What makes data products popular? Brian T. O'Neill, Founder and Principal of Designing for Analytics, returns to the podcast to help us crack the code on building data products that people love.

Additional materials: www.superdatascience.com/658

Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

The Super Data Science Podcast: Machine Learning | AI | Success

658: How to Build Data and ML Products Users Love

AI visionary and CEO of SingularityNET Dr. Ben Goertzel provides a deep dive into the possible realization of Artificial General Intelligence (AGI) within 3-7 years. Explore the intriguing connections between self-awareness, consciousness, and the future of Artificial Super Intelligence (ASI) and discover the transformative societal changes that could arise.

This episode is brought to you by AWS Inferentia (https://go.aws/3zWS0au), the AWS Insiders Podcast (https://pod.link/1608453414), and by Modelbit (https://modelbit.com), for deploying models in seconds. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• Decentralized and benevolent AGI [03:13]
• The SingularityNET ecosystem [13:10]
• Dr. Goertzel's vision for realizing AGI - combining DL with neuro-symbolic systems, genetic algorithms and knowledge graphs [25:50]
• How reaching AGI will trigger Artificial Super Intelligence [38:51]
• Dr. Goertzel's approach to AGI using OpenCog Hyperon [42:34]
• Why Dr. Goertzel believes AGI will be positive for humankind [53:07]
• How to ensure the AGI is benevolent [1:06:43]
• How AGI or ASI may act ethically [1:13:50]

Additional materials: www.superdatascience.com/697

697: The (Short) Path to Artificial General Intelligence, with Dr. Ben Goertzel

In this episode of the ODSC Ai X Podcast, host Sheamus McGovern speaks with Sandi Besen, AI Engineer and Ecosystem Lead at IBM Research, about designing rule-based, production-ready AI agents using IBM’s open-source BeeAI framework. Sandi shares her journey from the performing arts to AI engineering, unpacks the challenges of agent reliability and trust, and explores how frameworks like BeeAI are solving real-world issues through enforceable rules, observability, and open standards. This episode dives deep into multi-agent systems, communication protocols, and what it really takes to deploy AI agents safely and effectively in enterprise environments.

Key Topics Covered:
Sandi’s background and current role at IBM Research
What inspired the creation of the BeeAI framework and platform
The concept of "agent chaos" and how BeeAI brings structure and reliability
Comparison of popular agent frameworks: LangChain, LangGraph, CrewAI
Introduction to emerging agent communication protocols (MCP and A2A)
Enforcing hardcoded rules (conditional requirements) in agents
Building agent behavior guardrails and preventing rogue actions
Importance of observability, memory, and tracing in agent frameworks
Using OpenTelemetry for tracing agent decision-making
Challenges in agent safety, validation, and trust for enterprise use
How BeeAI makes deploying an agent with a UI fast and easy (in under an hour)
When to build from scratch vs. using a framework like BeeAI 
Common mistakes startups make when adopting cutting-edge AI tech
Trends in context engineering and long-term memory
The future of consulting in the age of AI

Memorable Outtakes:
“Agent chaos is real. We needed a way to bring structure, enforce rules, and make agents safe for production.”
“Conditional requirements let you hardcode business logic into your agents — not just suggest behavior, but enforce it.”

References & Resources:
Sandi Besen – AI Engineer & Ecosystem Lead at IBM Research: https://research.ibm.com/people/sandi-besen
Website: https://sandibesen.com/
LinkedIn: https://www.linkedin.com/in/sandibesen/
BeeAI: https://www.ibm.com/think/news/beeai-open-source-multiagent
BeeAI GitHub Repository: https://github.com/i-am-bee/beeai-framework
Agent Communication Protocol (ACP) Course (DeepLearning.AI): https://www.deeplearning.ai/short-courses/acp-agent-communication-protocol/
OpenTelemetry:  https://opentelemetry.io/
Google’s P2 Payment Protocol (for AI agents): https://ap2-protocol.org/
AP2 GitHub: https://github.com/google-agentic-commerce/AP2
OpenAI Agent Commerce Protocol: https://developers.openai.com/commerce/

Sponsored by:
🔥 ODSC AI West 2025 – The Leading AI Training Conference
Join us in San Francisco from October 28th–30th for expert-led sessions on generative AI, LLMOps, and AI-driven automation.
Use the code podcast for 10% off any ticket.
Learn more: https://odsc.ai


AI Agents That Follow the Rules: Sandi Besen

In this debut episode of Data Renegades, CL Kao and Dori Wilson dive into the unconventional paths that led them into developer tools, civic tech, and machine learning systems. CL recounts his experience building early open source infrastructure, mobilizing communities through data transparency projects, and now shaping how we design software around LLMs. This episode sets the tone for the show’s mission: celebrating builders who redefine the boundaries of what tools can do.

Data Renegades - Ep. #1, Introducing Data Renegades

In this episode, host Sheamus McGovern is joined by Lake Dai (Founder, Sancus Ventures; AI Professor, Carnegie Mellon University) to unpack how venture capital invests in AI startups, what founders need to know, and how individuals with less capital can still participate meaningfully. Together they explore the shifting AI ecosystem—from model‑builders to tool‑builders—what VCs look for in teams, and how energy and infrastructure will soon become critical bottlenecks. Lake also shares her startup idea rooted in gamified simulation for workforce retraining and life‑skills development.

Key Topics Covered:
- What VCs are really looking for: signals, spending patterns from major foundation model firms, and how that drives investment strategy.
- The transition from “one or two foundation models” to a diverse array of open‑source tools and the implications for startup builders.
- Why choosing the right tools is one thing—but choosing where you drive them (i.e., product‑market fit + customer value) is the competitive advantage.
- How energy inefficiencies and infrastructure constraints (compute, cooling, power) are emerging as AI bottlenecks and investment opportunities.
- How solo founders or small teams can still add value to startups (e.g., as advisors/operators) and what boundaries and commitments matter.
- The importance of building your early team—whether co‑founders or advisors—with the same care you would in selecting a partner for life.
- Lake’s personal startup idea: a gamified simulation environment to train people in different roles and life skills, making learning fun and highly personal.
- Advice for younger listeners and first‑time investors: ways to plug into the startup ecosystem even without large capital.
- Practical questions that founders should ask a fund: What is the operating platform? What resources, networks, and buyer access does the fund provide?

Memorable Outtakes:
- Lake Dai: “I’m looking at it as if OpenAI, xAI, and Anthropic, who raise so much money, and where do they spend it? That’s where I invest.”
- Lake Dai: “You are the one that decides which direction you are going… at the end of the day, AI is a tool … you have to do something meaningful with it — find your product‑market fit and be the preferred provider of your customer.”
- Sheamus McGovern: “What Lake just described isn’t just a technical footnote — it’s a massive strategic pivot for the AI ecosystem: the next frontier isn’t just bigger models, it’s how we power and deploy them.”

References & Resources:
- Lake Dai (Sancus Ventures): https://www.sancus.vc/team/lake-dai
- LinkedIn: https://www.linkedin.com/in/lakedai/
- Stanford University AI Index Report (for data‑center energy trends): https://aiindex.stanford.edu

This episode was sponsored by:
 🔥 ODSC AI East 2026 – The Leading AI Training Conference
Join us in Boston from April 28th–30th for expert‑led sessions on Agentic AI, AI Engineering, Data Science, Machine Learning, LLMOps, and AI‑driven automation.
Learn more: https://odsc.ai/east

🧠 Agentic AI Summit – Learn to Build and Deploy Autonomous AI Systems
Happening online this January, the Agentic AI Summit is your chance to dive into hands‑on workshops and expert sessions on AI agents, workflows, and real‑world automation.
Use the code podcast for 10% off any ticket for either event
Learn more: https://summit.ai



The VC Playbook: AI Deals, Founders & Joining the Game with Lake Dai

In episode 4 of Data Renegades, CL Kao and Dori Wilson sit down with Micah Wylde. They trace his journey from building fraud detection at Sift Science to architecting massive real-time systems at Lyft and ultimately founding Arroyo. In this conversation, Micah breaks down the real complexity of streaming systems, why schema evolution is still the hardest challenge in data, and where the industry might move over the next five years.

Subscribe

Data Renegades - Ep. #4, Streaming Made Practical with Micah Wylde

In this episode of ODSC’s Ai X Podcast, host Alex Landa, Head of Content at ODSC, speaks with Dr. Denise Gosnell, an award-winning computer scientist, startup advisor, and global authority in graph technologies. Dr. Gosnell is the former Chief Data Officer at DataStax, holds multiple patents (including one from AWS for an enterprise-scale AI engine), and earned her PhD in Computer Science from the University of Tennessee. She is also the author of Tech Confidential and The Practitioner’s Guide to Graph Data.
This conversation explores the evolution of graph systems, why explainability still matters in modern AI, lessons learned from deploying massive systems under pressure, and how teams can adopt a context-first mindset to build AI that survives contact with the real world.

Key Topics Covered:
Early lessons from her PhD work and why explainability remains foundational in AI systems
The role of learning styles and vocabulary empathy in AI adoption
How engineering teams can avoid silos and build products by meeting customers where they are
What “embrace the chaos” really means, and how it helps teams ship real AI systems
Why context—not model size—is the true differentiator for enterprise AI
The four essential graph patterns: neighborhoods, trees, paths, and recommendations
Why paths are the most underused graph pattern and the ROI organizations miss when avoiding them
How organizations know they’re ready—or absolutely not ready—for a unified graph layer
The biggest misconceptions founders and CTOs have about AI adoption today
How intuition, empathy, and cross-functional collaboration influence high-performance technical teams
Advice for practitioners trying to prioritize, pivot, and build AI systems that deliver ROI

Memorable Outtakes:
“Explainability matters… executives aren’t very excited about probabilistic black boxes in production.”
“The most important thing that I have done—and that I know—is the fact that I really don’t know anything. Nobody knows everything.”
“Hiring one brilliant 10x engineer is not going to get you where you want to go. What matters is teamwork and a place where failures aren’t punished.”

References & Resources:
Guest Links:
Dr. Denise Gosnell – Website & Writing: https://denisegosnell.ai
LinkedIn: https://www.linkedin.com/in/denisekgosnell/
Instagram: https://instagram.com/denisegosnell.ai
Substack: https://substack.com/@denisegosnell
OpenDataScience Blog Series: https://opendatascience.com/from-graphs-to-generative-ai-building-context-that-pays-part-1/
Books by Denise Gosnell:
Tech Confidential – Published September 2025
The Practitioner’s Guide to Graph Data (O’Reilly)
Links to both: https://www.amazon.com/stores/Denise-Gosnell/author/B087DSH8SB

Sponsored by:
ODSC AI East 2026 – The Leading AI Training Conference
Join us in Boston from April 28th–30th for expert-led sessions on Agentic AI, AI Engineering, Data Science, Machine Learning, LLMOps, and AI-driven automation.
Learn more: https://odsc.ai/east

Agentic AI Summit – Learn to Build and Deploy Autonomous AI Systems
Happening online this January, the Agentic AI Summit is your chance to dive into hands-on workshops and expert sessions on AI agents, workflows, and real-world automation.
Use the code podcast for 10% off any ticket for either event.
Learn more: https://summit.ai


Context, Graphs, and Embracing Mistakes in AI with Denise Gosnell

An album by Tomi Kauppinen on four insights for creating information visualisations: the roles of stories, time, space and theme.

Podcast episode / track 1: stories
Podcast episode / Track 2: time
Podcast episode / Track 3: space
Podcast episode / Track 4: theme

Information visualisation: the roles of stories, time, space and theme

Infoviz: Theme

Infoviz: Time

Part of an album by Tomi Kauppinen on four insights for creating information visualisations: the roles of stories, time, space and theme.

Podcast episode / track 1: stories
Podcast episode / Track 2: time
Podcast episode / Track 3: space
Podcast episode / Track 4: theme

Infoviz: Time

Infoviz: Stories

Heavybit is the leading early-stage investor in enterprise infrastructure. Since 2013, we've helped launch and scale visionary technical startups—from DevSecOps and feature flagging to AI code generation and beyond. We go hands-on from day 0, backing founders as they turn code into companies and build the future of software from the bottom up to the top down.

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast.

As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.

Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.

We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

With Ai X Podcast, Open Data Science Conference (ODSC) brings its vast experience in building community and its knowledge of the data science and AI fields to the podcast platform. The interests and challenges of the data science community are wide ranging. To reflect this Ai X Podcast will offer a similarly wide range of content, from one-on-one interviews with leading experts, to career talks, to educational interviews, to profiles of AI Startup Founders. Join us every two weeks to discover what’s going on in the data science community.

Find more ODSC lightning interviews, webinars, live trainings, certifications, bootcamps here - https://aiplus.training/  
Don't miss out on this exciting opportunity to expand your knowledge and stay ahead of the curve.

Philosophy, Artificial Intelligence, Digital Art, Virtual Worlds, Poetry, Storytelling, Web3, Design Thinking, Online Learning, Information Visualization, Transdisciplinary Projects, Media Experiences - stay tuned for  the Season 5 of Cloud Reachers podcast to be aired on September 8th, 2022! Plus you can find here previous seasons of Cloud Reachers, and also extras &  shorts, and episodes covering topics for Tomi's explorative information visualisation course & beyond.

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