Talking AI

In this episode, host Matt Paige talks with Nate Jones, a long-time AI expert and popular TikTok personality, about how AI is changing. They discuss how new reasoning models and design approaches are making large language models more than just advanced autocomplete tools.

They dive into how these models work by taking time to “think” through a problem. Nate explains that techniques like chain-of-thought and tree-of-thought allow AI to process more information before answering. They also touch on the importance of tokens and compute power, showing how these factors are changing software development and product design.

The conversation wraps up by looking at the bigger picture. Nate and Matt talk about the need to work with AI while keeping our own critical thinking skills sharp. They share personal stories, including how Nate teaches his daughter to use AI wisely, and invite listeners to explore more of Nate’s content on TikTok, Substack, and YouTube.

Key Moments:

• Changing AI Adoption Habits
• Voice Agents and Nuance
• Collaborating with AI in Daily Tasks
• Revolutionizing Product Discovery
• Exploring AI Reasoning Techniques
• Tokens: The Building Blocks of AI
• Inference and Compute Economics
• Debating AI vs. Human Intelligence
• AI in Education and Everyday Life

Key Links:

• Rockerbox's Website
• Connect with Nate Jones on LinkedIn
• Watch Nate Jones on YouTube
• Follow Nate Jones on TikTok
• Nate's Substack

Mentioned in this episode:

AI Opportunity Finder

Feeling overwhelmed by all the AI noise out there?

In this episode, host Matt Paige sits down with AI expert Andreas Welsch to talk about how companies can turn AI hype into real business value. Andreas shares his experience working with big enterprises and stresses the importance of training teams to use AI effectively. He explains that success in AI isn’t just about using new tools—it’s about better leadership and smarter integration into everyday work.

They discuss practical ways to boost AI skills through “social blended learning,” which mixes quick lessons with hands-on practice. Andreas also talks about the evolving role of the chief AI officer, who helps bridge the gap between tech and business, and shares thoughts on the future of AI agents and prompt engineering in transforming traditional work.

Looking ahead, the conversation covers how AI tools are becoming more accessible and powerful, making it easier for anyone in an organization to experiment and innovate. The discussion highlights the need for clear strategies and training, ensuring that technology supports real business outcomes while preparing teams for a changing work environment.

Key Moments:

• The Importance of AI Literacy
• Social Blended Learning Explained
• Empowering Teams with AI Tools
• The Rise of the Chief AI Officer
• AI Leadership as a Transitional Role
• Unlocking Potential with AI Agents
• Shifting from Software to Service
• Orchestrating AI Across Departments
• Human-Centered AI Design

Key Links:

• Andreas' Website
• Connect with Andreas Welsch on LinkedIn

LinkedIn Learning Courses:

• Agentic AI: Challenges and Opportunities for Leadership
• AI Agents: Preparing Your Organization for Change as a Business Leader

Mentioned in this episode:

AI Opportunity Finder

Feeling overwhelmed by all the AI noise out there?

How can high-reliability organizations transform their data from flat, 2D spreadsheets into a dynamic, 3D world of interconnected insights? In the Season 4 premiere of the Talking AI podcast, host Matt Paige dives deep with Jon Brewton, Founder & CEO at data², and Daniel Bukowski, CTO at data², to explore how leveraging knowledge graphs and AI is revolutionizing data transparency and explainability.

Jon and Daniel share their journey from traditional analytics to building a modular, cloud-agnostic, zero-trust AI platform that empowers industries such as defense, intelligence, energy, finance, and healthcare. They break down the core concepts of graph databases versus relational systems, discuss how graphs provide the connective tissue needed to support AI-driven decision making, and reveal how integrating LLMs with structured graph data can overcome challenges like hallucinations and unreliable outputs.

Learn how data² is transforming complex data into contextualized, three-dimensional insights that not only answer hard questions but also elevate the work of analysts and decision-makers. Whether you’re curious about how to improve data reliability or interested in the future of AI-augmented workflows, this episode is packed with practical insights and forward-thinking strategies.

Key Moments:

• The data² Journey: From Flat Data to Graphs
• Demystifying Knowledge Graphs & Their Value
• Graphs vs. Relational Databases: What’s the Difference?
• Integrating LLMs with Graph Data for Better Accuracy
• Transforming 2D Data into 3D Insights
• Real-World Use Cases in High-Reliability Industries
• Empowering Teams with Transparent, Explainable AI
• The Future of AI-Driven Analytics

Key Links:

• Data²
• Connect with Jon Brewton on LinkedIn
• Connect with Daniel Bukowski on LinkedIn

Mentioned in this episode:

AI Opportunity Finder

Feeling overwhelmed by all the AI noise out there?

Don't want to get behind an AI? You're in luck! Season four of the Talking AI podcast is almost here, and we're gearing up to bring you even more in-depth conversations with the pioneers shaping our future. This season, prepare to dive into the minds of AI startup founders, enterprise AI leaders, and some of the top voices in the field.

What to Expect:

• Expert Insights: Hear from the innovators and early adopters who are redefining what’s possible with AI.
• Bonus Episodes: Enjoy special bonus content featuring our CTO, Omar Shanti, who will deep dive into specific topics, tools, and approaches that are revolutionizing the industry.
• Diverse Perspectives: Whether you’re an AI aficionado or just starting to explore the landscape, our lineup of guests will offer valuable insights tailored to every level of interest.

While you wait for season four to drop, be sure to subscribe on your favorite podcast platform so you never miss an episode. Seriously, go do it!

Key Links:

• Talking AI

Get ready to talk some AI—Season 4 is coming soon!

How can organizations ensure that their data pipelines deliver consistent, trustworthy insights without frequent disruptions? In this episode of the Talking AI podcast, host Matt Paige co-host Omar Shanti, CTO of HatchWorks AI, speak with Andrew Jones, Principal Engineer at GoCardless, about the concept and practice of data contracts. Andrew explains what data contracts are, why they emerged, and how they improve data reliability and collaboration.

The discussion explores how data contracts relate to data mesh and platform thinking, helping teams share responsibility for data while maintaining clear standards. Andrew and Omar share examples of data contracts addressing issues like schema changes, governance, and data quality.

They also consider how data contracts support AI initiatives by ensuring that the data feeding into models is accurate and reliable. Practical steps are given, including starting with a clear problem and involving the right people.

Andrew provides resources for deeper learning, including his book and online materials. Matt and Omar also mention an upcoming webinar on data contracts, inviting listeners to learn more and move toward more structured, dependable data practices.

Key Moments:

• Introduction to data contracts and their purpose
• Highlighting the common reliability issues that data contracts can prevent
• Linking data contracts to data mesh and other modern data architectures
• Exploring how data contracts help maintain governance and compliance
• Demonstrating how data contracts ensure quality for AI-driven applications
• Discussing platform thinking and its role in scaling data contract implementations
• Offering practical advice on how to begin using data contracts in your organization

Key Links:

• Connect with Andrew on LinkedIn
• Connect with Omar on LinkedIn

Mentioned in this episode:

AI Opportunity Finder

Feeling overwhelmed by all the AI noise out there?

How is the growing world of AI agents reshaping enterprise systems? In this episode of Talking AI, host Matt Paige is joined by Praveen Gunasekaran, Senior Director and Chief Architect at Visa, and Omar Shanti, CTO of HatchWorks, to explore the possibilities of agentic systems and their impact on software development.

Together, they look at the power of agentic systems—technologies that can autonomously make decisions and execute changes in business processes without human intervention. This shift from deterministic to probabilistic systems opens up new opportunities for software developers to create more dynamic and responsive products.

One of the key points in this episode is that agentic systems could help to democratize access to tech, enabling people with minimal coding experience to harness more advanced tools. But with that comes the question of governance. Omar talks about ensuring accountability and accuracy while preventing potential risks associated with AI agents.

Curious about how AI agents are changing the landscape of automation and real-time systems? Tune in to discover the future of multi-agent systems, real-time processing, and AI-driven innovation with Praveen Gunasekaran and Omar Shanti!

Key moments:

• How Praveen defines agentic systems and thinking
• How the agent model could lead to greater democratization of technology
• Why governance is essential for ensuring accuracy
• How measures like "AI judges" and breaking tasks into manageable parts could be the key
• How “an agent mesh” could become a new architecture for AI systems
• Are APIs still the standard that the industry will follow?
• Praveen’s advice for making decisions on architecture and how agentic systems might change that

Key links: 

• Connect with Praveen on LinkedIn

Mentioned in this episode:

AI Opportunity Finder

Feeling overwhelmed by all the AI noise out there?

Could AI evolve from its position as a handy assistant to a fully-fledged teammate in the workplace?

Patrick Lynch, PhD, AI Faculty Lead at Hult International Business School, and Omar Shanti, CTO of HatchWorks, join host Matt Paige to explore the AI industrial revolution we’re seeing and how human-AI collaboration could drastically affect the way teams collaborate.

Patrick takes us through the "four faces of AI" - mechanical, analytical, intuitive, and empathetic - highlighting the progression of AI maturity and what it could mean for the future of work. This framework provides a valuable lens through which leaders can understand and leverage AI in the future.

The episode also touches on cutting-edge AI applications, such as Hume AI's voice models, which can detect and respond to human emotions, opening up new possibilities for AI-human interaction in various fields, from customer service to therapy and education.

Curious about how AI is becoming your new co-worker? Listen to Talking AI, where we explore how AI is turning into a real teammate at work. Subscribe on your favorite podcast platform and join us as we discuss how this technology is changing our future!

Key moments:

• Why we’re seeing an AI industrial revolution
• How we can start thinking of AI as co-workers
• The four faces of AI
• A demonstration of Hume AI
• How AI is starting to recognize emotion
• Potential use cases for AI co-workers
• The challenge of coding charisma into AI
• How adoption of AI could be affected by inaccurate results
• Which cultures are best suited to using AI

Key links: 

• Visit Patrick’s website
• TEDx Talks
• Connect with Patrick on LinkedIn
• Connect with Omar on LinkedIn

Mentioned in this episode:

AI Opportunity Finder

Feeling overwhelmed by all the AI noise out there?

Change is often met with resistance, but Neil Goodrich, Chief Innovation Officer at Envista Forensics, challenges us to rethink our approach to innovation in this episode of Talking AI.

Together with host Matt Paige, Neil explores where new AI tools can help to lead innovation and how small incremental changes can drive larger transformative projects. We look at how AI can boost efficiency at different stages of an innovation process, from creating faster prototypes to democratizing access to data insights across teams.

Matt and Neil swap ideas on how AI could impact things like customer feedback, everyday work, job displacement, and education (for better or worse). A key takeaway point from this episode is the importance of adaptability – a skill that we will all need as tech like AI continues to evolve rapidly.

Key moments:

• How AI can be involved in innovation projects big or small
• Neil provides the backstory to the DePaul innovation labs
• Will AI become an everyday tool like email is today?
• How AI could change different elements of an innovation process
• What excites and concerns Neil about the future of AI
• How AI could impact jobs and education

Key links: 

• Envista Forensics
• Connect with Neil on LinkedIn

Mentioned in this episode:

AI Opportunity Finder

Feeling overwhelmed by all the AI noise out there?

Generative AI may feel like the new kid on the block, but it's not as different from traditional machine learning as you might think.

In this episode of Talking AI, we’re joined by Simba Khadder, Co-Founder & CEO of Featureform, and Omar Shanti, CTO of Hatchworks AI, to discuss how generative AI builds upon established ML principles and infrastructure. We explore the misconception that it exists as its own little island, when in reality, we see a clear continuity between classic ML and newer AI technologies.

Simba and Omar break down the unique aspects of GenAI, such as prompting and large language models (LLMs), while also highlighting the shared foundations with traditional ML. They also touch on the evolution of retrieval augmented generation (RAG), the ML vs. GenAI lifecycle, and what MLOps teams should consider when it comes to driving value in a business.

Want to stay ahead in the fast-moving world of AI? Tune in to Talking AI where we break down the latest trends and tools in Generative AI, MLOps, and more. Subscribe now, and don't miss out on practical insights from industry experts. Let’s transform your data into real business impact!

Key moments:

• The similarities and differences between generative AI and traditional machine learning
• How prompts differentiate LLMs from earlier transformer models
• The challenges of implementing AI in production versus creating pilot projects
• How RAG has evolved and what it could mean for the future
• The importance of data as the core foundation for both traditional ML and generative AI
• How feature engineering in ML relates to embeddings in LLMs
• How an ML lifecycle differs from a GenAI one

Key links: 

• Featureform
• Connect with Simba on LinkedIn

Mentioned in this episode:

AI Opportunity Finder

Feeling overwhelmed by all the AI noise out there?

Does generative AI have a place in the highly regulated world of life sciences, and can it produce value without compromising patient safety?

In this episode of the Talking AI podcast, host Matt Paige sits down with Matt Lewis, Global Chief AI Officer at Inizio Medical, to explore the delicate balance between innovation and risk in healthcare AI.

Matt brings a wealth of experience from his role at Inizio Medical, a powerhouse in the life sciences industry that balances scientific knowledge with cutting-edge technology like AI to transform medical communication and content.

He shares invaluable insights on how AI is transforming pharmaceutical research, biotech advancements, and medical device development.

Matt reveals Inizio’s strategy for prioritizing AI use cases, explaining why there's no one-size-fits-all approach in such a complex field. He also discusses how AI can save time in creating patient summaries and why personalization and custom AI tools are needed to produce complex content.

Key moments:

• Generative AI's potential in life sciences and the associated risks
• How augmented intelligence can enhance decision-making and improve patient outcomes
• Matt’s dual role in improving internal operations and supporting clients in AI adoption
• How to identify and prioritize AI use cases unique to each organization
• Practical applications of AI and how they can save time and improve understanding
• The limitations of off-the-shelf AI tools like ChatGPT and the need for tailored solutions
• Why personalization in AI is important to provide tailored content

Key links: 

• Inizio’s Website
• Connect with Matt on LinkedIn
• The Neuron
• OpenTools
• Superhuman
• One Useful Thing
• There’s An AI For That
• Regulated industries white paper Conor Grennan (Chief AI Architect, NYU) and Matt Lewis co-authored

Mentioned in this episode:

AI Opportunity Finder

Feeling overwhelmed by all the AI noise out there?