Larry Birnbaum, Professor of Computer Science at Northwestern University and co-founder of Narrative Science, joins the AI Lab to explain why today’s large language models work at all—and why their success has surprised even longtime AI researchers.

In this conversation, Larry and Ryan explore how decades of AI research led to the current moment, why massive models somehow generalize instead of just memorizing, and what this means for businesses adopting AI at scale.

We also dive into:

• Why today’s AI boom feels sudden. but has decades of groundwork behind it

• The overfitting paradox: why massive models generalize instead of just memorizing

• How transformers and attention changed context, reference, and meaning in languag

• Why AI delivers the most value at scale and through personalization (work that wouldn’t

otherwise exist)

• Bias vs. inductive bias and how agreeable AI systems can reflect a user’s worldview back at them

• What AI breaks in education, and why fundamentals still matter for students and engineers

• The interpretability problem: we know how LLMs learn, but not what they’ve learned or how they decide

Larry shares hard-earned perspective from a career spanning academic AI research and real-world deployment, including lessons from building one of the earliest automated narrative platforms and why understanding AI’s limits is just as important as celebrating its breakthroughs.

Guest Bio:

Larry Birnbaum is a Professor of Computer Science at Northwestern University whose research focuses on artificial intelligence, natural language processing, and human–AI collaboration. He is the co-founder of Narrative Science, an early pioneer in automated storytelling from data, and has spent decades studying how machines can generate language that is coherent, contextual, and useful at scale.

Resources

→ Connect with Larry Birnbaum on LinkedIn: https://www.linkedin.com/in/larry-birnbaum-1393b4147/

Alex Czurylo, Chief Strategy & Operations Officer at Gen3 Marketing and former analytics and operations leader at Rakuten Advertising, joins the AI Lab to break down what it really takes to build a successful AI program inside an organization—long before ChatGPT made AI mainstream.

In this episode, Alex and Ryan unpack why the most effective AI strategies don’t start with tools, but with clearly defined business problems, strong governance, and internal capability-building.

• Why starting with a single, measurable business problem is the key to AI ROI

• How Rakuten Advertising built one of the earliest enterprise AI programs—years ahead of the curve

• What the “VP of AI Strategy & Operations” role actually owns (and why vision matters more than hype)

• How to approach AI governance without slowing down adoption

• Why AI training should be treated as a core employee benefit

• The hidden risks of outsourcing AI agents without internal ownership

• What Generative Engine Optimization (GEO) means—and how AI is reshaping marketing discovery

Alex shares hard-earned lessons from leading analytics, data science, and AI initiatives at scale, including how to balance experimentation with operational rigor, and why companies that delay AI enablement risk falling permanently behind.

Alex Czurylo is Chief Strategy & Operations Officer at Gen3 Marketing, where AI sits at the center of how the agency drives performance and innovation for clients. Previously, Alex spent over a decade at Rakuten Advertising leading analytics and operations, where he helped pioneer early enterprise AI use cases focused on automation, insight generation, and measurable ROI.

Known for his pragmatic, outcome-driven approach to technology, Alex has been an early adopter of language models and AI systems—long before generative AI entered the mainstream. His work bridges data science, strategy, governance, and organizational change, helping companies turn emerging technology into real business impact.

→ Connect with Alex Czurylo on LinkedIn: https://www.linkedin.com/in/alexczurylo/

We also dive into:Guest BioResources

Nate Nichols, an early builder in machine-generated content and now a product leader shaping “agentic” analytics, joins host Ryan Kurt for a candid conversation on how generative AI evolved, what we gained, and what we risk losing along the way.

We also dive into:

• How early AI systems differed from today’s agentic models and why that matters

• Why many modern AI breakthroughs were discovered, not deliberately designed

• AI as a clarity engine: structuring messy thinking into plans, writing, and decisions

• The risks of optimizing AI for engagement and uncomfortable parallels to social media

• Where agentic AI creates real value today, and where caution is warranted
  

Guest Bio: Dr. Nate Nichols is a product leader focused on generative and agentic AI for analytics. He previously spent over a decade building machine-generated content and data storytelling systems, and he earned his PhD in Artificial Intelligence from Northwestern University, where his research centered on machine-generated content.

Resources → Connect with Nate on LinkedIn: https://www.linkedin.com/in/nate-nichols/

Jen Stave, Launch Director at the Digital, Data, Design Institute at Harvard Business School , joins the AI lab to share expert insight into the most common mistakes in AI transformation, and practical steps for how to avoid them.

• What is The Digital Data Design Institute at Harvard Business School, and what are their goals

• Why companies need to rethink their operating model to harness AI tools

• How to measure the ROI of a major AI transformation

• How AI is disrupting data science

• The role leadership plays in shepherding AI innovation in an organization

Jen is an AI expert, specifically in the landscape of business, and launch director at Digital, Data, and Design Institute at Harvard.

The Digital, Data, and Design Institute is an environment motivating cutting-edge faculty research. They include 12 labs, each designed to explore and solve problems that our world faces today. The Institute also works with leading companies to adapt and secure AI and emerging technologies to transform their organizations.

→Connect with Jen on LinkedIn: linkedin.com/in/jen-stave

→ ⁠Learn more about Digital, Data, Design Institute at Harvard: https://d3.harvard.edu/

Alex Lehman, Vice President at Sapphire Ventures, joins the AI lab to discuss insight into the investment world after the recent generative AI boom and how businesses can use generative AI in their products.

We dive into:

• The migration to a talent-based consumer market from a name brand consumer market

  Should companies stay on the sidelines or start experimenting with AI?

• The concern of data privacy and AI

• Navigating AI-usage with your employees

Alex is an AI Investment expert, Board Advisor at Women in Sports Tech, and Investor at Sapphire Ventures.

At Sapphire Ventures, Alex focuses on enterprise infrastructure, data and analytics, and security. Sapphire contributes specialization, experience, and network to help teams navigate their companies journey to build a successful expansion stage to initial public offering.

Alex is a Board Advisor for the non-profit, Women in Sports Tech, which provides growth and funding opportunities for young women working to pursue careers in sports and technology.

→ ⁠Connect with Alex on LinkedIn: linkedin.com/in/alex-lehman-a0252975

→ ⁠Learn more about Sapphire Ventures: https://sapphireventures.com/

→ ⁠Learn more about Women in Sports Tech: https://www.womeninsportstech.org/

Rohan Sampath, Co-founder at Copilot, joins The AI Lab to discuss how executives can better understand and leverage VOC (Voice of the Customer) using AI.

We also dive into:

• Will AI startups become incumbents worst nightmare?
• The future of AI-powered sales
• How understanding customer sentiment with AI can supercharge your go-to-market
• How Copilot is helping companies dissect customer conversations in 60 seconds
• The evolution of conversational intelligence and LLMs (Large Language Models)

Rohan is an AI expert, advisor, podcast host, and co-founder of Copilot.

Copilot helps companies deeply understand the voice of their customer. Their tool records and transcribes customer conversations, use GPT-4 to extract topics, themes and insights that are tailored to your sales process and methodology (MEDDIC/BANT, etc.), and fill out your CRM with a summary of those insights.

Rohan is host of the AI Tech Sales Podcast. Every week, he interviews CEOs, Sales Leaders, and AI experts on how they think AI will change revenue organizations and the customer buying journey.

→ ⁠Connect with Rohan on LinkedIn: https://www.linkedin.com/in/rohansampath/

→ ⁠Learn more about Copilot: https://www.copilotup.com/

→ ⁠Listen to the AI Tech Sales Podcast: https://ai-tech-sales-podcast.simplecast.com/

Ryan Francis⁠, Partner and President of Chicago-based software studio, ⁠LaunchPad Lab⁠, joins the AI lab to share his perspective on how AI-driven development will redefine UX and programmer workflows.

• How ChatGPT will impact the future of web & mobile user experience
• Will ChatGPT replace Google as our go-to web search?
• How LaunchPad Lab went from development firm to AI firm overnight
• How ChatGPT will change how developers work
• How generative AI can transform the staffing industry

A entrepreneur and software engineer, Ryan brings a decade of experience building technology that transforms organizations inside out.

Ryan is currently Partner and President of Launch Pad Lab, a software studio that seemingly overnight has gone from a firm focused on web, mobile, and Salesforce development to becoming the go-to dev team for generative AI-driven solutions.

Before LaunchPad, Ryan held multiple roles within the finance world, most recently as Chief Financial Officer at Elixserve. On the side, him and his dad manufacture bunk beds and loft beds for adults as Francis Lofts & Bunks, a company the two founded in June 2012. Step Brothers anyone?

⁠https://youtu.be/3BlHY69ZsZ0⁠

→ ⁠Connect with Ryan on LinkedIn⁠

→ ⁠Learn more about LaunchPad Lab

Chris Hohman, VP of Product Management at FICX and Founder of Velocity AI joins the AI lab to discuss the age-old question in tech: to build or buy? In this episode, Chris shares his perspective on the pros and cons of open source vs in-house models — and more!

Other topics include:

• The challenges with generative AI in banking
• The different levels of impact AI will have on business
• Why we need to build models with a moral compass; the good & the bad of AI
• How restricting AI usage can create a digital divide in your company

Chris Hohman is a product leader and founder with over two decades of experience in the tech industry. He is currently the VP of Product Management at FICX and Founder of Velocity AI, a consultancy helping business embrace the AI revolution with confidence.

From scale-ups to industry Goliaths like Cisco, Adobe, and Amazon, Chris specializes in digital transformation, accelerating engineering efforts up to 50% through resource alignment and product development, and new technologies. With years of experience bringing successful products to market, Chris delivers with a unique combination of vision, leadership, management, and creativity.

→ ⁠Connect with Chris