Earley AI Podcast

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shaped by their environments and practices.Challenges with Legacy Systems:  Accessing and modernizing data from outdated systems adds complexity to organizational workflows, necessitating a fine balance between old and new technologies.Retrieval Augmented Generation (RAG):  The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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI 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: VKTREarley Information ScienceAI Powered Enterprise Book