AI in NYC Show

In Episode 20 of AI in NYC, we welcome back our original guest — Charlie O'Donnell — to talk about his upcoming book 'Founder Unfriendly: What Investors Won't Tell You About Getting Funded.' Charlie has spent years in the NYC venture ecosystem helping founders navigate the opaque, often misleading world of fundraising, and this book is his attempt to arm the 99% of founders who aren't insiders with the real playbook. Charlie breaks down why the feedback you get from VCs almost never reflects the real reason they passed, how junior associates can inadvertently string you along, and why the fundraising process actually starts way before you ever pitch a deck — possibly as far back as high school. He also shares a fascinating look at how he used AI to organize and structure a 250-page book from a messy list of inside-joke chapter titles. We also discuss the emotional arc of founding a company — including why the day you announce your startup might be the most dangerously misleading day of all. If your network congratulated you but didn't offer a single customer intro, that's a signal worth paying attention to. Whether you're a first-time founder or a repeat entrepreneur, this episode is packed with honest, practical insight you won't hear in a typical VC blog post. Sponsored by BePresent (bepresentapp.com) — the #1 app in its category that uses social media engagement techniques to keep you OFF your phone. Also: join us April 15th at 5:30 PM for our first in-person Cloud Code class for non-technical people in NYC!

In this episode of AI in NYC, Rob and Ryan sit down with Zachary Smith, co-founder of Datum, to explore why the foundational infrastructure of the internet needs a radical overhaul for the AI era. Zach — a lifelong New Yorker who traded a classical music career at Juilliard for the wild world of Linux web hosting in 2001 — brings a rare depth of experience spanning multiple companies, acquisitions, and a front-row seat inside Equinix, one of the largest interconnection companies on Earth.Zach introduces his concept of the 'splinternet' — a world where geopolitics, regulation, and the demands of AI workloads are fragmenting the once-unified internet — and explains why Datum is building an open network cloud to serve the next wave of what he calls 'alt clouds': the roughly one thousand (and growing) new cloud providers that don't fit neatly into the old hyperscaler model. From Databricks to GPU startups to niche SaaS platforms, Zach argues these alt clouds need shared infrastructure primitives they can't afford to build alone.The conversation also gets deeply personal. Zach opens up about the emotional toll of selling his first bootstrapped company after 11 years, the therapy and intentional downtime he needed before starting again, and the unique dynamic of building multiple companies with his identical twin brother Jacob. His mentor Bill Luby's advice — 'this is the best time because you have no past' — becomes a throughline for how Datum approaches building for the long term in a world obsessed with speed.Whether you're a founder, an infrastructure nerd, or just curious about how the physical internet actually works, this episode is packed with insights about what's changing beneath the surface of every AI application you use. Tune in for one of the most thoughtful conversations we've had about the invisible plumbing of the internet age. Check out datum: https://datumdata.ai/ Thank you to our sponsor: BePresent - Download their app here: https://apps.apple.com/us/app/bepresent-screen-time-control/id1644737181

What happens when AI meets your brain data? In Episode 18 of AI in NYC, Rob May and Anna Kirk sit down with Kristen Mathews, cyber/data/privacy partner at Cooley LLP with nearly 30 years of experience, who has carved out a fascinating niche at the intersection of privacy law and neurotechnology. Kristen breaks down what neurotech actually is — from invasive brain implants to consumer wearable headbands — and explains how AI has been the key catalyst turning a century of brain signal data into actionable, decoded information. The conversation dives deep into the different categories of neurotech, including how devices can not only read brain activity but also stimulate it — with real applications like predicting seizures 20 minutes before they happen and suppressing them with electrical pulses. Rob shares his firsthand experience from sitting on the board of a neurotech company, while Kristen paints a vivid picture of the current landscape, including New York City's role as a major hub for the neurotech community. Perhaps the most thought-provoking segment explores the ethical frontier: the difference between decoding 'intended speech' (helping ALS patients communicate) and 'inner speech' (your private thoughts). Where's the line? Can AI tell the difference? Kristen is refreshingly honest about what we don't yet know, while emphasizing that every neurotech application she's seen in practice today is being used for good. This episode is essential listening for anyone interested in AI, privacy, the future of brain-computer interfaces, and why the next big privacy debate may be about your thoughts. Relevant links: www.nytimes.com/2003/06/22/magazine/savant-for-a-day.html https://icaot.org/jose-delgado-a-controversial-trailblazer-inneuromodulation/ Kristen Mathews on Linkedin: https://www.linkedin.com/in/kristen-mathews-6025257?utm_source=share&utm_medium=member_mweb&utm_campaign=share_via&utm_content=profile Download BePresent: https://apps.apple.com/us/app/bepresent-screen-time-control/id1644737181

n Episode 17 of AI in NYC, hosts Rob May, Ryan Eppley, and Anna Kirk sit down with Alayna Kennedy — Director of AI Governance at MasterCard — to talk about what it actually looks like to turn high-minded AI principles into real, operational governance inside one of the world's largest financial companies. Alayna brings a rare combination of hands-on AI model development experience (she built fraud detection models at IBM for a major federal agency) and deep academic credentials in fairness, accountability, and transparency in machine learning. The conversation digs into the gap between publishing a principles document and actually embedding ethics into your data pipeline, product development, and deployment process. Alayna shares insights from her master's thesis research, where she interviewed data scientists and governance teams across companies to find out who's really putting AI ethics into practice — and who's just posting it on a website. The team also explores the biggest concerns facing major enterprises when it comes to frontier models vs. open source, the ethical blind spots most people miss, and where the real resistance to AI adoption comes from inside large organizations. Whether you're building AI products, governing them, or just trying to understand how the biggest companies in the world are navigating this moment, this episode is packed with practical insight. Plus, stick around for the crew's favorite Saturday morning NYC activities Thank you to our sponsor: BePresent https://www.bepresentapp.com/ More of Alayna's work: https://alaynakennedy.github.io/