AI-Curious with Jeff Wilser

What exactly is AGI—Artificial General Intelligence—and how close are we to achieving it? Will it transform the world for better or worse? And how can we even tell when true AGI has arrived?In this episode of AI Curious, we sit down with Dr. Ben Goertzel, the iconic computer scientist who coined the term AGI more than 20 years ago. As the founder of SingularityNET and the Artificial Superintelligence Alliance, Ben has spent decades thinking about the architecture, risks, and potential of general intelligence.We explore why today’s large language models (LLMs), while powerful, still fall short of true AGI—and what will be needed to bridge that gap. We dive into Ben’s prediction that AGI could arrive within just 1 to 3 years, and why he believes it will likely be decentralized. Along the way, we unpack some of the key ideas from his recent “10 Reckonings of AGI”—a candid look at the social, economic, and existential questions we must face as AGI reshapes human life.Topics include:[00:04:00] What AGI really means vs. current LLMs[00:10:00] Are we reaching the limits of current AI architectures?[00:13:00] How will we know when AGI has truly arrived?[00:17:00] The “PhD test” for human-level AGI[00:19:00] AGI timeline predictions (1–3 years? 2029?)[00:29:00] The 10 Reckonings of AGI: key societal impacts[00:36:00] The gap between AGI and superintelligence[00:44:00] Why a decentralized AGI might be safer[00:51:00] Surprising upsides of a post-AGI worldIf you’re curious about the future of artificial intelligence, this conversation offers a rare and unfiltered perspective from one of the field’s most original thinkers.SingularityNethttps://singularitynet.io/Ben Goertzel on Xhttps://x.com/bengoertzel🎧 Subscribe to AI-Curious:• Apple Podcastshttps://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308• Spotifyhttps://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b• YouTubehttps://www.youtube.com/@jeffwilser

What happens when an AI agent says something harmful, or makes a costly mistake? Who’s responsible—and how can we even know who the agent belongs to in the first place?In this episode of AI-Curious, we talk with Evin McMullen, CEO and co-founder of Billions.Network, a startup building cryptographic trust infrastructure to verify the identity and accountability of AI agents and digital content.We explore the unsettling rise of synthetic media and deepfakes, why identity verification is foundational to AI safety, and how platforms—not users—should be responsible for determining what’s real. Evin explains how Billions uses zero knowledge proofs to establish trust without compromising privacy, and offers a vision for a future where billions of AI agents operate transparently, under clear reputational and legal frameworks.Along the way, we cover:The problem with unverified AI agents (2:00)Why 50% of online traffic is now bots—and why that matters (2:45)The Air Canada chatbot legal fiasco (15:00)The difference between chatbots and agentic AI (13:00)What “identity” means in an AI-first internet (10:00)Deepfakes, misinformation, and the limits of user responsibility (22:00)Billions’ “deep trust” framework, explained (29:00)How platforms can earn trust by verifying content authenticity (34:00)Breaking news: Billions’ work with the European Commission (38:20)This one dives deep into the infrastructure of digital trust—and why the future of AI may depend on getting this right.Learn more: https://billions.network🎧 Subscribe to AI-Curious:• Apple Podcastshttps://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308• Spotifyhttps://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b• YouTubehttps://www.youtube.com/@jeffwilser

What exactly are AI agents doing out in the wild — and are they actually helping sales teams, or just adding noise?We explore the fast-evolving world of AI sales agents with a real-world case study from Alta, a startup deploying purpose-built AI agents named Katie, Alex, and Luna. In this episode of AI-Curious, we speak with Stav Levi-Neumark, Alta’s CEO and co-founder, about how agentic AI is already transforming sales workflows—from prospecting to pipeline generation to inbound response.We look under the hood to examine how these agents operate, what distinguishes them from chatbots, and how they interact with human reps. We also explore the ethics, limitations, and future of AI-human collaboration in business development—and what it means to build trust in AI systems.Whether you work in sales, lead a startup, or are just curious about how AI tools are functioning in the real world, this conversation offers a sharp, concrete look at the tech reshaping how companies grow.Topics and Timestamps:00:00 — What are AI agents doing, really?01:00 — Behind the scenes at HumanX and the rise of Alta03:00 — Meet Katie, Alex, and Luna: AI sales agents with defined roles08:00 — How AI agents qualify leads and determine buying intent13:00 — The distinction between chatbots and agentic AI18:30 — How AI agents can avoid becoming spammy LinkedIn bots22:00 — Alex the calling agent: real-time inbound response and transparency28:00 — What tools make an AI agent different from a workflow31:00 — Autonomy, decision-making, and sales team augmentation36:00 — The challenge of trust and how to begin using AI agents at low risk39:00 — Stav’s journey as a founder and the four-generation Vegas trip42:00 — How she uses AI personally: support agents, internal tools, and therapy44:30 — Advice for sales professionals on embracing AI46:30 — Predictions: what sales might look like in 5 to 10 yearsLet us know what you think—and whether Luna is getting the respect she deserves.About Alta:https://www.altahq.com/🎧 Subscribe to AI-Curious:• Apple Podcastshttps://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308• Spotifyhttps://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b• YouTubehttps://www.youtube.com/@jeffwilser

What does it mean to grow up in a world where AI is simply… normal? In this episode of AI-Curious, we're joined by Matt Britton, branding strategist and author of Generation AI: Why Generation Alpha and the Age of AI Will Change Everything, for a wide-ranging discussion about how artificial intelligence is transforming childhood, education, branding, healthcare, and the very fabric of society.We look at how Gen Alpha will interact with AI “sidekicks,” how the role of brands might erode in a world of personalized AI agents, and what this all means for marketers, parents, and future professionals. Matt also lays out why the traditional four-year college degree may collapse, how one-person billion-dollar companies are now within reach, and what core skills the next generation—and the rest of us—will need to thrive.We close with practical advice on how to future-proof ourselves in the age of intelligent agents, synthetic creativity, and AI-native consumers.Topics include:(0:00) Gen Alpha and the future of AI-native childhood(3:03) How AI will transform marketing and branding(7:04) LLMs, AI agents, and the death of traditional demographics(14:01) Rethinking education and the collapse of the knowledge economy(17:10) One-person billion-dollar companies and the new AI tech stack(21:40) Personalized healthcare, diagnostics, and AI as your doctor(25:21) One simple way to future-proof your life in an AI-powered worldLet us know what you think, and if this episode gets your gears turning, share it with someone who’s curious about the future.Matt Britton:https://mattbritton.com/The new book Generation AI:https://www.amazon.com/Generation-AI-Alpha-Change-Everything/dp/139430885X🎧 Subscribe to AI-Curious:• Apple Podcastshttps://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308• Spotifyhttps://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b• YouTubehttps://www.youtube.com/@jeffwilser

How is AI reshaping higher education? What do students actually need to learn in the age of large language models? And why might skills-based learning soon rival or even replace the traditional degree? In this episode of AI-Curious, we speak with Ben Tasker, "Dean of AI" at Southern New Hampshire University. Ben walks us through the structure of his “applied AI” curriculum, how his team uses AI to build courses in just 14 days, and why prompt engineering is becoming an essential literacy. We also break down the CREATE framework for prompting, designed to help users—students and professionals alike—level up their use of tools like ChatGPT.Other topics include:The tension between AI adoption and academic cheatingHuman skills vs. AI skills, and the World Economic Forum’s two-skill modelThe future of education: personalization, affordability, and AI-enabled scaleHow executives should rethink AI integration—with intention, not just experimentationWhy OpenAI Academy’s recent pivot could signal a broader shift in how we teach AIWhether you’re a student, educator, or business leader trying to find your footing in the in-between era of AI, this conversation offers a grounded, pragmatic perspective.Ben Tasker:https://www.bentaskerai.com/bens-ai-portfolio-thought-leadership🎧 Subscribe to AI-Curious:• Apple Podcastshttps://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308• Spotifyhttps://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b• YouTubehttps://www.youtube.com/@jeffwilser

Millions of people are finding companionship -- or even love -- with AI bots. (The heart wants what the heart wants.) In this episode of AI-Curious, we dive into the strange, sticky, and sometimes surprisingly emotional world of AI romantic partners.We’re joined by author and historian Jennifer Wright, who recently wrote a sharp op-ed for The Washington Post titled “Please Break Up With Your AI Lover.” While millions are already turning to AI bots for companionship, Jennifer makes a compelling case for why this trend—though rooted in real loneliness—could be deeply damaging to our ability to connect, to grow, to give love.We unpack:The surface problems of AI boyfriends/girlfriends, from poor memory to the illusion of affectionWhy constant flattery from bots may feel good—but ultimately erodes something essential in real relationshipsThe importance of sacrifice, caregiving, and challenge in human connectionWhether AI companions, even with future upgrades, can ever replicate the messy magic of real loveWhat AI fiction gets wrong—and why most AI-generated stories are (still) terribleHer take on AI and historical accuracy, and the troubling implications of getting facts wrong at scaleWhy creativity matters even when the output is bad—and what we lose when we outsource itPlus, Jennifer gives us a preview of her next book about America’s Gilded Age, and we swap war stories about terrible first novels, romantic relationships, and the puppy-induced joys of caretaking.Let’s get curious.Links from this episode:Jennifer Wright’s Washington Post op-ed: Please Break Up With Your AI LoverJennifer’s latest book: Madame Restell: The Life, Death, and Resurrection of Old New York’s Most Fabulous, Fearless, and Infamous AbortionistJennifer’s upcoming book: Glitz, Glam, and a Damn Good Time: How Mamie Fish, Queen of the Gilded Age, Partied Her Way to Power.🎧 Subscribe to AI-Curious:• Apple Podcastshttps://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308• Spotifyhttps://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b• YouTubehttps://www.youtube.com/@jeffwilser

LLMs are *so* 2024. Say hello to LGMs. 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 lifeIf 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 Podcastshttps://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308• Spotifyhttps://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b• YouTubehttps://www.youtube.com/@jeffwilser

In this engaging conversation, Sarah Franklin, CEO of Lattice and former CMO of Salesforce, shares her expertise on AI's transformative role in leadership and HR. She discusses how AI agents are moving from theory to practical applications across various sectors. Sarah emphasizes the importance of trust and human-centric values as leaders navigate the complexities of AI integration. The discussion also touches on future innovations like digital twins and avatar-led meetings, along with practical tips for addressing employee concerns about job security.

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 spacesFlynn’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 Podcastshttps://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308• Spotifyhttps://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b• YouTubehttps://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-makingInterview 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 differentiationIt’s a packed episode full of insights straight from the conference floor.Defined.AI:https://defined.ai/🎧 Subscribe to AI-Curious:• Apple Podcastshttps://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308• Spotifyhttps://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b• YouTubehttps://www.youtube.com/@jeffwilser