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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