The (Data-Driven) Top AI Trends, w/ the CEOs of HumanX and Read.AI
What are the top minds in AI actually talking about behind closed doors?At the HumanX conference—arguably the flagship event in the AI ecosystem—hundreds of speakers (from CEOs to policymakers to Kamala Harris) shared their unfiltered thoughts on the state and future of artificial intelligence. But with so much happening at once, even attendees couldn’t absorb it all.So HumanX did something novel: they partnered with Read.AI to record and synthesize every single session. The result? A real-time AI copilot for the conference and a post-event report that reveals the key themes, trends, and tensions shaping the industry.In this episode, we speak with HumanX CEO Stefan Weitz and Read.AI CEO David Shim to unpack the insights from that report—what they signal for 2025, what business leaders should pay attention to, and what’s probably just noise.We talk about the rise of agentic AI, the shift from AGI ambition to ROI expectations, and the practical realities of implementing AI inside large organizations. We also dig into issues of trust, open source, industry-specific adoption, and how AI is starting to reshape roles from customer service to legal to healthcare.Whether you’re in strategy, ops, tech, or just trying to keep up, this conversation offers a data-driven pulse check on where enterprise AI is headed.Highlights & Timestamps:[1:00] – How Read AI became the official AI copilot of the HumanX conference[3:10] – “You can’t be everywhere at once”—the problem this tech solves at events[6:15] – The most talked-about concept at HumanX: agentic AI[7:45] – Why AGI hype is shifting toward practical use cases with agents[8:58] – The fast hype-decay cycle of AI and the emerging focus on outcomes[12:26] – Open source, cost savings, and why business leaders care about transparency[14:19] – Trust as the “anchoring tenet” of enterprise AI adoption[16:45] – Real ROI: how Read AI identified $10M in sales pipeline in 30 days[20:03] – Why companies are hiding their AI wins from competitors[22:43] – Cross-industry learnings: how healthcare patterns may apply to other sectors[25:47] – The “put up or shut up” moment: 2025 as the year AI must deliver[29:06] – What business leaders should do before launching AI agent initiatives[35:03] – The #1 mistake orgs make with AI: failing to assign ownership[37:09] – Predictions: personalization, interoperability, and privacy friction ahead[42:28] – How Stefan and David personally use AI—for work, fun, and creative hackingLinks & Mentions:HumanX – Flagship AI conference co-founded by Stefan WeitzRead AI – Productivity-focused AI platform by David ShimSuno – AI music generation tool mentioned by StefanReplit – AI coding sandbox used by Stefan for strategy visualizationVeo by Google DeepMind – AI video generation tool referenced by David🎧 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 if we’re all chasing the wrong kind of AI? Dr. Ruchir Puri, Chief Scientist of IBM, argues that Artificial General Intelligence (AGI) is overrated—and that we should be focusing instead on AUI: Artificial Useful Intelligence. This is a pragmatic, business-focused approach to AI that emphasizes real-world value, measurable outcomes, and implementable solutions.In this episode of AI-Curious, we explore what AUI actually looks like in practice. We discuss how to bring AI into your organization (even if you’re just getting started), why IBM is betting big on small language models (SLMs), and how companies can move beyond hype toward real, trustworthy AI agents that do actual work.You’ll also hear:Why AI usefulness is a function of both quality and cost [00:11:00]The “crawl, walk, run” strategy IBM recommends for business adoption [00:14:00]Internal IBM examples: HR systems and coding assistants [00:16:00]Why SLMs may be a smarter bet than LLMs for many enterprises [00:37:00]A breakdown of how agentic systems are evolving to reflect, act, and self-correct [00:41:00]Whether you’re leading a startup or an enterprise, this conversation will help you reframe how you think about deploying AI—starting not with hype, but with value.🎧 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
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A Conversation with the AI Pioneer Who Coined ‘AGI’ — Dr. Ben Goertzel
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
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Should AI Agents Be Trusted? The Problem and Solution, w/ Billions.Network CEO Evin McMullen
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
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Agentic AI Case Study: AI "Sales Agents" in Action, w/ Alta CEO Stav Levi-Neumark
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
A podcast that explores the good, the bad, and the creepy of artificial intelligence. Weekly longform conversations with key players in the space, ranging from CEOs to artists to philosophers. Exploring the role of AI in film, health care, business, law, therapy, politics, and everything from religion to war. Featured by Inc. Magazine as one of "4 Ways to Get AI Savvy in 2024," as "Host Jeff Wilser [gives] you a more holistic understanding of AI--such as the moral implications of using it--and his conversations might even spark novel ideas for how you can best use AI in your business."