In this episode of AI-Curious, we explore a side of AI that rarely gets the spotlight: Large Geospatial Models (LGMs). You’ve heard of LLMs — now meet their real-world counterpart. LGMs could power everything from autonomous vehicles and urban planning to smarter first-response systems and industrial logistics.

We speak with Bill Lakeland, CEO of Spexi, a company building a decentralized fleet of self-flying drones that are actively mapping the planet — one 25-acre hex at a time. We dig into how these drones collect fresh, high-res data; how that data is authenticated and standardized; and how it could enable a new generation of real-world AI applications.

Along the way, we discuss:

• (5:00) What LGMs are, and how they differ from LLMs

• (13:07) Why real-time geospatial data is crucial for first responders

• (20:33) How drones fit into the LGM landscape

• (25:12) How Spexi’s autonomous drone “specxagons” work

• (31:43) Why their aerial data is 900x more detailed than Google Earth

• (36:26) How they’re addressing privacy, regulation, and standardization

• (40:02) What happens after the footage is collected — and how it’s turned into insights

• (45:35) The future integration of LGMs and LLMs

• (48:00) Speculative futures: how LGMs could change everyday life

If you’re curious about AI in the physical world — not just on screens — this is a conversation you won’t want to miss.

Spexi:

https://www.spexi.com/

🎧 Subscribe to AI-Curious:

• Apple Podcasts
https://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308

• Spotify
https://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b

• YouTube
https://www.youtube.com/@jeffwilser

In this episode of AI-Curious, we speak with Sarah Franklin, CEO of Lattice and former CMO of Salesforce, about how business leaders are adapting to the rapid rise of AI in the workplace. We explore what it means to lead during a time of disruption, how AI agents and digital workers are already being deployed across organizations, and why the biggest challenge is often not the tech—but the mindset.

Sarah shares her perspective on where AI is delivering real value today, from HR to sales to internal knowledge management, and she offers a candid take on how leaders can navigate change while maintaining trust, transparency, and human-centric values.

We also dive into the future: digital twins, avatar-led meetings, and what it might mean to lead a team that includes both humans and AI agents.

TOPICS & TIMESTAMPS

00:00 – Why we’re still early in understanding AI leadership

02:42 – Why past tech shifts (like cloud and mobile) don’t compare to AI

05:51 – Lattice’s mission and how AI fits into the HR stack

09:38 – Are AI agents real or still theoretical?

14:21 – Where AI agents are being used today (sales, service, HR)

20:02 – Digital twins and what leadership looks like with AI teammates

26:28 – How to address employee anxiety about AI and job security

30:19 – Sarah’s favorite personal and professional use cases for AI

34:59 – Prompting frameworks and why specificity matters

38:43 – A forecast for the future of AI and HR

Lattice

🎧 Subscribe to AI-Curious:

• Apple Podcasts
https://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308

• Spotify
https://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b

• YouTube
https://www.youtube.com/@jeffwilser

What happens when an AI student enrolls in university? In this episode of AI-Curious, we explore the fascinating case of Flynn, an AI-artist and the first AI to be admitted as a student at the University of Applied Arts Vienna. We speak with Chiara Kristler, one of Flynn’s co-creators, and Anika Meier, the curator of The Second-Guess: Body Anxiety in the Age of AI, where Flynn makes its artistic debut.

Flynn is more than just an AI chatbot—it engages in conversations, generates art, and even passed a verbal university admissions interview. But its presence raises big questions: Can AI be creative? How does AI challenge human artists? What does an AI student mean for the future of education?

We discuss:

• (00:00) Introduction to Flynn and why this is a breakthrough moment for AI

• (03:15) How Flynn was created and what makes it different from other AI agents

• (07:55) The university admissions process and how Flynn passed the interview

• (12:30) Can AI actually be creative, or is it just mimicking human artists?

• (18:04) The tension between AI and human artists—competition or collaboration?

• (24:22) AI fatigue, digital exhaustion, and the ethics of AI in creative spaces

Flynn’s journey raises deep questions about AI, creativity, and human identity. Join us for a thought-provoking conversation on what happens when machines start learning alongside us.

🔗 Talk to Flynn: https://i-am-flynn.web.app/

Flynn's

🎧 Subscribe to AI-Curious:

• Apple Podcasts
https://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308

• Spotify
https://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b

• YouTube
https://www.youtube.com/@jeffwilser

We’re reporting live from HumanX, one of the world’s largest AI conferences, where we’ve spent three intense days immersed in AI discussions, moderating panels, and speaking with some of the most influential voices in the industry. In this episode, we break down five takeaways from the conference, covering everything from AI’s growing role in politics to the future of AI-driven customer service and automation.

Then, we sit down with Daniela Braga, CEO of Defined AI, a leader in ethically sourced AI training data. We discuss the urgent need for transparency in AI data sourcing, the dangers of bias in large language models, and the growing demand for differentiated AI solutions.

5 takeaways from HumanX:
•AI is becoming political: Kamala Harris’s speech and the future of AI policy
•The death of human customer support and the rise of AI customer support (hot take: this is a good thing!)
•AI agents are finally getting real—how companies are deploying them today
•Businesses are scrambling to implement AI automation at scale
•Leaders are more AI-curious than ever—how executives are integrating AI into decision-making

Interview with Daniela Braga (CEO of Defined AI):
•The problem with AI training data: bias, legal concerns, and digital exploitation
•Why most AI models sound the same—and how that could change
•The myth that we’re “running out of data” and the future of AI training sets
•What’s next? Predictions for AI regulation, ethical sourcing, and industry differentiation

It’s a packed episode full of insights straight from the conference floor.

Defined.AI:

https://defined.ai/

🎧 Subscribe to AI-Curious:

• Apple Podcasts
https://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308

• Spotify
https://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b

• YouTube
https://www.youtube.com/@jeffwilser

There’s no shortage of hype about AI revolutionizing business, but what’s actually working right now? In this episode, we sit down with Peter Swimm, founder of the AI consultancy Toilville and former Principal Product Manager at Microsoft Copilot Studio, to cut through the noise and explore the real-world use cases of conversational AI.

Peter has been working on AI-powered automation for over a decade, helping companies integrate chatbots, AI agents, and large language models into their workflows. Unlike many AI evangelists, he isn’t here to drink the Kool-Aid. Instead, he lays out the hard truths about what AI can and can’t do today—including why fully autonomous AI agents are still far from reality.

We break down:

🔹 The most successful AI use cases in businesses today (hint: FAQ bots and automated customer support are actually delivering results)

🔹 The biggest misconceptions about AI agents and why they aren’t ready for prime time

🔹 How AI is transforming communication workflows, from email drafting to meeting summaries

🔹 The dangers of over-relying on AI for brainstorming and creative thinking

🔹 Practical tips for integrating AI into business operations without falling into the hype trap

⏱ Timestamps:

3:14 – Peter’s background in AI and Microsoft Copilot Studio

7:34 – What is Conversational AI and how has it evolved?

10:01 – The AI use cases that are actually delivering value in business

12:30 – AI’s role in communication automation and workflow efficiency

17:14 – The challenge of making AI-generated emails sound human

22:58 – Is AI actually good for brainstorming, or is it making us less creative?

29:36 – The truth about AI agents—why businesses aren’t adopting them yet

34:31 – Will AI agents ever work as promised? The barriers to real automation

38:36 – Smart ways to use AI for efficiency without giving up human oversight

40:26 – How Peter personally uses AI in his daily work

Toilville:

https://www.itstoilville.com/

🎧 Subscribe to AI-Curious:

• Apple Podcasts
https://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308

• Spotify
https://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b

• YouTube
https://www.youtube.com/@jeffwilser

In this episode of AI Curious, we explore one of the most profound applications of artificial intelligence—drug discovery and the future of personalized medicine. AI is already transforming how we develop treatments, and at the forefront of this revolution is Brice Challamel, VP of AI Products and Platforms at Moderna.

We dive deep into how AI is accelerating the discovery of life-saving drugs, including how mRNA technology—the foundation of Moderna’s COVID-19 vaccine—is shaping the next generation of treatments for cancer, rare diseases, and viruses. Brice shares insights on AI-powered protein design, how AI can give us an “evolutionary boost” in medicine, and what the future of personalized medicine looks like.

Key Topics:

• (3:50) Brice’s journey from Google to Moderna—why AI in biotech is his biggest passion

• (8:56) How AI played a critical role in the rapid development of Moderna’s COVID vaccine

• (12:28) The role of AI in drug discovery: understanding proteins and optimizing treatments

• (17:18) The rise of personalized cancer treatments—could AI help cure cancer?

• (30:10) The future of medicine: How AI is unlocking breakthroughs across multiple diseases

• (39:59) The biggest challenges—clinical trials, regulatory frameworks, and operational hurdles

• (46:02) AI’s impact on data security and patient privacy

• (49:05) The future of AI-powered healthcare: a world of personalized treatments, AI-driven patient care, and faster drug development

This episode is a must-listen for anyone curious about how AI is reshaping medicine, the ethics and challenges of deploying AI in healthcare, and what lies ahead for biotech, drug discovery, and personalized medicine.

aaaaaand... I'm launching a new podcast!

Don't worry, fans of AI-CURIOUS -- that's not going anywhere. This is a second podcast with its own independent feed. I'll still be producing AI-Curious each week.

The new pod is called THE PEOPLE'S AI: The Decentralized AI Podcast, presented by Vana. In the future, this will be available on all the usual podcast platforms (links to subscribe below.)

But for this week, I'm dropping THE PEOPLE'S AI into the feed for AI-Curious. It's a good primer on what Decentralized A" is all about.

AI-Curious will continue to be a general interest AI podcast. AI and Hollywood one week, AI and the military the next. The People's AI is a different beast...

Subscribe to The People's AI on APPLE:

https://podcasts.apple.com/us/podcast/the-peoples-ai-the-decentralized-ai-podcast/id1792518750?i=1000694109163

Subscribe to The People's AI on YouTube:

https://www.youtube.com/channel/UCnLiYlJulQIcmvCjnVRYotw

Subscribe to The People's AI on SPOTIFY:

https://open.spotify.com/show/3XFmg6Lqf7nnKwMkicBx8L?si=8c43eac26fd7445e

The People's AI on Twitter/X:

https://x.com/The_Peoples_AI

Jeff Wilser on Twitter/X:

https://x.com/jeffwilser

____________

In our debut episode of The People’s AI: The Decentralized AI Podcast, Presented by Vana, we dive into one of the most critical questions of the AI era: Who should own AI?As artificial intelligence becomes increasingly embedded in daily life, its ownership and governance will shape the future. Big Tech dominates AI development today, but a growing movement believes AI should be decentralized, open, and user-owned.

We speak with Anna Kazlauskas, co-founder of Vana, and Illia Polosukhin, co-founder of NEAR, to explore how decentralized AI could shift power away from centralized corporations and into the hands of individuals.

Key Topics Covered:

• What decentralized AI means and why it matters

• How AI models are built and trained—and who controls them

• The intersection of AI, data sovereignty, and blockchain

• The potential risks of centralized AI, from bias to economic concentration

• How AI assistants, autonomous agents, and data unions are reshaping the internet

• Predictions for the next 1-5 years in AI and decentralized technologies

About Vana:

Vana's vision is for user-owned AI through user owned-data. Its mission is to be the world's first open protocol for data sovereignty. Sign up for the first AI Data Summit, hosted by Vana, on Feb 28 in Denver. This will be the go-to event at Eth-Denver with leaders at the forefront of Decentralized AI tech and applications.

AI Data Summit, hosted by Vana:

https://lu.ma/aidatasummit

More on Vana:

https://linktr.ee/vanahq

Vana on Twitter/X:

https://x.com/vana

Anna Kazlauskas on Twitter/X:

https://x.com/anna_kazlauskas

NEAR: The Blockchain for AI

https://near.org/

NEAR on Twitter/X:

https://x.com/NEARProtocol

Imagine telling an AI Agent, “Book me a vacation to Tokyo—flights, hotels, dinner reservations—just take care of it.” That level of automation isn’t science fiction. It’s the future of AI Agents.

In this episode, we take a deep dive into the AI Agent revolution with Humayun Sheikh, CEO of Fetch AI. Fetch AI has been working on autonomous AI systems since 2018—long before AI Agents became a buzzword. Humayun was also a founding investor in DeepMind, giving him a rare, insider perspective on the evolution of AI-driven automation.

We explore the current landscape of AI Agents, and what it will take for them to go mainstream:

✅ What AI Agents can do today—and what’s still missing

✅ Why AI Agents aren’t yet mainstream despite the technology being ready

✅ The key roadblocks: lack of common protocols, interoperability, and infrastructure

✅ How Fetch AI is building a “Google for AI Agents” to solve these challenges

✅ The future of AI-powered automation and why the goal is invisible AI

We also discuss blockchain’s role in AI, decentralized models, and why large language models are becoming a commodity. Towards the end of the episode, Humayun teases the launch of a new LLM designed specifically for AI Agents.

📌 Timestamps:

[00:19] – The mission of Fetch AI: building an agent deployment framework

[02:10] – Why we need a Google of AI Agents for discovery and interaction

[04:29] – How intent translates into AI-driven task automation

[08:34] – The biggest hurdle: lack of interoperability and standardization

[13:20] – Real-world AI Agent applications today: software development, automation, and social media

[19:02] – The roadblocks preventing widespread AI Agent adoption

[25:15] – The philosophical shift: AI Agents should be invisible

[33:56] – What Fetch AI is building next: the AgentVerse marketplace, decentralized compute, and Cortex LLM

If you’re curious about the future of AI-driven automation, decentralized AI, and the next wave of digital assistants, this episode is a must-listen.🎧 Subscribe to AI-Curious for deep dives into the world of AI.

• Fetch AI:

https://fetch.ai/

Humayun Sheikh

https://x.com/HMsheikh4

🎧 Subscribe to AI-Curious:

• Apple Podcasts
https://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308

• Spotify
https://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b

• YouTube
https://www.youtube.com/@jeffwilser