Earley AI Podcast Seth Earley & Chris Featherstone

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 Müller


Links:

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-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

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 Özcan


Links:

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 Erickson


Links:
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 Sharma

Links:
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 Blumer

Links:
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 Fitz

Links:
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