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 world

If 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.

SingularityNet

https://singularitynet.io/

Ben Goertzel on X

https://x.com/bengoertzel

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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

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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 Alta

03:00 — Meet Katie, Alex, and Luna: AI sales agents with defined roles

08:00 — How AI agents qualify leads and determine buying intent

13:00 — The distinction between chatbots and agentic AI

18:30 — How AI agents can avoid becoming spammy LinkedIn bots

22:00 — Alex the calling agent: real-time inbound response and transparency

28:00 — What tools make an AI agent different from a workflow

31:00 — Autonomy, decision-making, and sales team augmentation

36:00 — The challenge of trust and how to begin using AI agents at low risk

39:00 — Stav’s journey as a founder and the four-generation Vegas trip

42:00 — How she uses AI personally: support agents, internal tools, and therapy

44:30 — Advice for sales professionals on embracing AI

46:30 — Predictions: what sales might look like in 5 to 10 years

Let us know what you think—and whether Luna is getting the respect she deserves.

About Alta:

https://www.altahq.com/

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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 world

Let 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

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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 cheating
• Human skills vs. AI skills, and the World Economic Forum’s two-skill model
• The future of education: personalization, affordability, and AI-enabled scale
• How executives should rethink AI integration—with intention, not just experimentation
• Why OpenAI Academy’s recent pivot could signal a broader shift in how we teach AI

Whether 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

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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 affection
• Why constant flattery from bots may feel good—but ultimately erodes something essential in real relationships
• The importance of sacrifice, caregiving, and challenge in human connection
• Whether AI companions, even with future upgrades, can ever replicate the messy magic of real love
• What AI fiction gets wrong—and why most AI-generated stories are (still) terrible
• Her take on AI and historical accuracy, and the troubling implications of getting facts wrong at scale
• Why creativity matters even when the output is bad—and what we lose when we outsource it

Plus, 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 Lover
• Jennifer’s latest book: Madame Restell: The Life, Death, and Resurrection of Old New York’s Most Fabulous, Fearless, and Infamous Abortionist
• Jennifer’s upcoming book: Glitz, Glam, and a Damn Good Time: How Mamie Fish, Queen of the Gilded Age, Partied Her Way to Power.

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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/

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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

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