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and discerning between vendors' aspirational capabilities and reality.- Traditional long-term technology planning is no longer applicable in the age of AI and large language models (LLMs) due to the unpredictable nature of AI's uses and leveraging capabilities.- Executives should personally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: VKTR Earley Information Science AI Powered Enterprise Book

Moritz Müller, a leader in AI applications, discusses the future of information access with retrieval augmented generation and large language models. He highlights the importance of metadata, vector similarity searches, and supervised fine-tuning for accurate data retrieval. The podcast explores personalized content, semantic search engines, and enriching embeddings to enhance language model accuracy. It ends with insights on how retrieval augmented generation will revolutionize AI innovations in the coming years.

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: VKTR 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: VKTR 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: VKTR 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: VKTR 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: VKTR 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: VKTR Earley Information Science AI Powered Enterprise Book