Earley AI Podcast

In this episode of the Earley AI Podcast, host Seth Earley sits down with Yang Li, a leading figure in AI and software innovation. Yang is the Chief Operating Officer of Cosine, an advanced AI development firm, with deep experience driving startups, scaling organizations, and pioneering advancements in engineering and software development. Yang's work focuses on leveraging AI to empower the next generation of developers, especially in navigating the increasingly complex landscape of modern and legacy codebases.Yang and Seth dive into how AI is reshaping the role of software engineers, the evolving challenges of handling massive backlogs and legacy systems, and what creativity and efficiency really look like in an age of AI-powered software development.Key Takeaways:AI's Impact on Software Engineering: AI is shifting the developer's role from hands-on coding to more creative, iterative, and strategic work.Tackling Legacy Code: Cosine is pioneering new ways for AI to handle outdated and complex codebases (like COBOL and Fortran) that most engineers—and AI models—struggle with.Augmenting, Not Replacing, Engineers: AI tools like Cosine's Genie reduce ramp-up time for engineers, help address daunting backlogs, and act as creative partners rather than outright replacements.The Challenge of Benchmarks: Yang explains why public coding benchmarks can be misleading when bringing products to real-world enterprise environments, especially with diverse codebases.The Emergence of ‘Vibe Coding': Idea-to-prototype time is shrinking, allowing non-technical team members to quickly bring their ideas to life using AI assistants.Risks & Limits: Over-reliance on AI, standardization versus differentiation, and the need for new evaluation criteria in engineering organizations.Future Skills: The importance of risk-taking, adaptability, and prompt engineering as software development evolves, plus insights into how organizations are rethinking career ladders and promotions in an AI-powered world.Insightful Quote from Yang Li:"Previously you had to use words and language to describe your idea, you can now show people your idea... The time between you having thought of an idea to actually be able to show people that idea has now reduced almost to zero because of vibe coding."Tune in to discover what's next for software engineering in the age of AI, and how to stay ahead in this rapidly changing landscape.Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

In this episode of the Earley AI Podcast, host Seth Earley sits down with industry analyst and advisor Tony Baer, a seasoned expert in data, cloud, and analytics. With decades of experience guiding global tech leaders like AWS and Oracle, Tony brings a nuanced perspective on how knowledge engineering is evolving—and why context is the missing link in many enterprise AI initiatives.Together, Seth and Tony explore the shift from static data models to dynamic knowledge frameworks, the renewed importance of governance, and how graph databases and generative AI are reshaping enterprise intelligence. This is a conversation packed with hard-earned lessons and actionable insight for data, IT, and transformation leaders aiming to make AI work in the real world.Key Takeaways:Knowledge engineering today is about dynamic, adaptive structures—not static ontologies or rigid models.The role of the knowledge engineer is shifting: it's less about technical mastery and more about bridging data, business, and domain expertise.Context is foundational. The five W's—Who, What, When, Where, Why (and How)—unlock meaningful, actionable intelligence.Graph databases and AI are enabling real-time connections across data, turning static information into living knowledge.Generative AI delivers the most value when rooted in organizational context. RAG strategies demand clean data and strong information architecture.Successful AI initiatives are focused. Start with well-bounded, high-impact processes—avoid boiling the ocean. Core principles from previous data waves still apply. It's about evolving governance, stewardship, and architecture for the AI era. Sustainable value comes from feedback loops, iteration, and alignment—not silver bullets. Tune in to discover how to make AI practical, actionable, and intelligent for your organization.Quote of the Show: "Just because something is old does not make it wrong. There are a lot of disciplines we've built up over the years—governance, data stewardship—that still matter. The principle was right. We just adapt it and use our learnings from each cycle to become more knowledgeable and proficient." Tony BaerLinksLinkedIn: https://www.linkedin.com/in/dbinsight/Website: https://www.dbinsight.ioThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

In this episode of the Earley AI Podcast, host Seth Earley welcomes two insightful guests from Anders, a top 100 CPA firm: David Hartley and Dave Blatt. David Hartley is a seasoned CPA with a profound understanding of the synergy between finance and technology. He advocates for how AI can enhance traditional accounting roles rather than replace them. Dave Blatt brings a wealth of knowledge in AI automation and analytics, focusing on empowering mid-sized companies to harness AI for competing with larger players.Join us as we dive into the world of AI applications in the finance, accounting, and mid-market operations sectors. Our guests dispel common myths and fears surrounding AI, exploring how small and medium-sized enterprises can practically and effectively adopt AI technologies to drive transformation and growth.Key Takeaways:Demystifying AI: Understanding AI in the context of mid-market companies and addressing misconceptions around AI replacing human jobs.AI for Mid-Sized Enterprises:** How AI is accessible and beneficial for mid-sized businesses, allowing them to compete with larger organizations.Impact on Accounting: Enhancing traditional accounting roles through AI and freeing up time for more value-added activities.Implementation Strategies: Best practices for implementing AI in mid-sized companies, focusing on education, small projects, and quick wins.Real-World Applications: Case studies in industries like construction and manufacturing, where AI has improved efficiency and productivity.Communication and Trust: The importance of communication and building trust among team members to ensure successful AI adoption.Quote of the Show: "Start small and not make it so daunting... get some quick wins that will be a catalyst to doing more projects and bigger efforts." - Dave BlattLinks:LinkedIn: https://www.linkedin.com/in/davehartley/LinkedIn: https://www.linkedin.com/in/daveblatt/Website: https://anderscpa.comArticle: AI Adoption Is Not as Hard as You Think – Start Now or Fall BehindThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

In this episode of the Earley AI Podcast, we welcome guest, Jack Lampka, an accomplished advisor and speaker with over 27 years of experience in corporate roles within the tech and pharma sectors. Now based in Munich, Germany, Jack specializes in enhancing data storytelling and cultivating a product mindset among technical employees. His extensive career journey includes living and working in countries like Poland and the United States.Key Takeaways from this Episode:The importance of a product mindset for technical teams when developing AI solutions.Understanding the misconceptions and realistic expectations for AI and generative AI in businesses.How to successfully sell AI solutions internally by focusing on business needs and creating a comprehensive product marketing plan.The role of data storytelling in bridging the gap between technical and non-technical users.Insights into the hype surrounding Agentic AI and its relevance to current business applications.Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

Join Seth Earley on Earley AI Podcasts as he welcomes Adam Honig, a pioneering force in the field of customer relationship management (CRM). As the founder of Spiro AI, Adam challenges the conventional need for CRM systems by offering an innovative AI-driven alternative. With a rich history of building one of the largest Salesforce consulting partners—eventually acquired by Accenture—Adam's insights blend tradition with transformative technology, sparking discussions about the evolving landscape of CRM. Key Takeaways:Revolutionizing CRM: Understand Adam's perspective on why traditional CRM systems are antiquated and how Spiro's AI-driven approach offers a modern solution. Automated Data Capture: Learn how Spiro AI automates the tedious process of data entry and offers real-time insights for sales teams without manual input. Industry-Specific Challenges: Explore the unique hurdles faced by manufacturing and distribution sectors in adopting CRM and AI technologies. AI Implementation: Discover practical implementations of AI, including order entry automation, in revolutionizing traditional business models. Future of Work: Delve into a candid discussion on how AI could lead to significant job displacement, and the broader economic implications. Roadmap of Innovation: Get a sneak peek into future developments, including autonomous AI agents and enhanced integration with product data.Quote from the show:"Salespeople didn't go into sales to enter data. They want to meet with customers. They want to be where the action is, and they need the software to just get out of their way." – Adam HonigLinks:LinkedIn: https://www.linkedin.com/in/adamhonig/Website: https://spiro.aiX: https://x.com/adamhonigThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

In this episode, Seth Earley is joined by Brian Magerko, a professor of digital media at Georgia Institute of Technology and a pioneer in applied AI and computer-human interaction. Brian shares his journey through the academic realm and his fascinating experiences, including co-founding EarSketch, an educational platform that merges coding with music for nearly 2 million users. Together, Seth and Brian explore the bridging of technical language gaps, the role of AI in creativity, and unravel common misconceptions about generative AI. Listen in as they discuss the complexities of AI-driven creativity, the importance of fostering AI literacy in organizations, and the ethical considerations that come with the integration of cutting-edge technology. This episode is packed with insights that are sure to provoke thought and inspire innovation in any AI enthusiast or professional. Join us as we continue our journey into the evolving landscape of artificial intelligence.Key Takeaways:The evolution of AI from aspirational concepts to today's realities in the marketplace.Insights into the bridging of technical language gaps and the role of AI in creativity.Common misconceptions and myths about generative AI and its responsible use.Importance of a holistic organizational approach to adopting AI technology, including involving diverse stakeholders.Discussion on the implications of biases in AI and the significance of responsible data handling.Quote from the show:"They are tools, not oracles, you know, they're things that are great in the hands of people that know how to use them." - Brian MagerkoLinks:LinkedIn: https://www.linkedin.com/in/magerko/Website: https://expressivemachinery.gatech.eduX: https://x.com/thatmagerkoThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

In this episode, hosts Seth Earley and Chris Featherstone are joined by Don Gossen  to explore the transformative potential of AI and blockchain in decentralized energy networks. This episode explores how AI and blockchain technologies work together to optimize energy consumption, secure transactions, and drive innovation in local energy management. Don shares real-world case studies showcasing the impact of AI-driven IoT solutions, from reducing costs to enabling energy sovereignty in European markets.Key Takeaways:AI's Role in Energy Optimization – How AI-powered agents connect with IoT devices to enhance efficiency and manage decentralized transactions.Blockchain for Security & Transparency – The role of blockchain in securing transactions and ensuring trust in energy markets.Real-World Applications – Case studies of AI-driven decentralized energy networks lowering costs and increasing sustainability.Future Trends – The emergence of AI-driven economic models that could redefine how energy is produced and consumed.Tune in to hear Don's insights on the cutting edge of AI, blockchain, and the future of decentralized energy.Quote from the show:"Blockchain technology offers elegant solutions to problems of provenance in data and ML models, enabling higher fidelity and trustworthiness. The integration of decentralized blockchain with centralized ML technology presents conflicts, but it is essential for developing better solutions and new economic models. It's about more than just replacing tasks; it's about redefining how we manage and transact value in an increasingly autonomous ecosystem." – Don GossenLinks:LinkedIn: https://www.linkedin.com/in/donald-gossen-40ab96/Website: https://nevermined.ioX: https://x.com/dongossenThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

In this episode, hosts Seth Earley and Chris Featherstone are joined by John Lenker, an accomplished expert in enterprise search and data governance. John, who has presented to technology leaders like the CTO of NASA and the CIO of the Marshall Space Center, shares his extensive knowledge and experiences from working with leading companies. Currently engaged with Big ID, John delves deep into the evolving landscape of search technologies, data security, and enterprise-specific solutions.Key takeaways:Evolution of Search Technologies:  Current search tools are transitioning from simple keyword-based systems to sophisticated question-based interactions, offering synthesized answers and enhancing data findability.Importance of Security:  John underscores the critical need for granular security in modern search technologies, detailing the challenges of securing sensitive documents amidst cloud migration and generative AI implementations.Trust and Customization:  Organizations can trust search vendors to enhance data findability while retaining existing systems. Companies must consider both common needs and unique requirements shaped by their environments and practices.Challenges with Legacy Systems:  Accessing and modernizing data from outdated systems adds complexity to organizational workflows, necessitating a fine balance between old and new technologies.Retrieval Augmented Generation (RAG):  The future of search lies in interactive models like GPT, evolving towards more contextually relevant search experiences.Quote from the show:"Effective information architecture is the backbone of superior search experiences. It's not just about finding information—it's about finding the right information securely and efficiently." – John LenkerLinks:LinkedIn: https://www.linkedin.com/in/jlenker/Website: https://bigid.comX: https://x.com/LenkerITProThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

In this episode of the Earley AI Podcast Sahitya Senapthy, Founder and CEO of Endeavor, joins us for an episode filled with rich discussions on AI, data management, and the intriguing paths of technological advancement in industrial manufacturing. Sahitya's career has spanned work with the US Air Force, AWS, and Palantir. Sahitya joins our hosts, Seth Earley and Chris Featherstone, as they have an in-depth discussion about the intersection of AI and industrial manufacturing.Key takeaways:Rethinking AI Implementation: The importance of moving beyond simple chatbot applications like ChatGPT to realize real ROI through generative AI for sales optimization and cost savings in industrial spaces.Phased Approach to Tech Deployment: The "crawl, walk, run" methodology along with proof-of-concept (POC) phases is crucial in acclimating users and ensuring new tools deliver tangible ROI, avoiding "shelf-ware."Data Privacy and Security: Amidst the integration of sophisticated AI solutions, maintaining data privacy and security remains paramount.Quote from the show:"Real ROI in industrial spaces comes from effectively using generative AI for sales and cost savings—not just relying on chatbots." - Sahitya SenapathyLinks:LinkedIn: https://www.linkedin.com/in/sahityas/Website: https://www.endeavor.aiThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

In this episode of the Earley AI Podcast Camden Swita, the Head of AI and ML Innovation at New Relic, joins us for an insightful discussion on the transformative role of AI in modern technology. With a rich background spanning journalism, product management, and cutting-edge AI/ML initiatives, Camden brings a unique perspective on leveraging artificial intelligence to enhance both professional and creative workflows. Camden joins our hosts, Seth Earley and Chris Featherstone, as they navigating the complexities of data readiness and AI operationsKey takeaways:Understanding Vendor Offerings and Data Infrastructure: The importance of scrutinizing vendor promises and the potential of building simpler AI solutions, like basic chatbots, in-house. Consulting legitimate data scientists and engineers to assess data readiness before plunging into AI investments was highly recommended.Impact of Generative AI on Content Creation: Generative AI's role in automating content creation is rapidly evolving. While it offers incredible efficiencies in some areas, its application in creative writing is still experimental and requires a balance between traditional methods and automation.Modular Retrieval Augmented Generation (RAG): The concept of Modular RAG was explored as a way to enhance language models with relevant context. This system uses specific data sources to fill knowledge gaps, making responses more accurate and targeted. The discussion included how visual tools like heatmaps can identify and improve sparse contexts.Quote from the show:"Understanding the actual capabilities of AI systems and the state of your own data infrastructure is crucial. Investing in foundational data work isn't glamorous, but it's the backbone of any successful AI implementation. Without it, even the most advanced algorithms can't deliver meaningful results." - Camden SwitaLinks:LinkedIn: https://www.linkedin.com/in/camden-swita-54a41aa/Website: https://newrelic.comThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

In this episode of the Earley AI Podcast Ron Green, Founder of KUNGFU.ai joins host Chris Featherstone. Ron's expertise spans over 25 years in artificial intelligence and machine learning. Starting his journey in computer science during the early days of AI, he has witnessed and contributed to the evolution of the field from modest neural networks to today's complex, groundbreaking systems. With a master's degree in AI from Sussex, he has firsthand experience in areas ranging from protein folding predictions to advanced graph models. Key takeaways:Feedback Loop in LLMs: Discover why training large language models (LLMs) using their own generated data can create a feedback loop reducing model capabilities.AI Accuracy and Trust: Insights into the importance of building trust in AI through accurate models and robust graph environments handling diverse data associations.Ethical AI Development: Discussions on the ethical challenges and necessary oversight in AI, emphasizing transparency and policy controls to mitigate biases.Quote from the show:"Accuracy in AI models builds trust, and that's crucial for their successful deployment. But it's vital to remember that all models have biases; the key lies in identifying and addressing the unfair ones early on." - Ron GreenLinks:LinkedIn: https://www.linkedin.com/in/rongreen/Website: https://www.kungfu.aiPodcast: https://www.kungfu.ai/resources/hidden-layersThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

In this episode of the Earley AI Podcast we are joined by guest David Marra a seasoned expert in AI-driven investment strategies and founder of Marken Asset Management. David brings invaluable insights into the transformative potential of AI, particularly in complex payroll workflows, ERP systems, and financial services.David joins our hosts, Seth Earley and Chris Featherstone, as they explore the current state and future of AI, including the integration of large language models (LLMs) and the importance of robust data management.Key takeaways:AI for Simplifying Workflows: AI, particularly chatbots, can streamline complex payroll tasks, improving productivity by up to 30% and reducing errors.AI in Financial Services: Though slower to adopt AI, financial services have vast potential, offering long-term growth opportunities through AI investments.Global AI & Investment: Japan's AI market is booming, and companies with strong data infrastructures are best positioned to benefit from AI advancements.Quote from the show:"2023 was the wake-up call for realizing new technology's immense potential, and as we transition pilot programs to production systems in 2024, we'll start seeing real, tangible outcomes by 2025. The application layer of AI isn't just a technological enhancement; it's poised to become a multi-trillion-dollar market, revolutionizing capabilities and creating workflows that weren't even conceivable before." - David MarraLinks:LinkedIn: https://www.linkedin.com/in/david-marra-8693b44/Website: https://markinfunds.comThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

In this episode of the Earley AI Podcast we are joined by guest Yuri Dvoinos, the Chief Innovation Officer at Aura, a leading cybersecurity company based in Boston. With an extensive background in information security, AI applications, and data privacy, Yuri brings a wealth of knowledge on how to protect personal information in the digital age.Join our hosts Seth Earley and Chris Featherstone as Yuri explains the intricacies of data privacy, the adverse effects of phone scams, and the critical role of AI in detecting and thwarting sophisticated fraud attempts, including deepfakes and phishing scams.Key takeaways:The Importance of Understanding Your Digital Footprint. Learn how your online activities impact your privacy and what steps you can take to protect yourself.Identity Protection and the Impact of Scams. Delve into the psychological toll of phone scams, particularly on seniors, and how to safeguard against such threats.The Role of AI in Scam Detection. Understand how AI can detect psychological pressure and scam tactics in real-time, and the challenges in distinguishing AI-generated chats from real conversations.The Rise of Deepfakes. Explore the dangers of deepfakes in voice and video manipulation, and the need for heightened vigilance.Quote from the show:"Understanding one's digital footprint and protecting personal information online is no longer optional—it's essential. The rise of deepfakes and sophisticated scam tactics means that we need to be more critical and skeptical of the information we encounter. Leveraging AI to detect psychological pressure and scam tactics in real time can help us stay one step ahead, but ultimately, it starts with heightened awareness and constant vigilance." - Yuri DvoinosLinks:LinkedIn: https://www.linkedin.com/in/dvoinos/Website: https://www.aura.comTwitter: https://x.com/YuriyNosThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

In this episode of Earley AI Podcasts, we welcome Bartek Roszak, an expert in artificial intelligence and data science. With a career starting as an equity trader and evolving to lead AI strategy and implementation at STX Next, Bartek brings deep insights into the world of AI-driven trading and data quality improvement.Join hosts Seth Earley and Chris Featherstone as they explore Bartek's experiences, the nuances of deploying AI in trading, and the future potential of generative models.Key takeaways:Understanding the intricacies of modular rag for batch processing and data quality improvement.Insights into the use of AI bots in trading, and a critical view on publicized successful strategies.The importance of validating models to prevent data leakage and overfitting, and monitoring accuracy post-deployment.Challenges and solutions in training generative AI models, including the necessity for human validation.How advanced techniques like re-rankers and embedders enhance the accuracy of large language models (LLMs).The evolving trends in AI, including the hype around newer approaches like prompt engineering and multi-agent strategies.The significance of knowledge architecture and metadata in enriching content embeddings for better outcomes.Quote from the show:"Embracing opportunities across different industries and persevering through rejections is crucial. The field of AI is ever-evolving, and staying adaptable and curious will open doors you never imagined." — Bartek RoszakLinks:LinkedIn: https://www.linkedin.com/in/bartekroszak/Website: https://www.stxnext.comThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

In this episode of the Earley AI Podcast guest Tobias Zwingmann, an esteemed analytics and AI expert from Hanover, Germany, brings a wealth of experience from his work with SaaS platforms and consulting, and he shares invaluable insights on the practical intricacies of AI in business.Join our hosts Seth Earley and Chris Featherstone as they discuss with Tobias the importance of business leaders understanding AI, the pitfalls of misleading sales tactics, and the necessity of organizational alignment for successful AI implementation. With topics ranging from data quality to the challenges of adopting generative AI, this episode is a treasure trove of actionable advice for anyone looking to navigate the complex world of artificial intelligence.Key takeaways:The critical need for business leaders to educate themselves on AI and LLMs to ask the right questions and evaluate vendors effectively.The foundational role of good data in AI projects and examples of AI used to rectify data issues.The tendency of software vendors to oversell solutions and the issues arising from improper data formats and organizational misalignment.Challenges presented by fragmented processes, systems, and data in large enterprises and the benefit of small, targeted interventions.The importance of data labeling, taxonomies, ontologies, and metadata in effectively leveraging AI.Misconceptions about AI as pure software and the need to shift mindsets for working with generative AI.Difficulties in scaling generative AI and defining outcomes, leading to missed opportunities for customers.Quote from the show:"Understanding AI requires commitment at the senior level. You need those workshops. You need commitment and understanding because, without alignment, no AI implementation will truly succeed." - Tobias ZwingmannLinks:LinkedIn: https://www.linkedin.com/in/tobias-zwingmann/Website: https://www.rapyd.aiTwitter: https://x.com/ztobiWebsite: newsletter.tobiaszwingmann.comThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

In this episode of Earley AI Podcasts, we are joined by Nick Usborne, a veteran copywriter with over four decades of experience and an advocate for the sophisticated use of generative AI in human-centric communication. Nick provides a wealth of insights into the pitfalls and potentials of integrating AI into marketing and how businesses can leverage AI without losing their unique voice.Key Takeaways:Human Connection Matters:The episode opens with Nick Usborne expressing disappointment and loss of trust in a brand due to an impersonal automated onboarding process, emphasizing the need for emotional intelligence in all interactions.Education and Training in AI:Nick stresses the importance of better educating employees and businesses on AI capabilities and limitations.The Sameness Trap:A discussion on the risk of using identical AI models to create content, leading to homogenization and a loss of brand uniqueness.Limitations of AI:Nick elaborates on AI's current inability to genuinely experience emotions and sensory input, stressing the crucial role of human supervision.Structured Prompts for AI:Nick shares methods, like the RACE framework, to optimize AI outputs and ensure relevance and quality.Human Creativity in Marketing:The necessity of human involvement to preserve creativity and innovation in marketing efforts despite the speed and efficiency of AI.Quote from the show:"AI will never replace the human touch in creating meaningful connections and fostering trust. It's a partner, not a tool, and our role is to guide it with emotional intelligence and creativity." – Nick UsborneThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

This episode of the Earley AI Podcasts features Jason Radisson, an expert in digital transformations who has worked with renowned companies such as McKinsey, eBay, and Uber.Tune in as Jason shares his insights on the misconceptions surrounding AI startups and the importance of having a quality team with enterprise experience. He also highlights the agility of startups in implementing new features and integrations, challenging the notion of slow processes.Key takeaways:-AI startups benefit from having a quality team with enterprise experience, allowing them to be agile and quickly implement new features and integrations.- Non-tech companies often struggle to adapt to automation due to cultural barriers and legacy thinking, despite automation not requiring lengthy change management processes.- The gig economy presents challenges in optimizing large workforces, requiring a balance between employer and employee perspectives to create win-win solutions.- Organizations need to actively seek out innovative strategies and technologies to stay competitive, rather than relying on traditional approaches such as enterprise data warehouses and data lakes.Quote from the show:"The common approach of starting with an enterprise data warehouse and data lake is a fallacy. It's crucial to work backwards from customer-first use cases and focus on initiatives that will drive business value. By making quick developments and enabling additional investment, companies can harness the power of AI and machine learning technologies to transform their operations and stay ahead of the curve." - Jason RadissonLinks:LinkedIn: https://www.linkedin.com/in/jason-radisson/Website: https://www.movo.coWays to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-homeApple Podcast: https://podcasts.apple.com/podcast/id1586654770Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/Stitcher: https://www.stitcher.com/show/earley-ai-podcastAmazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcastBuzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

With extensive experience in AI and machine learning dating back to 1998, Cohen-Dumani brings valuable insights into the historical and present-day landscape of AI, emphasizing the importance of foundational knowledge, expertise, and knowledge management in making AI work effectively within organizations.Tune in to this enlightening conversation as they discuss the attention and resources that must be invested in unstructured data and knowledge to leverage the full potential of AI.Key takeaways:- A foundational reference architecture is critical for making sense of data and discerning between vendors' aspirational capabilities and reality.- Traditional long-term technology planning is no longer applicable in the age of AI and large language models (LLMs) due to the unpredictable nature of AI's uses and leveraging capabilities.- Executives should personally experiment with AI tools and allow more freedom for workers to adopt AI, rather than stifling innovation.- Building an extensible and expandable data foundation and good enterprise architecture is crucial to avoid data silos and maintain consistency in data.Quote from the show:"I think one of the challenges that organizations have is they're not investing the time, the effort, the money, the resources, and the attention on unstructured data, on knowledge. You know, if you look at any accounting department, they spend inordinate amount of time and resources on numbers, on transactional data. But if you look at how much effort is put on unstructured data, it's night and day. And yet unstructured data is 80+% of the data most organizations have." - Daniel Cohen-DumaniLinks:LinkedIn: https://www.linkedin.com/in/dcohendumani/Website: https://www.withum.comThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

A tech innovator with profound expertise in AI and its applications, our guest Alex Gurbych joins us with rich insights into how AI integrates into varying industries. Alex has extensive experience addressing the challenges and potentials of AI, especially in legacy systems and organizations.Tune in to this enlightening conversation as they dissect how AI can be aligned with business value, explore the nuances of AI consciousness, and discuss the necessity of thinking like a data scientist in today's fast-evolving tech landscape.Key takeaways:- The Overestimation of AI: Alex Gurbych tackled the common hype surrounding AI capabilities and stressed the importance of understanding its limitations and training.- Challenges in AI Integration: The hurdles encountered when integrating AI into legacy systems and the necessity of defining clear use cases for practical applications were discussed.- AI in Healthcare and Biosciences: The role of AI in drug design and development, protein folding, and target discovery was dissected with a focus on both its potential and limitations.- AI and Consciousness: A fascinating exploration of whether AI can achieve consciousness ensued, with thoughts on the complexity of the human brain and AI's rapid evolution.- Behavioral Change and AI Adoption: The discussion highlighted a case of AI adoption success among technicians versus challenges faced by doctors, showcasing the importance of behavior change driven by AI use cases.- The Role of Data Scientists: The critical investment in data scientists and the growing necessity for everyone to adopt a data scientist's mindset were underscored.Quote from the show:"The biggest challenge is really to define your use case. What do you actually want to get out of AI? And when you have a very crisp definition of that, then it's much easier to actually make it work. But if you just say, oh, I want to use AI because everybody's using AI and it's a hot topic, then it's not going to help you much." - Alex GurbychLinks:LinkedIn: https://www.linkedin.com/in/ogurbych/Website: https://blackthorn.aiThanks to our sponsors: VKTR Earley Information Science AI Powered Enterprise Book

Seth Earley and Chris Featherstone are joined by special guest Bob Levy. Bob Levy, Founder and CEO of Immersion Analytics, brings a wealth of experience in technology and data visualization, having worked with top companies such as IBM, Rational Software, and Mathworks. He shares his profound insights on integrating multidimensional visualization technology using virtual and augmented reality to tackle complex data challenges.Bob Levy is Founder & CEO of Immersion Analytics. With extensive experience in R&D and product management at companies like IBM and Rational Software. Bob is an expert in AI and data visualization. He's been a speaker at prestigious events like MIT Technology Review's EmTech Caribbean and Reilly Strata Data Conference, and has won competitions like MIT's Reality Virtually hackathon and Tableau's DataDev Competition.Key Takeaways:- Examples of how visualization tools help investors make more informed decisions based on a multitude of data attributes.- The transformative potential of VR and AR in business settings and educational environments, backed by partnerships with tech giants like Microsoft and Apple.- Visualization technology as a tool for simplifying the understanding of AI-related compliance and emerging standards.- The discussion on the lack of global compliance standards and the need for potential new standards or refinement of existing ones.- Use cases in derivatives trading, financial performance metrics, and real-time pricing data for detecting anomalies and opportunities.- Innovative ways to visualize artificial neural networks and understand the training processes via VR.- Visualization tools for web and enterprise-level applications, including programming languages and hardware requirements.- The crucial role of visualization in making AI systems comprehensible to non-technical stakeholders like regulators.Quote of the Show:"Seeing all the data points and complexity is crucial for understanding the true nature of the data and avoiding misinterpretation." - Bob LevyLinks:LinkedIn: https://www.linkedin.com/in/boblevy/Website: https://www.immersionanalytics.com/Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-homeApple Podcast: https://podcasts.apple.com/podcast/id1586654770Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/Stitcher: https://www.stitcher.com/show/earley-ai-podcastAmazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcastBuzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Seth Earley sits down with Moritz Müller, a distinguished figure with a rich background in consulting and a leader in artificial intelligence applications. Before carving out his niche at Squirrel AI, Moritz Müller honed his skills at a prestigious consulting firm in Switzerland and spearheaded an ambitious venture by setting up an office in Singapore.As the head of product management at Squirrel, Moritz brings a wealth of experience from digital transformation programs and a deep understanding of AI technologies across various industries. His insights into the burgeoning world of retrieval augmented generation (RAG) and large language models (LLMs) are second to none, offering listeners an in-depth look at the future of information access and management.Moritz brings his expertise full-circle by stressing the importance of metadata, vector similarity searches, and the need for ongoing maintenance of knowledge bases to ensure that emerging technologies truly enhance our search capabilities and knowledge utilization.Key Takeaways- A thorough exploration of retrieval augmented generation and how it's poised to reshape data handling in the digital era.- The importance of ACLs, knowledge graphs, digital body language, and conversational search for personalizing organizational data access.- The need for supervised fine-tuning of LLMs to ensure relevance and accuracy in data retrieval processes.- How to troubleshoot LLM errors and why successful information retrieval is critical for the effective implementation of RAG.- The ongoing challenges and considerations in using AI for effective document search and retrieval within organizations.- The significance of structuring content, tailoring prompts, and understanding the user context to harness the full potential of language models.Quote from the show: "The pairing of information retrieval technology with large language models isn't just a minor improvement; it's a revolutionary step forward. It's about reaching into that vast ocean of data and pulling out the exact details you need – that's the game-changer." - Moritz MüllerLinks:LinkedIn: https://www.linkedin.com/in/moritzbmueller/Website: https://squirro.com/Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-homeApple Podcast: https://podcasts.apple.com/podcast/id1586654770Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/Stitcher: https://www.stitcher.com/show/earley-ai-podcastAmazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcastBuzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Erdem Özcan is an esteemed expert with a rich background in computer science, focusing on innovations in AI. With a PhD in computer science and significant industry experience, including work on IBM's Watson and at Elemental Cognition, Dr. Özcan has been at the forefront of blending symbolic AI and deep learning systems. Today, he is actively engaged in developing solutions that enhance the reliability and explainability of AI applications.Tune in to this enlightening conversation and gain deeper insights into the future trajectories and current challenges within the world of artificial intelligence as explained by one of the leading thinkers in the field.Key takeaways:- Symbolic vs. Statistical AI: Erdem discusses the critical differences and applications of symbolic AI versus statistical methods, emphasizing the need for reliably representing concepts for efficient AI outcomes.- The Role of Cogent English: Insight into how Cogent, a platform developed by Erdem, assists in translating complex business knowledge into APIs and conversational interfaces using a subset of English tailored for formal reasoning.- Challenges in Generative AI: Exploration of issues that arise with generative AI, particularly around reliability and the operational deployment of reasoning systems.- Development of Neurosymbolic AI: Erdem predicts a significant shift towards hybrid AI architectures that combine both symbolic and deep learning approaches to handle real-life complex scenarios more efficiently.- Importance of Explainability in AI: A discussion on why explainability and the ability to audit AI decisions are crucial, especially as AI systems become more integrated into critical decision-making processes.- Comparison of Formal Reasoning Systems and LLMs: Erdem explains why formal reasoning systems can be more reliable than large language models (LLMs) in complex problem-solving scenarios.Quote from the show:"Translating human expertise into AI systems is not just about feeding data into algorithms. It's about creating structures that allow machines to reason and make decisions transparently and reliably." – Erdem ÖzcanLinks:LinkedIn: https://www.linkedin.com/in/aerdemozcan/Website: https://ec.ai/Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Lief Erickson brings expertise in technical writing and content strategy consultation. Having steered numerous organizations through the integration of AI and coherent information architecture, making the complex accessible. With a voice of authority in AI and content management the EIS Podcast is thrilled to have him on the show.Tune in to this episode for a comprehensive understanding of how structured content and precise prompt engineering are pivotal to leveraging AI in the realm of content creation and management.Key Takeaways:- Large language models (LLMs) require clear prompts and structured content to produce accurate and trustworthy responses.- The importance of structured content in enabling effective retrieval and utilization by generative AI, akin to finding a book in a library.- Misconceptions about generative AI's capabilities in content management, highlighting the need for careful curation and validation.- Real-world applications of AI that can help increase brand loyalty, efficiency, reduce support calls, manage risk, and boost revenue.- The emerging role of prompt engineering and its significance in ensuring the relevance and accuracy of AI-generated content.- Legal and ethical considerations in using AI for content creation, with insights on copyright and the ownership issues surrounding machine-generated content.Quote of the Show:"Understanding structured content is like understanding the blueprint of a building—it's what allows us to scale and architect information in ways that align with our strategic goals." - Lief EricksonLinks:LinkedIn: https://www.linkedin.com/in/lief-erickson/Website: https://www.intuitivestack.io/Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Manish Sharma is the co-founder of Resolve AI. With a rich history spanning over two decades in the technology industry, Manish offers profound perspectives on the intersection of artificial intelligence, information architecture, and knowledge management.Tune in as Manish dissects popular AI myths, underscores the importance of bridging the technological gap, and emphasizes the need for robust security measures in today's digital landscape.Key takeaways:- When implementing AI solutions like large language models, CISOs should ask questions around data security, access controls, model guarantees, and emerging risks like prompt hacking to properly manage risks.- Information architecture is critical for data privacy, security, and ensuring AI systems can only access appropriate data sources and provide the right information to different user groups.- Retrieval augmented generation using a knowledge graph or index is important to avoid hallucinations and ensure AI systems can only respond based on curated data sources.- Scripted responses may be needed in some cases like legal to provide verbatim answers instead of generated responses.-  User personas and metadata are important to ensure AI systems understand the context and privileges of different user groups to provide appropriate and non-confusing information.- When integrating AI solutions with knowledge repositories like SharePoint, only curated subsets should be connected instead of entire repositories, and information should be properly tagged and structured.  Quote of the show:"A key to successful AI integration is not just in understanding the technology itself but in grasping the nuances of user needs, processes, content, and knowledge that remains timeless, no matter the advancements in tech. Coming to grips with that is where the real value lies." - Manish SharmaLinks:LinkedIn: https://www.linkedin.com/in/manish-sharma-rezolve/Website: https://www.rezolve.ai/Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Thomas Blumer is a renowned expert in AI-driven transformation with extensive experience in implementing groundbreaking artificial intelligence and knowledge strategies within complex business environments. Echoing a profound understanding of metrics-driven governance of AI systems, Thomas has made significant strides in aligning AI applications with overarching business goals. As a strategic advisor and consultant, he has facilitated diverse organizations in their journey to integrate AI to optimize efficiency, enhance user experiences, and drive actionable business outcomes. His expertise is instrumental in developing robust AI governance frameworks that ensure data, algorithms, and knowledge are in strict adherence to driving value and enterprise strategy.Key takeaways:- Defining and measuring KPIs tailored to customer and user lifecycle is crucial to drive business outcomes with AI and knowledge systems.- The transition from proof of concept to proof of value in AI implementations often encounters hurdles due to artificial environments and upstream data issues.- AI's implementation should focus on improving specific tasks and processes, ensuring tangible improvements rather than the technology's mere presence.- Storytelling and emotional resonance play a pivotal role when data alone does not suffice in persuading stakeholders about AI initiatives.- Governance structures need to strike a balance between centralized standards and decentralized, data-driven decision making.- Large language models have brought about a revolution in accessing corporate knowledge and productivity, highlighting the need for responsible usage.Quote of the show:"Bringing AI into the fold isn't just about technology; it's about shaping an ecosystem that thrives on data integrity, governance, and context to create impactful narratives." - Thomas BlumerLinks:LinkedIn: https://www.linkedin.com/in/thomasblumer/Website: https://www.zyris.comWays to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Trent Fitz holds over 20 years of experience in the tech industry. Currently a C-level Product Strategy and Technical Marketing Leader at Zenoss. He is an expert in global marketing, product strategy, business development in cloud computing, cybersecurity, and AI. Repeatedly proving his effectiveness in the industry by leading solutions to projects in innovative company's such as IBM, Sailpoint, Trustwave and other various startups. Key takeaways:- APM tools such as Dynatrace, AppDynamics, and New Relic are key, and their integration has been aided by standards like open telemetry.- AI governance is crucial on technical, business process, and enterprise strategy levels.- The maturity models for AIOPs involve governance, decision making, and data/information architecture.- There is a general lack of appreciation for data and content within IT organizations.- AIOPs includes machine learning, and there's a need to educate about structured data and AI capabilities.Quote of the show:"At the core of AIOPs lies a fundamental need to not just visualize but truly understand the staggering complexity of modern IT environments. It's not just about piles of data or sophisticated algorithms; it's about cultivating a genuine appreciation for the significance of that data and how we can harness it to drive smarter, more proactive operations." — Trent FitzLinks:LinkedIn: https://www.linkedin.com/in/trent-fitz/Website: https://www.zenoss.comWays to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Ian Hook is an exemplary professional whose journey spanned from an early career as a blacksmith and preschool teacher to becoming a seasoned expert in knowledge management and artificial intelligence (AI) at Nevartis. His unorthodox path and hands-on experience have endowed him with a deep understanding of the intricacies of knowledge management and its pivotal role in leveraging generative AI tools efficiently and effectively within operational teams. Ian's significant contributions have led to remarkable operational efficiencies, including an $18 million savings for his company by centralizing market research resources.Key Takeaways:- Knowledge management and generative AI are integral to improving the speed and accuracy of issue detection and remediation in operational teams.- Understanding the lineage and flow of data is vital for data scientists to fulfill their responsibility effectively.- Ian Hook illustrates the considerable impact of having a centralized knowledge management platform on efficiency and cost savings within a corporate setting.- The importance of governance in the context of utilizing generative AI is highlighted to mitigate unreliable outcomes due to ungoverned data.- Knowledge graphs are presented as sophisticated tools that visualize expertise and the relationships between different domains of knowledge.- The episode explores the limitations of large language models and emphasizes the importance of human oversight to prevent inaccuracies.Quote of the Show:"In our quest to harness AI, we must remember that the texture of human knowledge and expertise is the bedrock upon which these systems must be built." - Ian HookLinks:LinkedIn: https://www.linkedin.com/in/ianhook1/Website: Novartis.comWays to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Mark Pickren currently serves as the President of Next Net Media. With over 25 years of experience as a seasoned entrepreneur and business leader, he possesses expertise in marketing-focused technology companies. Mark has demonstrated a consistent track record of building and managing successful ventures, with leadership experience spanning various industries, including Fintech, SaaS, and Digital Marketing. He has effectively overseen hundred-million-dollar P&Ls at large public corporations and Madison Avenue agencies. Remaining at the forefront of the dynamic digital landscape, Mark consistently delivers innovative solutions for consumers and businesses.Takeaways:Organizations need to prepare for around a 25% decline in organic search traffic as search becomes more personalized. Marketers need to focus on multi-dimensional targeting and providing value to specific customer personas to optimize content for search.As repetitive tasks are automated, career paths will focus more on managing autonomous agents and leveraging AI effectively.  Large language models pose risks if not properly overseen by humans, and differentiation requires responsible use of proprietary data and knowledge.Emerging technologies like retrieval-augmented generation will have major impacts on enterprises by improving information access.Quote of the Show:"Don't be a cynic. Lean into the better angels of technology, and be part of the solution." (Advice for graduates on how to approach emerging technologies.) - Marc PickrenLinks:LinkedIn: https://www.linkedin.com/in/marcpickren/Website: https://nextnetmedia.com/Marc's Website: https://www.marcpickren.com/Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Our guest this episode is Kristina Francis, a Executive Director at JFFLabs. Jobs for the Future (JFF) is a nationwide nonprofit dedicated to reshaping U.S. education and workforce systems for inclusive economic progress.Kristina is a experienced professional with a rich background spanning management consulting, software development, engineering, and cybersecurity. She began in database administration at the American Institutes for Research, evolving from an individual contributor to leading a 120-member development team for the Department of Defense. In 2016, a pivotal moment led to a dual career path, involving founding a consulting company, angel investing in women-owned tech ventures, and engaging in workforce opportunities. Currently serving as the Executive Director for JFFLabs at Jobs for the Future, Kristina  provides a distinctive perspective on the present and future of workforce and education, emphasizing innovation, disruption, and foresight into the implications of emerging technologies.Takeaways:AI has the potential to both disrupt jobs and create new job opportunities, but ensuring access to skills training will be important for workforce development.Personalized learning and career discovery tools that integrate assessments and map out skills pathways could help more people navigate changing job opportunities.Addressing systemic barriers and biases will be important to ensure all populations can benefit from new economic opportunities.Regions and employers can play a role in workforce development through public-private partnerships, on-the-job training programs, and investing in employees' skills.Quote of the Show:" How do we get more innovators, school systems, programs, and employers to get on board and provide the support and systems needed so that everyone in our communities is able to discover and navigate through our system to achieve their highest potential? "- Kristina FrancisLinks:LinkedIn:https://www.linkedin.com/in/kristinaharrisonfrancis/Website: https://www.jff.org/Email: KFrancis@JFF.orgWays to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/  Thanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Our guest this episode is Alexander Schober, a data & AI project owner at Motius. He manages a diverse team of tech experts, focusing on Machine Learning, Knowledge Graphs, and Data Analysis. Alexander previously worked at Siemens Technology which involved pioneering research in Federated Learning and Self-Supervised Methods for anomaly detection. He used algorithms like Federated Averaging and SimCLR to address data privacy and label sparsity. Alexander joins Seth Earley and Chris Featherstone to the discuss knowledge graphs, metadata modeling for data engineering, using large language models to build data pipelines and more.For more content related to LLM's and Knowledge Graphs: https://www.earley.com/case-studies Takeaways:AI Enhancements with Knowledge Graphs: While not strictly required, knowledge graphs enhance the capabilities of AI, particularly large language models. The ability to provide context and resolve conflicts within the data contributes to more accurate and reliable AI outcomes.Unified Metadata Model: There's a need for a unified metadata model across different tools and platforms in the data engineering and AI landscape. Disjointed metadata tools can lead to inefficiencies, and efforts should be made to integrate and unify metadata for better collaboration.AI-Powered Data Pipeline Construction: Large language models can be used to generate data pipelines based on provided metadata. This approach can streamline the data engineering process, ensuring that quality checks, governance attributes, and privacy classifications are integrated into the pipeline.Quote of the Show:" All of these things are interconnected. Knowledge graphs, ontologies and semantics. They are all very important."                    - Alexander SchoberLinks:LinkedIn:https://www.linkedin.com/in/alexander-schober/Website: https://www.motius.comWays to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Today's guest is Rachad Najjar, working the forefront of innovation in the fields of organizational learning and knowledge management for nearly a decade. Prior to this, he served as a knowledge management advisor for the Dubai Land Department, where he played a pivotal role in achieving the EFQM Excellence Award. Notably, he's also a co-author of a recent book on knowledge management and research innovation, alongside numerous scientific publications in prestigious journals. In his ground breaking thesis, he introduced a framework to configure collaboration for virtual collectives, improving effectiveness across various professional contexts. Rachad joins Seth Earley and Chris Featherstone to the discuss his insights on AI, knowledge management, enterprise strategy implementation and more.Takeaways:Seven guiding principles for a successful AI strategy, including a strong business case, process integration, quality training data, continuous supervision, powerful computing infrastructure, and AI and ML skills.AI governance should involve diverse expertise, including legal, supply chain, project management, and knowledge management.Focus on how generative AI is adding value in knowledge management and learning, particularly in areas such as customer support, search, learning, and marketing.Quote of the Show:"AI models heavily depend on the quality of the training data, so quality in and quality out."              - Rachad NajjarLinks:LinkedIn: https://www.linkedin.com/in/rachadbn/Article: 7 Guiding Principles of a Successful Enterprise AI StrategyArticle: A conversation between a knowledge sharing advocate and a knowledge sharing skepticArticle: AI Integration Strategy for Learning and Knowledge Management SolutionsWays to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Today's guest is Amar Goel, founder of Bito. Amar joins Seth Earley and Chris Featherstone to the discuss the increase in new A.I. tools, LLMs and the journey behind forming Bito! The A.I. assisted software developing tool. Takeaways:Converting AI prototypes into reliable, production-ready products is a non-trivial task, often requiring significant effort and expertise.AI has the potential to assist developers in various ways, from code refactoring to code migration, helping to address issues related to legacy code and modernization.The cost of running AI models can be significant, and businesses need to consider the expenses involved in deploying AI tools in their products and services.AI can play a pivotal role in streamlining developer processes, such as enhancing code quality, security, and test coverage, while allowing developers to maintain their creative freedom. However, it's essential to strike a balance between automation and creativity in the development process.Quote of the Show:"We don't know what we don't know yet" about AI ethics and privacy, as everyone is learning on the job." - Amar GoelLinks:LinkedIn:https://www.linkedin.com/in/amargoel/Website: https://https://bito.ai/Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors:CMSWireEarley Information ScienceAI Powered Enterprise BookThanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Today's guest is Sanjay Mehta, Head of Industry Commerce for LucidWorks. Sanjay joins Seth Earley and Chris Featherstone to the discuss the rapidly evolving hype of generative AI and how it can be applied to your industry.Takeaways:Sanjay points out that emerging AI is "not turn key". Maybe from a consumer side but when it comes to B2B there are many hoops to jump through before it's easy and effective.Data is the lifeblood of modern businesses, and its true potential shines when we connect the dots between customer behaviors, product attributes, and user experiences. At the heart of this transformation is the concept of ingesting good product data into the vector space.There are many preceded knowledge graphs for certain industries. When you build your index of data it is important to know your users context and application. Using a knowledge base to build your own vector space can be helpful. Quote of the Show:“AI is Not Turn Key" - Sanjay MehtaLinks:LinkedIn:https://www.linkedin.com/in/sanjaymehta/Website: https://lucidworks.comWays to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Today's guest is Doug Kimball, Chief Marketing Officer for Ontotext .  Doug joins Seth Earley and Chris Featherstone to the discuss the rapidly evolving world of knowledge graphs and AI.Takeaways:Doug Kimball's statement about knowledge graphs being an "add to" and an "enhancement of" data is spot on. In the world of modern data management and analytics, knowledge graphs are a game-changer.There is a proper way to ask the right questions when communicating with Generative AI models. It is important to include the correct context and parameters.Knowledge graphs have many applications to a variety of different business models and use cases. Doug mentions an example where a mass migration of population from one place to another could be an opportunity for businesses to track and profit based off of user demographics utilizing knowledge graph practices.Quote of the Show:“Knowledge graphs are not a rip and replace, they are an add to/enhancement of" - Doug KimballLinks:LinkedIn:https://www.linkedin.com/in/dougkimball/Website: https://www.ontotext.com/Twitter: https://twitter.com/TheDKimballWays to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors:Marketing AI InstituteCMSWireEarley Information ScienceAI Powered Enterprise BookThanks to our sponsors: CMSWire Earley Information Science AI Powered Enterprise Book

Today's guest is Ben Clinch, Head of Information Architecture for BT Group .  Ben joins Seth Earley and Chris Featherstone to the discuss the rapidly evolving world of data science in organization. Takeaways:An intriguing aspect is the common practice of Large Language Models (LLMs) utilizing generic data models Ben and Seth discuss more effective ways to harness the power of LLMs through specialized data models and organization.Companies will realize quickly that they cant do any sensible Generative AI without a core of useful referential data to utilize, train and not hallucinate.If people lean on Generative AI, that accelerates things rapidly, but all it does is deferring knowledge to somebody else's data model.Some people ask if we really need a data model.  Can't we just get an industry standard view and follow that?  Do you want to buy an org chart?  Do you want to defer how you structure your teams to somebody else's view of how you should?  This may be a good starting point, but a terrible ending point.What is the ROI on data modeling?  Think of data as an asset for your organization, and think of people as an asset for your organization.  Everybody from the chairman to the guy sweeping the floor understand an org chart. They understand you have to organize your people.  Otherwise, there will be involuntary anarchy.Quote of the Show:“Taxonomy is a chart of accounts for knowledge" - Seth EarleyLinks:LinkedIn:https://www.linkedin.com/in/benclinch/Website: https://www.bt.com/Twitter: https://twitter.com/BritishTelecom Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

Today's guest is Glenn Gow, CEO of Coaching at The Peak Performance CEO Coach. Glenn joins Seth Earley and shares how people should start leaning into what technology is advancing today. Glenn expresses the importance of learning these new materials to create opportunities for you and your company. Be sure to listen in on Glenn giving his advice on how larger companies should incorporate AI into their business!Takeaways:Glenn believes that the enhanced value that Predictive AI and Analytical AI can bring to CEOs can create a crucial aspect of the evolution. By harnessing AI approaches, CEOs can gain insights that can drive decision-making and strategic planning. Glenn advocates for adopting AI methodologies to empower CEOs in navigating the rapidly evolving business landscape.Glenn created a concept known as "Winner Takes All." This concept is if you excel in AI, both you and your direct competitor will consistently accumulate data about your customers. This resource empowers you to gain insights into your customer base, enabling you to enhance your understanding and knowledge. The stakes are high, as falling behind your competitor could lead to setbacks and missed opportunities.An example of the vast impact Chat GPT and AI have on our world is Chegg—software designed to provide students with vital information to excel in school. However, when Chat GPT came to light, the AI world dramatically shifted. In a single day, the creation of Chat GPT caused Chegg's stock to plummet by 45%. Today, AI is globally, revolutionizing to assist with education, essay writing, tests, and countless other domains. Its pervasive influence continues to reshape the way we approach and engage with knowledge.Glenn believes enterprises will find it effortless to gather information about open-source technologies their competitors developed. By integrating the resources into their frameworks and incorporating their data, businesses will gain access to carry out operations within their competitors' organizations that were once beyond their reach. Glenn thinks people should take advantage of these opportunities to safeguard their data.Glenn describes prompting by taking a large language model and condensing it to a specific area of focus. This act of shrinking allows the model to channel toward a defined domain or subject matter. By honing the model's attention on a particular area, it targets outputs that align with the desired scope. This makes it simple for users to leverage the language model while meeting specific objectives.Quote of the Show:“Become good at all the tools that are being made available to us, because that's going to create opportunity for you.” - Glenn GowLinks:LinkedIn: https://www.linkedin.com/in/glenngow/ Website: https://www.glenngow.com/ Twitter: https://twitter.com/glenngow1 Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: Thanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

Today's guest is Kirk Marple, Technical Founder and CEO at Unstruk Data. Kirk joins Seth Earley and Chris Featherstone to  discuss organizing historical data and long-term memory. Kirk emphasizes the importance of organizing data in a manner that allows for seamless integration with novel models and shares valuable advice on understanding data. Takeaways:The semantic web serves as a powerful tool for optimizing business applications and data organization.  A prevalent misconception surrounding AI is that individuals need to construct their own models and be data science experts. Advancements unfold at a rapid pace. People need to harness the power of AI and employ it strategically within their business operations.Data lies at the core of everything. To optimize the utilization of emerging models effectively it is important to organize data in a way that seamlessly integrates with novel models. AI implementation needs to be approached with a practical mindset.  In the last 6-9 months large language models have developed the ability to engage in meaningful conversations with their underlying data. This aspect of interactive communication tends to be overlooked. The focus often leans towards retrieval and entity extraction.Over the years, people have addressed the issue of non-equalization of data intent through the provision of taxonomies. In the future Kirk anticipates that AI will play a pivotal role in enhancing this process. Quote of the Show:“It's a data set. Not just a hard drive.” (03:50)Links:LinkedIn: https://www.linkedin.com/in/kirkmarple/ Website: https://www.unstruk.com/ Twitter: https://twitter.com/unstruk Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

Today's guest is Alex Babin, Co-Founder and CEO at ZERO Systems. Alex joins Seth Earley and Chris Featherstone to share two of the biggest misconceptions of AI and a  new AI metric data tool. Using AI to track data improves performance. Takeaways:The biggest misconceptions about AI are:AI can work out of the box. ChatGPT shows people what it can do but that doesn't mean that AI can do everything.You can throw data at AI and it will execute your needs perfectly.  AI technology is changing, but it hasn't met this level of expertise yet.A best practice to avoid these misconceptions of AI is to start from the beginning. Figure out your company's ROI and reconstruct all the steps required.There's a new layer of metric data that has never existed before,  user-generated data or a feedback loop. As you interact with a tool a new type of metadata is born. As you feed more data and information to the tool it creates a data flywheel.Ontologies don't always overlap to give a full understanding. AI can be a stitching mechanism to join two ontologies that should be communicating. You can use AI to Alex explains how the two ontologies aren't connected. Fortune1000 companies can use AI to use data more effectively. Organizations need end-to-end solutions. An enterprise-scale solution doesn't exist right now. They're using fragmented solutions and piecing it together.Interconnecting data and compartmentalizing it can lead to end-to-end solutions, skilled AI models (SAMs).  AI is an arms race right now. The focus is on making things bigger, faster, and more powerful. Without governance it can be dangerous. We need to collectively figure it out. Quote of the Show:“Throwing ChatGPT on top of your problems will not solve it.” (04:51)Links:LinkedIn: https://www.linkedin.com/in/alexbabin/ Website: https://zerosystems.com/ Twitter: https://twitter.com/zeromailapp?lang=en Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

Today's guest is Maxim Serebryakov, Co-Founder and CEO at Sanas. Max joins Seth Earley and Chris Featherstone and shares what influenced him to start his company. Max discusses what it was like to study artificial intelligence at Stanford and how it created a broad perspective on how things work. Max believes if you go above and beyond you can help anyone. Takeaways:Max was born in New York, moving back to Russia where his family is from as a child. When he returned to the United States, hearing the accents around him led to the creation of his company, Sanas.Artificial intelligence shows the limitations of modern-day voice conversion research. You're not just modulating the pitch and tone, you're changing the underlying phonetics that are present within it.Initially, they chose to deploy Sanas in contact centers and enterprises because speech is very structured. Sanas helps large companies improve customer service interactions which is crucial to their service.Quote of the Show:“We ended up building an algorithm that really doesn't exist in the research world. It's very innovative. It works on the edge, works with clients, and it's very efficient.” (11:02)Links:LinkedIn: https://www.linkedin.com/in/maximser/ Website: https://www.sanas.ai/ Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

Today's guest is Michael Todasco write extensively about Generative AI. Mike joins Seth Earley and Chris Featherstone to discuss all things generative AI and why people should embrace AI.  He also shares valuable advice on how to build a better connection with your customers.Takeaways:While he was at PayPal, Mike was responsible for innovation and improving employee performance. Embrace AI. Working with AI will result in better solutions.It is important for everyone to know what their competitive advantage is and what their end goal is.One great way to get proprietary information about your customers is to stage a gated experimentation process.One of Michael's experiments was writing a book using an Excel spreadsheet. He took what was written in Excel and pasted it into ChatGPT to craft 56 different writing genres. Quote of the Show:“Your job is not going to be replaced by AI. It's going to be replaced by a human who's using AI.” (08:17)Links:Twitter: https://twitter.com/todasco LinkedIn: https://www.linkedin.com/in/todasco/ Website: https://medium.com/@todasco Ways to Tune In:Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

Today's guest is Gordon Hart, Co-Founder and Head of Product at Kolena. Gordon joins Seth Earley and Chris Featherstone and shares how ​​machine learning algorithms are a challenge from different perspectives. Gordon also discusses the core problem in his company before they turned it around. Be sure to listen to Gordon's advice on how to validate models in order to have a successful product!Takeaways:Gordon noticed that developing algorithms internally or buying from other model vendors has really had a constant unexpected model behavior. It made him feel he couldn't trust the models to behave sensibly. Gordon started his company because he noticed that time after time, he was getting blindsided. He knew there was a better way to develop models and validate what they were doing. The key challenge that Gordon and his team ran into was that when you have all the data when they were looking at that one number, they were looking at that aggregate metric computed across their entire benchmark.Gordon expresses the importance of going through scenarios with your products. He found that when you break down your evaluation into these different scenarios, the test gives you an understanding of how this model improves in the aggregate over previous models and how are the failures distributed.Testing data is more critical than training data because your testing data is used to determine if your new model has the correct behaviors.Testing the full pipeline from pre-processing through post-processing rather than testing the model component will oftentimes improve the visibility into how your product is actually going to work when you put it out there.Quote of the Show:“Having your evaluation metrics align with the way that your system is going to be evaluated in the field is a key thing that you can do to get a better understanding of ‘is this model better for what I set out to do?'” (22:36)Links:Twitter: https://twitter.com/kolenaIO LinkedIn: https://www.linkedin.com/in/gordon-hart/ Website: https://www.kolena.io/ Ways to Tune In:Website: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

Today's guest is Daniel Faggella, Head of Research and CEO at Emerj Technology Research. Dan joins Seth Earley and Chris Featherstone and shares how martial arts influenced him to get into artificial intelligence. Dan also discusses what his experience was like with surveillance technology creation technology. Dan had a machine that could generate the next 10 slides of your desired moving picture. Be sure to listen in on Dan giving his advice on how you should properly use open AI!Takeaways:Dan got into artificial intelligence by practicing the martial art, Jujitsu. He started a Jujitsu gym which helped support him when he was in school. Jujitsu helped motivate him and keep his mind balanced.Dan mentions how generative AI has been starting to bubble up since the spark of ChatGPT. He sees people starting to experiment with social and proposals. With AI in general, people are looking at junctures within the workflow. Identifying junctures where can push a button will lead to streamlined deliverables.Generative AI finds the juncture pockets and knows exactly where those settle in.Dan speculates that people will evolve their use of ChatGPT and structure different FAQs.Dan believes that one day we'll use Generative AI to create a feedback loop allowing humans to say what's wrong and what's right to train AI systems.Quote of the Show:“The dust has yet to settle on the early cluster of those use cases in Generative AI.” (19:06)Links:Twitter: https://twitter.com/danfaggella LinkedIn: https://www.linkedin.com/in/danfaggella/ Website: https://emerj.com/ Podcast: The AI and Business PodcastArticle: Lotus Eaters and World EatersWays to Tune In:Website: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbE?si=73cd5d5fc89f4781 iHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/ Thanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

Today's guest is Michelle Zhou, Co-Founder and CEO at Juji, Inc. Michelle joins Seth Earley and Chris Featherstone and dives into what proprietary data is and how it can be used correctly. Michelle also discusses the one lesson she has learned is that you have to build a product that can help people. You want to achieve your customers' outcomes, not your outcomes. Be sure to listen in on Michelle giving her advice on how to pick out the golden nuggets in AI data to show a coherent and meaningful summary!Takeaways:When Michelle first started with computer science, she wasn't fond of it until she attended Michigan State University where two professors changed her perspective on computers. They gave her the opportunity to work on building graphical user interfaces for power management and worked on projects that dealt with AI data storytelling.Michelle explains that the AI data storyteller gives a set of data and tasks of the user which then gives the user visual preferences. It also consists of a series of animated data visualization.During Michelle's first 15 years of research, she was working on understanding users in a task context. For example, what their tasks are, what they're looking for, what their visual preferences are, and what their verbal preferences were.Michelle has noticed a lot of students will strive for a degree that their family has done in the past. Michelle says that you don't always have to follow any degree you don't want. There are so many unique degrees to pick from.Michelle believes that transparency drives responsibility and since they have a powerful AI system, she wants to make sure that they use their AI in a responsible way.The one lesson Michelle has learned is that you really have to build a product that can help people. Make sure to achieve your customers' outcomes and not yours. You don't want to waste their time.Quote of the Show:“I want to really democratize the use of this cutting-edge technology.” (23:41)Links:TwitterLinkedInWebsiteWays to Tune In:Website Apple PodcastSpotifyiHeart RadioStitcherAmazon MusicBuzzsproutThanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

Today's guest is Juan Sequeda, Principal Scientist at data.world and Co-Host of the Catalog & Cocktails Podcast. Juan joins Seth Earley and Chris Featherstone and shares how to understand the problem that you are trying to solve. Juan also discusses how your company's success should be defined differently. Don't focus on just on saving money to make money. Focus on solving a problem.  Juan also shares valuable advice on how understanding who you report to helps you speak the same language.  Takeaways:Juan believes the market is immature when it comes to what they want or what they think they want. This is where data catalogs become important so that companies can locate information. From the perspective of the data management world, it's focused on only technology. The problems that they had been trying to solve 30 years ago continue to be the same problems they've been trying to solve.If you are on the technical side of your business, it is important to understand who you should be reporting to. Understanding this early on will help you tailor information to meet the correct outcome. Juan's definition of a knowledge graph is representing real-world concepts and the relationships between those real-world concepts end up forming a graph. The reason why the graph is really valuable is because you can integrate data coming from many diverse sources.Quote of the Show:“Keep working on the same vision.” (07:50)Links:TwitterLinkedInWebsitePodcast: Catalog & Cocktails presented by data.worldJuan's Portfolio Book: Integrating Relational Databases with the Semantic WebWays to Tune In:WebsiteApple Podcast SpotifyiHeart RadioStitcherAmazon MusicBuzzsproutThanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

In this episode, our guest is Andy Fitzgerald and Information Architecture & Content Strategy Consultant.Highlights:1:40 - Getting from Ph.D. in English and Literature in information architecture and knowledge graphs9:23 - Schema.org14:30 - How can we get search to be like "Google"?19:00 - The trouble with self-organizing information20:40 - The KFC debacle in Germany and case for keeping humans in the loop22:15 - Knowledge graphs and AI29:35 - Role of linguistics33:00 - What happens when you don't apply knowledge graphs to AI projects37:00 - Boutique knowledge graph - UXMethods.org48:00 - Value of smaller scale knowledge graphs and simplicityLinks:Connect with Andy on Linkedinandyfitzgeraldconsulting.comUX Methods - a community powered, linked data driven knowledge graph for learning about the techniques of user experience design.Jim Hendler's papersGall's Law Thanks to our sponsors:Marketing AI InstituteCMSWireEarley Information ScienceAI Powered Enterprise BookThanks to our sponsors:Marketing AI InstituteCMSWireEarley Information ScienceAI Powered Enterprise BookThanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

In this episode, Seth and Chris talk with Peter Voss,  Founder, CEO, and Chief Scientist at AGI Innovations & Aigo.ai.Highlights:2:58 "Software is quite dumb"3:51 "What is reality?"5:00 Coining the phrase "Artificial General Intelligence" - what it means9:00 On understanding cognition in the deepest terms11:10 What is consciousness?15:20 Difference between "Artificial Intelligence" and "Artificial General Intelligence"19:00 The 3 waves of AI29:45 What is cognitive architecture?34:30 Quality of data vs quantity of data38:00 Practical applications for building personalization systems39:20 What can organizations do to prepare for AI driven systems?46:30 One corporate bot or multiple bots?53:45 Automation should be able to deliver the superior customer experience, not the cheaper second class optionLinks:Connect with Peter on LinkedinVisit the Aigo.ai websiteThanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

In this episode, Seth and Chris talk with Dan Turchin, CEO & Founder of PeopleReign.Highlights:4:30 What drives Dan's mission to impact a billion lives at work? 11:15 Disruption and the future of work17:50 What will happen when people can have a day a week back from automation?20:00 Work will change more in the next 30 years than in the previous 30024:30 AI is really still in its infancy - how can we use it for good as it grows up?29:00 What are the pre-requisites to success with AI?37:50 How do you sell the business on the need to address their data?43:00 Choosing use cases to get started with51:00 What's next?Links:That episode of his podcast with Seth that Dan mentionshttps://peoplereign.io/2022/09/seth-earley-author-of-the-ai-powered-enterprise-discusses-the-future-of-knowledge-managementDan's LinkedIn Profilehttps://www.linkedin.com/in/dturchin/PeopleReignhttps://peoplereign.io/ Thanks to our sponsors:Marketing AI InstituteCMSWireEarley Information ScienceAI Powered Enterprise BookThanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

In this episode, Seth and Chris talk with Dr. Mark Maybury, former CTO with Stanley, Black & Decker.Highlights:3:30 Mark's early influences9:10 What he does with his "spare" time - it is planned16:30 His experience at Stanley, Black & Decker - making the elephant dance22:50 Transitioning from analog to mixed reality (physical and digital)31:00 AI - doing the early foundational work without existing ML systems40:00 Early development of sentiment and intent analytics45:00 Future projects including movie project getting students excited about careers in AI in the service of the public good48:45 Ready Robotics51:00 Development of a COVID De-activization protocolLinks:LinkedIn Profilehttps://www.linkedin.com/in/dr-mark-maybury-28532/Ready Roboticshttps://ready-robotics.com/ Thanks to our sponsors:Marketing AI InstituteCMSWireEarley Information ScienceAI Powered Enterprise BookThanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

In this episode, Seth and Chris talk with Steve Stesney, Senior Product and Data Practice Lead at Predictive UX. Highlights:3:30 What is predictive user experience and how did Steve get there?5:30 Grasping disambiguation and the move to graph data18:00 Building trust in the data19:26 Explaining taxonomy, ontology and knowledge graph to executives21:30 Connecting UX and knowledge graphs28:00 Managing the open floodgates once users discover what knowledge graphs can do36:30 What is "predictive ux" ?Links:LinkedIn Profilehttps://www.linkedin.com/in/stephenstesney/Websitehttps://www.predictiveux.com/ Thanks to our sponsors:Marketing AI InstituteCMSWireEarley Information ScienceAI Powered Enterprise BookThanks to our sponsors: Marketing AI Institute CMSWire Earley Information Science AI Powered Enterprise Book

In this episode, Seth and Chris talk with Scott Taylor, the "Data Whisperer" about telling stories about data management.Highlights:2:00 Data Whisperer origin story9:30 Translating complex dry material into a story that resonates11:30 Why master data is the most important data and how to help execs understand it18:15 Bad data + AI = AS (Artificial Stupidity)22:30 Every system demos perfectly26:25 Don't say "data quality"27:30 Definition of digital transformation32:00 Ugly babies and the reality of bad data38:30 About the book, "Telling Your Data Story" 99% buzzword free (coupon code in show notes)47:00 Data management is macro trend agnostic49:00 What's next - more puppets and dad jokes52:00 Influencing the next generation of data managersLinks:LinkedIn Profilehttps://www.linkedin.com/in/scottmztaylor/Website www.MetaMetaConsulting.comBOOKTelling Your Data Story  - Data Storytelling for Data Management20% off with code: DATAWHISPERER (publisher site only)https://technicspub.com/data-storytelling/Top ContentToo Much Tech Talk?  (A puppet service announcement)The Little Red Data Hen - A Cautionary TaleConnecting Data Management to the Essence of Your BusinessData Has Got to Move to Have ValueThe Super Hero Adventures of **Master Data** Scott Taylor - The Data Whisperer YouTube Channel Thanks to our sponsors:Marketing AI InstituteCMSWireEarley Information ScienceAI Powered Enterprise Book

In this episode, Seth and Chris talk with Henrik Hahn about driving innovation and change in his role as Chief Digital Offer at global chemical specialty giant, Evonik.Highlights:12:30 Organizational change and culture science14:30 Augmented intelligence vs artificial intelligence20:00 On deciding where to start29:00 Using data to measure success39:00 Organizational design44:00 Dealing with information gatekeepers48:30 What kinds of tools are getting best traction52:00 Lessons learned while tackling big changeLinks:https://corporate.evonik.com/enhttps://www.linkedin.com/in/henrik-hahn/Thanks to our sponsors:Marketing AI InstituteCMSWireEarley Information ScienceAI Powered Enterprise Book