Future Tech And Foresight

Marc and Cooper explore how enterprises are breaking free from big-tech vendor lock-in by using task-specific small language models to slash costs and boost accuracy.About the Episode The corporate AI landscape is shifting away from single-vendor dependence on tech giants. While mainstream narratives remain obsessed with massive general-purpose models, scaling enterprises are hitting walls with soaring token costs and security risks. This episode explores how forward-thinking organizations are adopting specialized, task-specific Small Language Models (SLMs) and model ensembles to achieve redundancy and absolute cost control.We unpack the impressive economics of AI inference, showcasing real-world case studies where businesses cut monthly compute bills from tens of thousands of dollars to just a few hundred. Far from losing capability, these fine-tuned architectures actually drive task accuracy up from 75% to over 95% compared to legacy setups, proving that smaller models can dramatically outperform generalized LLMs for specific business applications.Looking ahead, we discuss how AI agents will eventually mature into ubiquitous, invisible infrastructure—much like the internet or modern operating systems. From evolving job descriptions to the rising energy demands of data centers, this conversation maps out how to strategically position your operations for a decentralized, multi-provider AI future.About the GuestCalvin is the Co-Founder and COO of Neurometric AI, a pioneering company that helps organizations improve performance and cost efficiency by intelligently orchestrating inference-time compute for multi-model AI systems. Beyond his work at Neurometric, Calvin leads AI automation strategy across the industrial and infrastructure sectors as an Advisor to Pilot Wave Holdings. He also serves as an Advisor at the Milken Institute, conducting research on capital markets and private capital formation policy.Previously, he co-founded and served as CEO of Rhove, a fintech company that democratized real estate investing and went public via a NASDAQ direct listing. His work has been featured by the White House, Fast Company, and he co-hosts the podcast Inference Time Tactics. Through his work, Calvin continues to explore how intelligence, capital, and policy intersect to shape the next era of innovation.Linkedin: https://www.linkedin.com/in/coopernyc Website: https://www.neurometric.ai/Timestamps00:01:12 - Episode Commences 00:03:14 - Cooper's AI and Fintech Journey 00:06:58 -Small Language Model Inference Discussion 00:10:35 - AI Market Evolution Discussion 00:14:59 - AI Vendor Dependency Risks 00:18:40 - Small Language Models Implementation Update 00:23:08 - Large Language Model Market Trends 00:29:09 - AI Evolution and Applications 00:33:56 - AI Integration in Business Operations 00:37:03 - AI and Robotics Transformation Discussion 00:49:10 - Episode ConcludesAdditional Notes:For more check out the website: ⁠⁠https://futuretechandforesight.com/⁠⁠ Or connect with me on – Twitter: ⁠⁠https://twitter.com/FutureTech_Pod⁠⁠ Linkedin: ⁠⁠https://www.linkedin.com/company/futuretechandforesight/

Marc and Anthony break down how organizations can adopt AI effectively, why AI augments rather than replaces jobs, and what professionals must do to stay competitive in an AI-first world.About the Episode:AI adoption is no longer a future consideration — it’s a present-day reality reshaping how organizations operate across industries. In this episode, the discussion explores how AI is being implemented in real business environments, from customer support and financial services to healthcare and education. The conversation challenges common misconceptions about AI-driven job loss, reframing AI as a productivity amplifier rather than a replacement for human work.A key focus of the episode is why many organizations fail at AI implementation. Instead of fixing broken processes, companies often attempt to automate inefficiency, leading to disappointing results and internal resistance. The discussion highlights the importance of leadership, process redesign, and human oversight in ensuring AI systems are deployed safely, ethically, and commercially. The urgency of adoption is also examined, particularly as consumer expectations increasingly demand AI-powered experiences.The episode concludes with a forward-looking look at the AI-first workplace, emphasizing the growing need for upskilling, strong communication skills, and the ability to translate ideas into execution. From AI’s role in education to emerging physical AI applications, the conversation underscores a clear message: those who learn to work with AI will gain a lasting competitive advantage, while those who resist risk being left behind.About the Guest:Anthony Franco is a serial entrepreneur who's founded seven companies and successfully exited six—including two acquisitions by publicly traded firms. After consulting for 40% of the Fortune 100 and watching countless AI projects fail spectacularly, he co-created AI First Principles and the WISER Method. These aren't theoretical frameworks. They're battle-tested approaches born from real-world experience: watching organizations automate broken processes, chase vanity metrics, and miss the fundamental truth that AI amplifies whatever you feed it. Anthony's work focuses on helping leaders think AI-first while automating last—ensuring they solve actual problems instead of creating faster chaos. He's the co-host of How to Founder podcast and holds over 25 patents in technology and consumer products. His approach is simple: question everything, simplify ruthlessly, then automate intelligently. Because the future doesn't belong to companies with the most sophisticated AI—it belongs tothose who know what problems are worth solving.Linkedin: https://www.linkedin.com/in/anthonyfranco/Timestamps:00:01:16 - Episode Commences00:03:38 - AI Entrepreneurship Through Serendipity00:06:11 - AI's Role in Job Augmentation00:10:17 - AI Implementation Challenges in Organizations 00:18:26 - AI Adoption: Opportunities and Challenges00:22:34 - AI Adoption and Competitive Advantage00:27:49 - AI Adoption and Human Oversight00:34:23 - AI Adoption for Competitive Advantage00:38:49 - AI Language Models: Strengths and Adoption00:44:21 - AI Integration in Education Discussion00:41:54 - Episode ConcludesAdditional Notes:For more check out the website: https://futuretechandforesight.com/Or connect with me on –Twitter: https://twitter.com/FutureTech_PodLinkedin: https://www.linkedin.com/company/futuretechandforesight/

Marc and Richard Kedziora explore how AI, wearables, and real-world health data are enabling personalized wellness, preventive care, and new insights into complex medical challenges.About the Episode:This episode explores the rapid evolution of personal health technology and how AI is revolutionizing preventive care, wellness, and chronic disease management. From wearables and continuous glucose monitoring to data-driven health insights, the discussion highlights the tools and approaches empowering individuals to take control of their health, while also emphasizing the importance of training healthcare providers to leverage these technologies effectively. Listeners will gain insight into the intersection of technology, real-world evidence, and medical research, including the challenges of translating innovative ideas into clinical trials and scalable solutions.The conversation also covers emerging applications such as anosmia detection for early disease identification, rare disease treatment using AI, and the creation of global data repositories to normalize and compare research findings. Richard shares forward-looking perspectives on how AI and data aggregation will improve patient outcomes, streamline healthcare delivery, and accelerate innovation in the coming years. This episode offers a thought-provoking look at the transition from reactive sick-care to proactive, personalized health management.Additionally, listeners will hear about practical steps for improving personal wellness, including leveraging existing technologies to track lifestyle, nutrition, and sleep. Richard’s insights underscore the value of combining individual accountability with societal-level changes, while exploring how AI can uncover patterns in health data that would otherwise remain hidden. This discussion provides actionable ideas for anyone interested in improving their health, developing new medical technologies, or understanding the future of healthcare innovation.About the Guest:Richard Kedziora is the co-founder of Estenda Solutions, a leading company specializing in custom software development, data analysis, and AI for healthcare and medical companies. With a remarkable journey spanning over 30 years, he possesses a deep understanding of designing, developing, and deploying successful projects. His extensive experience enables him to provide valuable guidance and innovative insights, resulting in cost-effective solutions that improve patient outcomes. Mr. Kedziora received his M.B.A. from West Chester University and a Bachelor of Science in Computer Science from Duquesne University where he received the Excellence in Computer Science Award. He has spoken at numerous technical and healthcare conferences on a variety of topics and written or co-authored multiple articles focused on healthcare information technology, several published in peer-reviewed scientific journals. His work with clients has won multiple awards including a HIMSS Davies Award in 2017 and he recently received the Health 2.0 Outstanding Leadership Award.Website: https://www.estenda.com/Linkedin: https://www.linkedin.com/in/rjkedziora/Timestamps:00:01:17 - Episode Commences00:03:49 - Tech Entrepreneur's Journey in Digital Health 00:06:34 - Advancements in Personal Health Technology 00:20:46 - Health Tech Innovation and Collaboration 00:25:54 - Anosmia Research and Data Integration 00:34:19 - AI and Wearables in Healthcare 00:40:17 - Transition to Preventative Healthcare 00:45:06 - Episode ConcludesAdditional Notes:For more check out the website: https://futuretechandforesight.com/Or connect with me on –Twitter: https://twitter.com/FutureTech_PodLinkedin: https://www.linkedin.com/company/futuretechandforesight/

Marc and Dr. Ewelina Kurtys explore how living neurons are being used to build radically new biocomputers, examining the technology’s origins, challenges, ethics, and potential to outperform traditional computing in energy efficiency and complex problem-solving.About the Episode:This episode dives into the emerging world of biocomputing — a field exploring how living neurons can serve as powerful, energy-efficient processors capable of learning, adapting, and solving complex problems in entirely new ways. The conversation traces how this field developed, from early entrepreneurial vision to today’s cutting-edge research happening across a small number of pioneering companies worldwide, including groundbreaking work taking place in Switzerland.Listeners will hear about the promise of building central bioservers accessible remotely, how neurons dramatically outperform silicon chips in energy efficiency, and the technical challenges behind training living cell systems to behave like computational processors. The discussion also takes a forward-looking stance, exploring timelines, research milestones, commercialization paths, and why AI integration is essential to accelerating progress.Beyond the technical story, the episode thoughtfully examines ethical considerations around using human-derived neurons, questions of potential consciousness, and how society might navigate regulation and responsibility as this technology evolves. The result is a fascinating preview of a possible future where biological and digital computing work side by side to power the next generation of intelligence.About the Guest:Dr. Ewelina Kurtys comes from a multidisciplinary background spanning pharmacy, biotechnology, and neuroscience, bringing together scientific expertise with a strong focus on real-world innovation. Her work centers on the development of biocomputing systems that use living neurons to process information, pushing the boundaries of how computers can be built and what they can achieve. She has played a key role in advancing research, patent development, and commercialization strategies in this emerging field. With experience bridging academic research and applied technology, she works closely with global partners and institutions exploring bioprocessing and neuron-based computing. Through her work, Ewelina continues to help shape the future of computing, energy efficiency, and human-machine intelligence.Linkedin: https://www.linkedin.com/in/ewelinakurtys/Timestamps:00:01:14 - Episode Commences00:03:26 - Biocomputing: Living Neurons in Tech00:09:27 - Biocomputer Development With Living Neurons 00:19:05 - Neuron Survival in Biocomputer Research00:21:16 - Biocomputing Research and Investment Plans00:24:19 - Ethical Implications of Biocomputing Organoids00:29:55 - Biocomputer Development and Algorithms00:33:01 - Biocomputing and Remote Lab Collaboration00:40:34 - Episode ConcludesAdditional Notes:For more check out the website: https://futuretechandforesight.com/Or connect with me on –Twitter: https://twitter.com/FutureTech_PodLinkedin: https://www.linkedin.com/company/futuretechandforesight/