor environments Deployment challenges for indoor environments Overcoming rugged IoT deployment challenges Implementing rugged IoT devices Choosing scalable and future-proofed rugged IoT devices Use cases and real-world examples Leveraging partnerships to create better rugged IoT solutions Related Content For the latest innovations from ASUS, OnLogic, and Crystal Group, follow them on: Twitter: @ASUS, @OnLogic, @CrystalGroup LinkedIn: ASUS, OnLogic, Crystal Group

Location intelligence is already a part of our everyday lives, from using our phones to get directions to finding a nearby restaurant. But businesses now are starting to see the transformative potential of location intelligence. In fact, 95% of businesses now consider location intelligence to be essential, thanks to its ability to lower costs, improve customer experience, and enhance operations. But many businesses struggle to get the most out of their location data because it's often siloed in different departments or systems. AI and digital twins can help businesses to break down data silos and create a single, comprehensive view of their spaces in real time. AI can be used to analyze large volumes of location data and identify patterns and trends. Digital twins are virtual replicas of real-world objects or environments that can be used to track and monitor changes over time. In this podcast, we discuss the importance of location intelligence, the use of AI and digital twins for tracking and monitoring, and how to implement AI-powered tracking and monitoring safely and securely. Join us as we explore these ideas with: Tony Franklin, GM and Senior Director of Federal and Aerospace Markets, Intel  Christina Cardoza, Editorial Director, insight.tech Tony answers our questions about The importance of location intelligence Businesses’ challenges with achieving real-time insights The role digital twins and artificial intelligence play Tools and technologies necessary for success Using Intel® SceneScape OpenVINO™, Geti™ for location intelligence Addressing privacy concerns with AI-powered tracking and monitoring Future advancements of AI, digital twins, and location intelligence Related Content To learn more about the importance of location intelligence, read Monitor, Track, and Analyze Any Space with Intel® SceneScape. For the latest innovations from Intel, follow them on Twitter @intel and on LinkedIn at Intel Corporation.

Edge computing is quickly becoming known for its ability to improve business operations by reducing latency, delivering high performance, and providing real-time insights. But despite its promise, many businesses—especially in the industrial space—struggle to successfully adopt edge computing. One challenge is that industrial edge computing can be complex to scale. While it is relatively easy to get started with a few edge devices, managing a large-scale edge computing infrastructure can be daunting. Additionally, lack of a single edge computing standard can make it difficult to integrate edge devices and applications from different vendors. To overcome these challenges, businesses need to take a strategic approach to edge computing adoption. This includes carefully planning their edge computing architecture, selecting the right edge devices and applications, and implementing a robust management and orchestration framework. In this podcast, we discuss the state of edge computing across different environments, how businesses can successfully approach edge computing, key challenges and how to solve them, and what the future holds for edge computing in this space. Join us as we explore these ideas with: Martin Garner, Head of IoT Research, CCS Insight Dan Rodriguez, VP and GM of the Network and Edge Solutions Group, Intel Christina Cardoza, Editorial Director, insight.tech Martin and Dan answer our questions about: 2:49 The state of edge computing 7:04 Different edge opportunities for businesses 11:14 Why adoption is more challenging for manufacturers 15:02 How to successfully approach edge computing 20:52 Lessons learned from industry examples 24:08 The edge computing ecosystem and partnerships 26:36 Future proofing investments and efforts 28:00 What’s next for edge computing Related Content To learn more about adopting edge computing, read IoT Initiatives to Scale Industrial Edge Computing. For the latest innovations from CCS Insight and Intel, follow them on Twitter @ccsinsight and @intel, and on LinkedIn at CCS Insight and Intel Corporation.

There is a common misconception that AI will become an intrusive part of our everyday lives—but it’s actually quite the opposite. The reality is that AI has the potential to enhance everyday life in many ways that we may not even notice. For example, AI video analytics can be used in smart cities to monitor traffic flow, identify hazards, and help emergency responders quickly respond to incidents. Of course, there are still concerns around security and privacy. But many companies are committed to implementing AI in a way that prioritizes user security. In this podcast, we talk about the opportunities AI video analytics provide communities, real-world use of AI video analytics in smart cities, and how to successfully deploy these systems in a safe and secure way. Join us as we explore these ideas with: Srivikraman Murahari, VP of Products and Strategic Alliances, Videonetics Christina Cardoza, Editorial Director, insight.tech Srivikraman answers our questions about ChallengesAI video analytics address in smart cities Implementing AI solutions that balance citizen privacy and well-being Developing and deploying solutions citywide Technology infrastructure that goes into successful deployments Creating end-to-end solutions with ecosystem partners Additional opportunities and use cases for AI video analytics Related Content To learn more about what Videonetics is doing in the AI video analytics space, follow them on Twitter and LinkedIn.

Are we in for an autonomous mobile robot (AMR) takeover? Not exactly. But we can expect to see more AMRs implemented across industries to streamline production, improve operations, enhance work safety, and increase productivity. That’s because recent technology advancements have made the hardware and software components necessary to building these systems more cost-effective and accessible. And with artificial intelligence becoming more mainstream, it’s now possible not only to create AMRs capable of doing human tasks but integrate them into human worker environments. In this episode, we talk about how all this is possible today, what we can expect in the future, top applications and opportunities for industries, and all the ins and outs of developing, deploying, and implementing AMRs safely and securely. Join us as we explore these ideas with: Claire Liu, Senior Product Marketing Manager, congatec Timo Kuehn, Systems Architect and Product Manager, Real-Time Systems Christina Cardoza, Editorial Director, insight.tech Claire and Timo answer our questions about: The meaning of autonomous mobile robots Implementing AMRs safely on the factory floor Developing AMRs to meet real-time demand Taking a modular approach when designing AMRs Tools and technologies necessary for AMR development Biggest use cases and opportunities for AMRs today AMR advancements we can expect Related Content To learn more about autonomous mobile robots, read IoT Virtualization Jump-Starts Collaborative Robots. For the latest innovations from congatec and Real-Time Systems, follow them on Twitter at @congatecAG and LinkedIn at congatec and Real-Time Systems GmbH.

Businesses and organizations are filled with all kinds of data that could provide valuable insights into their operations and decision-making. But first they need a strategy and the proper tools and technologies in place to put it all in motion. In this episode, we look at various data-driven strategies, challenges, and best practices from across industries. We also explore the key components of a successful data-driven culture, such as collecting and managing data, leveraging artificial intelligence and predictive analytics, and forming partnerships with other businesses. By understanding these concepts, businesses can harness the power of data to unlock insights and make informed decisions. Join us as we explore these ideas with: Saransh Karira, Head of Engineering, Awios Atif Kureishy, CEO and Founder, Vistry Christina Cardoza, Editorial Director, insight.tech Saransh and Atif answer our questions about The meaning of data-driven cultures Technological advancements making data more accessible Successfully implementing a data-driven strategy AI’s role in creating data-driven cultures Lessoned learned from the industry Leveraging expertise from partners For the latest innovations from Awiros and Vistry, follow them on: Twitter at @awirosweb and @vistryai and LinkedIn: Awiros and Vistry