Earley AI Podcast

In this episode, Seth and Chris talk with Linda Andersson, Founder & CEO of Artificial Researcher about AI powered semantic search.Highlights:5:00 - Linda's journey to her work14:20 - Domain knowledge and ontologies17:07 - Knowledge extraction20:05 - Why we need ontologies20:50 - Bias and not knowing what you don't know25:40 - Structuring and curating the knowledge base30:00 - Supervised vs semi-supervised models38:15 - What is Academia missing 43:30 - Getting the right start for AI projectsLinksInformation about Artificial Researcherhttps://artificialresearcher.com/ www.linkedin.com/company/artificialresearcherDemo pages for index and the ontologies generated by the Artificial Researcher Data pipeline solution:https://passageretrieval.artificialresearcher.com/ https://graph-demo.artificialresearcher.com/Contact Linda:https://www.linkedin.com/in/linda-andersson-76483916/https://calendly.com/artificial-researcherThanks to our sponsors:Earley Information ScienceCMSWireMarketing AI InstituteThanks 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: 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: https://podcasts.apple.com/podcast/id1586654770 SpotifThanks to our sponsors: 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: 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: 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: 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: CMSWire Earley Information Science AI Powered Enterprise Book