AI in NYC Show

Listen to Rob, Anna, and Ryan discuss the New York tech scene and recent

AI articles with Charlie O'Donnell. Charlie is a life long New Yorker

and long time venture capitalist. He discusses his experience working

for Josh Kopelman and Fred Wilson, two of the most successful venture

capitalists of all time, and the key catalysts that have turned NYC into

a dominant hub for AI.

Charlie's blog - thisisgoingtobebig.com

Welcome to exhilarating episode of AI Innovators with Rob May!

In this episode, Rob is joined by Dan Schwarz, founder of FutureSearch, for an in-depth conversation about the future of artificial intelligence and the pivotal role forecasting plays in understanding where AI is headed. Unlike any previous guest, Dan brings his unique perspective as a leader of a company that leverages AI to predict the future of AI itself.

Dan and Rob dig into some of FutureSearch’s boldest forecasts—like predictions on OpenAI’s 2027 revenue and the emerging business models that could power an intelligence explosion.

They explore how AI-driven forecasting is dramatically improving the ability to answer tough questions about technology, industry disruption, and the timeline for true superintelligence.

Dan shares FutureSearch’s methodology, the importance of track records in making credible predictions, and why the next wave of AI revenue is likely to come from “agents” rather than traditional products like ChatGPT.

Throughout the episode, you'll get insights into the challenges and opportunities facing foundational model companies like OpenAI and Anthropic, the impact of disruptive new technologies, and why positive feedback loops could make AI’s evolution much faster—and more surprising—than most expect.

Whether you’re an investor, technologist, or just fascinated by AI’s rapid progress, this episode is loaded with expert analysis, real-world examples, and forward-looking ideas to keep you ahead of the curve.

• Costs and Investment: OpenAI is burning through far more capital than previous tech companies due to the enormous compute costs required for their models. The money they’ve raised is more about meeting these high operating expenses than signaling runaway revenue success.

• Competition and Technological Disruption: Key risks include rivals (like Anthropic, Google) overtaking OpenAI in model quality. There’s also the ever-present possibility that a left-field technology breakthrough could upset current leaders.

• Forecasting Superintelligence: Future Search contributed to AI 2027, a collaborative forecast about the path to superintelligence. Dan sees the automation of coding, followed by automated AI research, as critical “dominoes” that could lead to an intelligence explosion—though he’s skeptical about this all happening extremely soon.

• Limits to Forecasting: There are fundamental, probabilistic limits to what either humans or AI can forecast—some things simply can’t be known in advance due to inherent uncertainty (like specific “black swan” events), but much of the world is more predictable than people expect when approached rigorously.

Dan's Links

(Linkedin)

futuresearch.ai

02:00 – Establishing Credibility Through Track Records: Why past performance and reputation matter when building trust in AI leadership.

06:22 – ChatGPT as OpenAI’s Revenue Engine: A look at how ChatGPT has become a central monetization tool for OpenAI.

07:06 – The $100B Vision: OpenAI’s Agent Strategy: Exploring how autonomous AI agents could be the key to OpenAI's next major growth phase.

13:06 – AI in 2027: The Road to Superintelligence: Predictions and pathways leading toward artificial general intelligence in the next few years.

15:54 – The Human Edge in Forecasting: Why human intuition still holds value against algorithmic predictions—at least for now.

17:29 – AI and the Rise of Superhuman Forecasting: How advanced AI models are already beginning to outperform human experts in prediction accuracy.

23:18 – Strategic Insights for AI Investors: Key considerations and principles when evaluating long-term AI investments.

Welcome to exhilarating episode of AI Innovators with Rob May!

In this episode, we explore the transformative power of AI in marketing and branding with our distinguished guests: Catherine Perloff, a journalist focused on the advertising business of big tech platforms, and Noah Brier, an entrepreneur passionate about integrating AI into marketing strategies.

Catherine and Noah delve into how AI is reshaping the advertising landscape by enabling creativity and accelerating content creation. They discuss the challenges marketers face with AI adoption, such as the slow integration within large enterprises and concerns over data privacy and brand safety.

Rob, Catherine, and Noah also consider the future role of AI in branding and marketing, emphasizing the importance of maintaining strong brand identities in a rapidly evolving technological environment. Whether you're a marketer, technologist, or simply curious about AI's influence, this episode is packed with valuable insights to help you keep pace in the AI-driven world. Tune in to discover how AI experts are pushing the boundaries of what’s possible in marketing!

• AI in Marketing: Explore how AI is driving innovation in marketing by streamlining the creation of ads and enabling more dynamic advertising strategies.
• Challenges in AI Adoption: Learn about the hurdles large brands face in adopting AI, from legal barriers to cultural resistance within organizations.
• Branding and AI's Future: Gain insights into the evolving role of branding in an AI-centric world and how brands can position themselves for success amidst changing media landscapes.

Catherine's Links

(Linkedin)

Noah's Links

(Linkedin)

(brxnd.ai)

04:43 – AI in Advertising: How the advertising industry is embracing AI for creativity, targeting, and efficiency.

07:45 – Brand Renewal Through Experimentation: The role of AI in driving brand reinvention and creative risk-taking.

12:49 – AI Tools & Brand Identity: Balancing AI-generated content with quality control and brand authenticity.

14:22 – Data Sharing Dilemmas: Navigating the privacy, trust, and security challenges of AI data sharing.

19:45 – Rethinking Branding Fundamentals: Examining how AI is reshaping the core principles of branding.

20:49 – Global Brand Consistency: Leveraging AI to ensure cohesive brand experiences across international markets.

Welcome to another exciting episode of AI Innovators with Rob May! In this episode, we dive deep into the intersection of artificial intelligence and risk analysis with Scott Weller, co-founder of Enfi AI.

• Scott shares his insights on how AI is transforming the credit industry by streamlining the underwriting process, making commercial lending more efficient, and, ultimately, boosting economic growth.
• Rob and Scott discuss the challenges and solutions surrounding AI's role in financial services, including dealing with LLM hallucinations and building agent-based systems.
• Scott also reflects on the evolution of digital coworkers and their role in the future workforce.
• Whether you're an entrepreneur, technologist, or simply curious about AI's impact, this episode is packed with valuable insights on staying ahead in the AI-driven world. Tune in to explore the future possibilities with AI experts leading the charge!

Episode Highlights:

• Efficient Credit Analysis: Scott highlights how AI can streamline credit risk assessment by automating mundane tasks, allowing analysts to focus on more complex decision-making, ultimately enabling banks to lend more efficiently.
• Agent-Based Systems: He discusses the development of agentic systems that are fine-tuned to specific tasks, helping reduce errors like hallucinations and improving overall system reliability in data-heavy environments like finance.
• Future of Digital Workforces: Scott envisions a future where digital coworkers, empowered by natural language processing, work alongside humans to enhance productivity and drive innovation in various industries.

Scott's Links

(Linkedin)

(enfi.ai)

01:00 - Streamlining Credit Risk Assessment.

03:53 - "Agent Systems for Controlled AI Tasks."

08:12 - Future: Human-AI Workforce Collaboration.

13:19 - "Automate Mundane for Success."

16:16 - Trustworthy AI Models for Financial Services.

19:32 - Challenges in Agent Planning Accuracy.

21:34 - Optimizing Task Execution Plans.

24:05 - Join ENFI AI: AI Partnerships Invited.

Welcome to another episode of AI Innovators with Rob May, where we explore the transformative impact of artificial intelligence on various industries.

In this episode, we're joined by the insightful Karen Hao, a freelance journalist known for her expertise in AI and technology reporting.

Karen shares her unique journey from a mechanical engineering background to becoming a leading journalist covering AI advancements, initially at MIT Technology Review.

Together, Rob and Karen dive into pressing topics such as the current landscape of AI ethics, the rapid developments in AI capabilities, and the ongoing global competition in the AI space, particularly between the US and China.

Karen also provides a sneak peek into her forthcoming book on OpenAI, promising an in-depth look at one of the most influential companies in AI today.

Tune in to hear their thought-provoking discussion on the societal impacts of AI, the challenges of maintaining ethical standards in an ever-evolving field, and the importance of fostering international collaboration for the benefit of all.

00:42 - Karen Hao's career and unexpected start in AI journalism.

01:11 - Karen Hao's initial reluctance to cover AI and eventual realization of its significance.

02:31 - Exploration of AI research and its societal impacts.

03:31 - Society's preparedness to handle AI's ethical dilemmas.

03:59 - Complex world challenges ethical AI development.

05:33 - Race against time in AI development versus ethical consideration.

05:39 - Deep Seek's impact and reflection on AI industry's scaling beliefs.

07:45 - Thoughts on hardware as the only moat in AI development.

09:07 - Public market reactions and AI defensibility concerns.

10:30 - Discussion on AI hardware innovation and talent.

12:01 - Societal costs demand efficient AI hardware and software.

13:02 - Ethical concerns in AI development supply chains.

13:34 - Hope for innovative solutions to AI's power consumption.

14:30 - Silicon Valley's AGI obsession and skepticism.

15:29 - AGI's shifting definition and its relevance in AI development.

17:12 - Concerns over ideological divides hampering AI dialogue.

17:50 - US-China AI competition narrative's incorrectness.

19:37 - Importance of international collaboration in AI research.

20:20 - Shift from competition to cooperation for global AI progress.

20:42 - Book recommendation: "Non Zero" by Robert Wright.

20:49 - Karen Hao's book announcement and its focus on OpenAI.

21:18 - Inside story of OpenAI and future AI implications.

Karen Hao's Links

(Linkedin)

Welcome to another episode of the AI Innovators Podcast!

I'm your host, Rob May, and in today's episode, In today's episode, our distinguished guest is Joseph Jorgensen, the founder of Capsule Video.

Join us as Joseph shares the story behind Capsule, a ground-breaking AI-powered video editing platform designed to make video creation easier for businesses, especially large enterprises.

From the challenges of video content creation to the innovative ways Capsule leverages AI to streamline the editing process, Joseph provides invaluable insights into the dynamic intersection of technology and business.

AI Innovators Podcast is sponsored by Half Court Ventures and the Investing in AI newsletter, this episode promises to provide a wealth of knowledge for anyone interested in the cutting-edge developments in AI and their real-world applications.

Jorgensen provides a candid look into their strategic approach of integrating multiple AI models while maintaining the flexibility to adapt to rapidly evolving technology.

Key highlights include:

- How Capsule Video leverages AI to simplify video editing processes

- Their strategic focus on enterprise clients and brand consistency

- The challenges and solutions in implementing AI models effectively

- Practical insights into product development in the fast-moving AI landscape

This conversation is especially relevant for entrepreneurs, tech professionals, and anyone interested in the practical applications of AI in content creation. Jorgensen's parting wisdom about balancing celebration of achievements while maintaining forward momentum offers valuable perspective for aspiring business leaders.

Whether you're a startup founder, AI enthusiast, or business professional looking to understand the future of video content creation, this episode provides actionable insights and thought-provoking discussion about the role of AI in transforming traditional industries.

Joseph Jorgensen's Links

(https://capsule.video/)

(Linkedin)

(Joseph's Linkedin)

0:00:02 - Joseph Jorgensen introduces their platform philosophy.

0:00:13 - Rob May's podcast introduction and welcome.

0:00:48 - Joseph Jorgensen's greeting.

0:01:01 - Beginning of founding story discussion for Capsule.

0:03:09 - Discussion of AI video editing begins.

0:05:20 - Discussion about AI implementation strategy.

0:07:26 - Transition to business and go-to-market discussion.

0:09:12 - Sponsorship break (Half Court Ventures and Investing in AI newsletter).

0:09:55 - Discussion of AI model limitations and workarounds.

0:13:09 - Product strategy discussion in rapidly changing AI landscape.

0:15:11 - Discussion of problems they wish others would solve.

0:17:24 - Career advice segment begins.

0:19:38 - Closing remarks.

0:19:58 - Outro and subscription reminder.

Welcome to another episode of the AI Innovators Podcast!

I'm your host, Rob May, and in today's episode, we're wrapping up the year with a bang by looking ahead to AI in 2025. I've gathered a panel of AI experts from Half Court Ventures to discuss the current landscape, future trends, and the evolving challenges and opportunities in the AI sphere.

AI Innovators Podcast is sponsored by Half Court Ventures and the Investing in AI newsletter, this episode promises to provide a wealth of knowledge for anyone interested in the cutting-edge developments in AI and their real-world applications.

So, sit back, relax, and get ready to be inspired by the insights of the Half Court Ventures Team - Byron Galbraith, George Lin, and Eric Koziol

Episode Highlights:

• OpenAI's Market Position: Byron Galbraith, George Lin, and Eric Koziol analyze whether OpenAI remains the frontrunner in the AI industry amidst rising competition, legal challenges from Elon Musk, and varying business models.
• Big Tech's Dominance: We dive deep into the capabilities and future potential of major companies like Google, Nvidia, Meta, and Apple. With insights into compute power, custom chips, and the scaling of AI hardware, our panelists George Lin and Byron Galbraith provide a comprehensive outlook.
• Next-Gen AI Architectures: George Lin introduces his prediction on the shift beyond transformer architectures, citing innovative models like mamba and rwkv. The panel discusses how these could revolutionize AI by extending context and efficiency.
• Generative Media Breakthroughs: Byron Galbraith brings to light the impact of Flux models on the generative media space, the quest to reduce inference costs, and the shifting landscape of local versus cloud-based model training.
• Custom Software Development with AI: Eric Koziol delves into the notion of personalized software, where the cost of software development drops, enabling bespoke applications tailored to specific business processes. This segment examines both the benefits and potential drawbacks of this democratization.

Thanks for tuning in to the AI Innovators Podcast. Stay ahead of the curve by subscribing, and don't miss out on our next deep dive into AI trends and strategies!

0:00:50 - Addressing the status of OpenAI and competitive threats.

0:01:25 - Byron Galbraith on OpenAI's market position and technical challenges.

0:02:17 - Eric Koziol's take on OpenAI's market strength and technical weaknesses.

0:02:40 - George Lin's insights on OpenAI's expanded focus and business strategy.

0:03:38 - Opinions on changing from startup focus to big companies in AI.

0:04:24 - Eric Koziol highlighting Google's investments in energy and compute capacity.

0:05:17 - George Lin talks about Google's internal resources and AI integration.

0:06:06 - George Lin mentions Facebook's advantages concerning human-vetted training data.

0:06:24 - Byron Galbraith supports Google and Meta's positions in the AI space.

0:07:54 - Rob May suggests potential Apple advantages in AI.

0:08:30 - Eric Koziol comments on Apple's potential challenges in AI innovation.

0:08:48 - George Lin discusses Apple's MLX framework and potential in AI.

0:09:35 - Byron Galbraith on benchmarking Apple processors for AI tasks.

0:10:34 - Rob May transitions to individual interesting AI topics for discussion.

0:11:04 - George Lin predicts moving beyond transformer architecture in 2025.

0:12:08 - Byron Galbraith supports re-exploring recurrent models in AI.

0:13:21 - Eric Koziol on the need for evolving AI architecture.

0:13:34 - George Lin mentions advancements in computation and data collection tools for AI.

0:13:53 - Rob May moves to Byron's topic on generative media space.

0:14:29 - Byron Galbraith highlights the introduction and impact of the Flux model.

0:15:34 - George Lin discusses democratization and consumer hardware for AI models.

0:16:26 - Eric Koziol asks Byron about advancements in generative models and their progress.

0:17:44 - Byron Galbraith on the improvements and future of Flux and generative models.

0:18:20 - Byron Galbraith talks about Flux model capabilities and training efficiency.

0:19:26 - Rob May transitions to Eric's interesting topic on personalized software.

0:20:23 - Eric Koziol explains the concept of personalized software in businesses.

0:21:15 - George Lin questions if enterprises will adopt AI tools over enterprise-grade software.

0:21:39 - Eric Koziol on the trade-offs of homegrown software versus buying software.

0:22:36 - Byron Galbraith discusses the maintenance of software built using AI tools.

0:23:46 - Rob May concludes on the importance of monitoring the trend of personalized software.

0:24:26 - Closing remarks and call for listener feedback and guest suggestions.

Welcome to another exciting episode of the AI Innovators Podcast! I'm your host, Rob May, and today we have a truly special guest joining us: Kevin Novak.

Kevin is a former data scientist at Uber and now a venture capitalist with Rackhouse VC.

In this episode, we dive deep into fascinating topics surrounding the transformative power of AI in early-stage businesses, the evolving landscape of data and infrastructure, and the nuances of AI investment strategies.

Episode Highlights:

• Kevin delves into the shift from viewing data as a byproduct to recognizing its critical role in AI systems, and the implications of increasing AI demands on data centers and power capacity.
• We discuss the performance dynamics of large language models versus small, specialized AI models, and their future potential, including mobile integration.
• Kevin shares valuable insights into the unpredictable impacts of AI across various industries, the importance of continuous experimentation, and the concept of Harvard's "jagged frontier."
• We explore the strategic challenges and opportunities in AI-focused venture capital, Kevin's approach to early-stage investments, and the essential traits of successful startup teams.
• Kevin and I also touch upon the importance of deep customer relationships, managing AI’s operational complexities, and the evolving role of AI in enhancing current business metrics.

Sponsored by Half Court Ventures and the Investing in AI newsletter, this episode promises to provide a wealth of knowledge for anyone interested in the cutting-edge developments in AI and their real-world applications.

So, sit back, relax, and get ready to be inspired by the insights of Kevin Novak on the AI Innovators Podcast.

Kevin Novak's

(rackhouse.vc/)

(Kevin's Linkedin)

Rob's Links

( halfcourt.vc )

( Rob AI Newsletter )

01:00 - Determining genuine AI companies from buzzword claims.

06:40 - Focus on fundamentals, proprietary data, experienced AI team.

11:11 - Large language models grow with more resources.

13:00 - Limitations challenge scaling large language models.

16:52 - Balancing cost, profitability, and AI advancement challenges.

20:52 - Companies often dictate customer roles, causing insecurity.

22:44 - Adapting workflows to technology shifts drives success.

26:23 - Diligence pays off despite emotional misalignment.

29:27 - Invest globally, focus: complete businesses, max $2M.

Welcome to another exciting episode of the AI Innovators Podcast! I'm your host, Rob May, and today we're diving into a truly unique domain as we explore the intersection of AI and the insurance industry.

Our guest is Alex Schmelkin, CEO of Sixfold AI, a company that's revolutionizing how insurance companies underwrite policies.

In this episode, Alex gives us an insider look at the traditional human-led underwriting process and how Sixfold AI is reshaping this landscape with advanced AI technology. We discuss the challenges and opportunities in automating underwriting, the impressive ROI their solutions bring, and the intricacies of adapting AI across different insurance types.

Alex shares valuable insights into the decision-making journey of choosing to enable traditional insurance carriers rather than becoming one, and his perspective on the future of AI insurance. We also touch on the emerging field of AI model insurance and the critical role of document ingestion in their AI tech stack.

Get ready to learn from Alex’s vast experience and gain practical advice that every entrepreneur and AI enthusiast can apply. Whether you're in the insurance industry or simply fascinated by AI's transformative power, this episode is packed with valuable takeaways. So, tune in and join us on this deep dive into the future of AI in insurance!

Alex Schmelkin's Links

( https://sixfold.ai/)

(Linkedin)

(Alex's Linkedin)

Rob's Links

( halfcourt.vc )

( Rob AI Newsletter )

01:00 - Underwriters assess risk using vast data volumes.

04:54 - AI evaluates insurance applications for underwriting decisions.

08:14 - Innovators podcast by Half Court Ventures, AI.

11:38 - Enhancing insurance with advanced underwriting models.

15:16 - AI exclusions in insurance policies raise concerns.

17:44 - Reinsurance differs between life and PNC sectors.

21:39 - Focus on your core strength and excel.

23:12 - Target buyer's conference indicates optimal selling approach.

Welcome back to another episode of AI Innovators with Rob May, the podcast that deep dives into how AI is reshaping industries and the groundbreaking minds behind it.

In today's episode, we're joined by Pawel Zimoch, co-founder of Featrix AI, a company known for pioneering vectorization solutions for the enterprise.

As we explore the world of vectors and embeddings, Pawel unpacks the significance of data predictability and why some data sets work better with AI than others.

We'll also delve into the evolution of Featrix, from its founding story to its innovative strides in custom embeddings and multi-modal data analysis.

Whether you're an entrepreneur, a data scientist, or simply curious about the future of AI, this episode is packed with insights you won't want to miss. Tune in for a fascinating conversation on the complexities, challenges, and exciting advancements in the realm of AI.

Pawel Zimoch's Links

( Featrix.ai )

(Linkedin)

( Featrix)

Rob's Links

( halfcourt.vc )

( Rob AI Newsletter )

00:00 - Embeddings use cosine similarity for comparative analysis.

04:57 - Predictive data value varies; feature engineering necessary.

06:28 - Efficient AI system predicts project viability quickly.

12:04 - Human judgment and problem-solving skills prevail.

13:59 - Learning computer science is essential for understanding AI.

16:26 - Managing models requires significant context from data scientists.

22:28 - Connect with others for broader learning perspectives.

23:28 - Success in entrepreneurship relies on understanding people.