AI-Curious with Jeff Wilser

What happens when AI stops living only on screens and starts measuring the physical world?
In this episode of AI-Curious, we talk with Ben Bond of Simbe about physical AI, retail robotics, and how autonomous robots are already helping stores understand what is actually happening on their shelves.
Simbe is focused on store intelligence through its shelf-scanning robot, Tally, a six-foot autonomous sensing robot used by major retailers across grocery, club, home improvement, and other high-volume retail environments. We explore how Tally moves through stores, detects missing products, checks shelf conditions, reads prices, and gives retailers a clearer picture of what is happening in the aisles.
We also discuss why the physical world is still surprisingly under-measured. Online retailers have had decades of analytics, SEO, merchandising tools, and digital optimization, but brick-and-mortar stores have often relied on human observation, spot checks, and labor-intensive manual audits. Ben explains how physical AI can create a new data layer for stores, helping retailers prioritize work, improve inventory accuracy, catch out-of-stock items, and operate more efficiently.
The conversation also gets into why Tally is a robot rather than just a ceiling camera or drone, why it does not currently talk to shoppers or stock shelves, and why the robot’s ability to move close to products from multiple angles creates richer, more precise data. We also talk about whether robots are taking retail jobs, why Simbe sees its work as additive rather than replacement-driven, and how robotics may evolve beyond humanoids into more specialized systems.
Finally, Ben shares where physical AI and robotics may be headed next, including supply chain, manufacturing, healthcare, disaster response, and a future where robots collaborate not only with humans, but with other robots.
Guest
Ben Bond — SVP of Strategy and Client Success, Simbe
Follow AI-Curious on your favorite podcast platform:
Apple Podcasts
Spotify
YouTube
All Other Platforms
For anyone interested in Jeff’s AI Workshops for their company:
Reach out directly at jeff@jeffwilser.com

What happens when AI agents become the audience?
In this episode of AI-Curious, we talk with Mark Howard, Chief Operating Officer of TIME, about how one of the world’s most iconic media brands is preparing for a web increasingly shaped by AI agents, AI crawlers, and machine-readable content.
TIME is now operating across what Mark describes as two internets: one built for human readers, with photos, design, layout, and the familiar red border, and another built for machines, stripped down into structured text that AI agents can crawl, parse, and use. We explore how TIME is using this shift to build new products, new internal workflows, and even a new kind of ad inventory designed for AI agents.
Mark walks us through the work behind TIME’s AI transformation, including how the team organized more than 100 years of journalism, nearly a million pieces of content, across scattered databases, PDFs, and legacy systems. We discuss the creation of a private LLM grounded in TIME’s archive, the launch of TIME AI, and how tools like summaries, translations, audio briefings, and article-level chat can expand access without changing the underlying facts of the reporting.
We also talk about what TIME considers sacred: trust, original reporting, editorial integrity, and the journalist-source relationship. Mark explains why TIME does not generate journalism with AI, how the editorial team shaped the product’s voice and guardrails, and why every company needs to define what AI should never touch.
Finally, we explore the agentic web, AI crawlers, GEO, publisher monetization, brand-verified facts, and what it means to sell ads to robots. Mark shares how TIME is thinking about crawler blocking, AI citations, referral traffic, markdown pages, and the future of media as AI search changes how people find information.
Guest
Mark Howard — Chief Operating Officer, TIME
Follow AI-Curious on your favorite podcast platform:
Apple Podcasts
Spotify
YouTube
All Other Platforms
For anyone interested in Jeff’s AI Workshops for their company:
Reach out directly at jeff@jeffwilser.com

Will AI ever become conscious, or are we mistaking intelligence for inner life?
In this episode of AI-Curious, we talk with neuroscientist Anil Seth about one of the biggest questions in artificial intelligence: whether AI can truly become conscious. Anil is Professor of Cognitive and Computational Neuroscience at the University of Sussex, where he directs the Sussex Centre for Consciousness Science.
We explore why Anil believes today’s AI systems are not conscious, why language and intelligence are not the same as experience, and why humans are so quick to project minds onto machines. We also discuss his argument that consciousness may be deeply tied to living biological systems, rather than something that can simply be copied into silicon.
The conversation moves through neuroscience, philosophy, AI ethics, and the future of human relationships with machines. We talk about the cultural pull of Frankenstein, HAL, the singularity, and mind uploading, as well as the risks of assuming AI deserves rights if it only appears conscious. Anil also explains why brain organoids and biological systems may raise more serious consciousness questions than today’s chatbots.
Finally, we look at why this debate matters now, especially as people form emotional bonds with AI companions and increasingly interact with systems that can seem empathetic, aware, and alive.
Guest
Anil Seth — Professor of Cognitive and Computational Neuroscience, University of Sussex; Director, Sussex Centre for Consciousness Science
Follow AI-Curious on your favorite podcast platform:
Apple Podcasts
Spotify
YouTube
All Other Platforms
For anyone interested in Jeff’s AI Workshops for their company:
Reach out directly at jeff@jeffwilser.com

What happens when AI agents move from small experiments to full enterprise deployment?
In this episode of AI-Curious, we talk with Samantha Gloede, KPMG’s Global Head of Risk Services and Global Trusted AI Leader, about what it takes to govern AI agents at scale. KPMG is deploying and advising on AI across a global workforce and client base, giving Sam a rare view into how enterprise AI is actually working beyond the hype.
We explore what a governed agent fleet looks like, why AI agents need different levels of oversight depending on their risk, and how companies can avoid letting autonomous systems run without accountability. Sam explains KPMG’s framework for thinking about agents, from simpler task-based tools to more sophisticated collaborators and orchestrators that work across systems, teams, and workflows.
We also discuss why many organizations are investing heavily in AI but still struggling to prove ROI, and why CEO-level ownership, cross-functional strategy, data readiness, security, and change management are critical to scaling AI successfully. Sam shares where companies are seeing real traction, including technology, engineering, customer experience, onboarding, and value-chain transformation, as well as why regulated industries like finance and healthcare need extra care around transparency, compliance, and human oversight.
Finally, we get into the human side of AI adoption: whether companies are using AI to empower people or simply cut costs, how shadow AI emerges when employees do not have trusted tools, and how Sam uses AI in her own work and personal life as a working parent.
Guest
Samantha Gloede — Global Head of Risk Services and Global Trusted AI Leader, KPMG
Follow AI-Curious on your favorite podcast platform:
Apple Podcasts
Spotify
YouTube
All Other Platforms
For anyone interested in Jeff’s AI Workshops for their company:
Reach out directly at jeff@jeffwilser.com

Here’s a concise Apple Podcasts/Buzzsprout-ready version based on the Ari Peskoe transcript and its timestamps.
Are ordinary people helping pay for Big Tech’s AI build-out?
In this episode of AI-Curious, we talk with Ari Peskoe, director of the Electricity Law Initiative at Harvard Law School, about the growing fight over AI data centers, electricity demand, and who should pay for the infrastructure behind the AI boom.
As AI usage grows from simple chatbot prompts to more compute-heavy agentic workflows, data centers are becoming one of the most visible and controversial parts of the AI economy. We explore why these facilities require so much power, how they can strain local grids, and why the costs of new power plants, transmission lines, and utility upgrades may end up being spread across ordinary ratepayers.
Ari helps us unpack the utility business model, the role of public utility commissions, the PJM electricity market, and the strange economics of marginal cost, where the last and most expensive electron can affect prices for everyone. We also discuss whether data centers are paying their fair share, how communities are reacting, and what policy changes could help make sure the costs of AI infrastructure are more transparent and fairly allocated.
We also get into the local environmental concerns around data centers, including water use, diesel backup generators, noise, construction impacts, greenhouse gas emissions, and the tension between clean energy pledges and the speed of AI-driven demand growth.
Guest
Ari Peskoe — Director, Electricity Law Initiative, Harvard Law School
Follow AI-Curious on your favorite podcast platform:
Apple Podcasts
Spotify
YouTube
All Other Platforms
For anyone interested in Jeff’s AI Workshops for their company:
Reach out directly at jeff@jeffwilser.com