Send us a text We’re back with Part 2 of our must-listen conversation with Dave Garrison, leadership strategist and veteran CEO, on what it really takes to unlock performance through engagement. In this episode, we go deeper into the psychological drivers of motivation — autonomy, mastery, and purpose — and explore how to stop employee churn, combat burnout, and lead with clarity (not just charisma). Plus: how to rethink your approach to hiring and the controversial take on using AI in leadership decisions. Stick around for a surprise recap guest who brings it all home. 💥 🕒 Time-Stamps: 00:12 – Autonomy, Mastery, Purpose 04:48 – How to Stop Churn 07:10 – Laying the Hammer Down 08:00 – Burnout 14:50 – Are You Using AI Wrong? 16:27 – Energy Level 17:40 – Coach Katherine Mayne's Take 19:57 – Hire for Aptitude, Fire for Attitude 22:19 – The Recap 🔗 Connect with Dave on LinkedIn 📘 Explore his book, Buy-In Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

In this episode, we go beyond the famous C. elegans connectome to explore how signal propagation doesn’t always follow the wires. Using powerful whole-brain calcium imaging combined with single-cell optogenetic activation, researchers mapped over 23,000 neuron pairings to build a functional atlas that rewrites parts of the worm’s wiring diagram.

We dive into:

How extrasynaptic neuropeptide signalling connects neurons outside synapses The discovery of functional connections invisible in the wiring diagram How C. elegans neural signals propagate both directly and indirectly The creation of a functional connectome that predicts spontaneous activity better than anatomy alone The surprising flexibility and plasticity of even simple nervous systems

📖 Based on the research article: “Neural signal propagation atlas of Caenorhabditis elegans” Francesco Randi, Anuj K. Sharma, Sophie Dvali & Andrew M. Leifer Published in Nature (2023). 🔗 https://doi.org/10.1038/s41586-023-06683-4

🎧 Subscribe to the WOrM Podcast for more full-organism neuroscience that goes deeper than the wires!

This podcast is generated with artificial intelligence and curated by Veeren. If you’d like your publication featured on the show, please get in touch.

📩 More info: 🔗 ⁠⁠www.veerenchauhan.com⁠⁠ 📧 [email protected]

This book is essential for anyone eager to understand the groundbreaking advancements in generative AI and its transformative effects across industries, making it a valuable resource for both professional growth and creative inspiration. Generative AI: Disruptive Technologies for Innovative Applications delves into the exciting and rapidly evolving world of generative artificial intelligence and its profound impact on various industries and domains. This comprehensive volume brings together leading experts and researchers to explore the cutting-edge advancements, applications, and implications of generative AI technologies. This volume provides an in-depth exploration of generative AI, which encompasses a range of techniques such as generative adversarial networks, recurrent neural networks, and transformer models like GPT-3. It examines how these technologies enable machines to generate content, including text, images, and audio, that closely mimics human creativity and intelligence. Readers will gain valuable insights into the fundamentals of generative AI, innovative applications, ethical and social considerations, interdisciplinary insights, and future directions of this invaluable emerging technology. Generative AI: Disruptive Technologies for Innovative Applications is an indispensable resource for researchers, practitioners, and anyone interested in the transformative potential of generative AI in revolutionizing industries, unleashing creativity, and pushing the boundaries of what’s possible in artificial intelligence. Audience AI researchers, industry professionals, data scientists, machine learning experts, students, policymakers, and entrepreneurs interested in the innovative field of generative AI.

This workshop is designed to equip software engineers with the skills to build and iterate on generative AI-powered applications. Participants will explore key components of the AI software development lifecycle through first principles thinking, including prompt engineering, monitoring, evaluations, and handling non-determinism. The session focuses on using multimodal AI models to build applications, such as querying PDFs, while providing insights into the engineering challenges unique to AI systems. By the end of the workshop, participants will know how to build a PDF-querying app, but all techniques learned will be generalizable for building a variety of generative AI applications.

If you're a data scientist, machine learning practitioner, or AI enthusiast, this workshop can also be valuable for learning about the software engineering aspects of AI applications, such as lifecycle management, iterative development, and monitoring, which are critical for production-level AI systems.

Artificial intelligence has been successfully applied to bioimage understanding and achieved significative results in the last decade. Advances in imaging technologies have also allowed the acquisition of higher resolution images. That has increased not only the magnification at what images are captured, but the size of the acquired images as well. This comprises a challenge for deep learning inference in large-scale images, since these methods are commonly used in relatively small regions rather than whole images. This workshop presents techniques to scale-up inference of deep learning models to large-scale image data with help of Dask for parallelization in Python.

Overview of dementia prediction using AI, and a summary of Henry Musto's work and plans for future research.

A fireside chat exploring Sovereign AI and the software-hardware stack to enable its adoption in the public sector, European enterprises, and regulated industries such as defense, manufacturing, BioTech, and FinTech. Date: 2025-07-08.

Drawing from practical lessons learned while building and maintaining customer-facing AI applications across Bloomberg Law, Bloomberg Tax, and Bloomberg Government, this talk explores the unique position of data-rich enterprises in today’s rapidly evolving AI landscape. These organizations possess deep reserves of proprietary data that foundational models have not seen during training. This talk will examine the strategic and technical considerations of leveraging such exclusive datasets, and how these enterprises can meaningfully participate in the AI transformation without developing their own models.

Discover the transformative potential of dark data: the vast amounts of collected but unused information. This presentation will explore real-world examples, technical challenges, and ethical considerations, equipping attendees with strategies to harness dark data for competitive advantage and responsible AI practices.

This talk covers how Python notebooks are evolving from static documents to interactive, collaborative, and production-ready environments, using Marimo. We’ll examine emerging trends—such as AI-powered and reactive notebooks, notebook-as-app frameworks, and integration with modern workflows—equipping attendees with insights to leverage notebooks to reshape coding, teaching, and scientific publishing.

While AI tools promise to revolutionize how developers write code, blindly trusting their output can introduce subtle, yet critical, vulnerabilities and bugs into our systems. The rapid adoption of AI in every corner of software development, from smart editors to automated code generation, presents new challenges for maintaining code quality and system integrity. This presentation will expose common, often overlooked, pitfalls developers face when leveraging AI for coding tasks.

This hands-on tutorial will guide participants through building an end-to-end AI agent that translates natural language questions into SQL queries, validates and executes them on live databases, and returns accurate responses. Participants will build a system that intelligently routes between a specialized SQL agent and a ReAct chat agent, implementing RAG for query similarity matching, comprehensive safety validation, and human-in-the-loop confirmation. By the end of this 4-hour session, attendees will have created a powerful and extensible system they can adapt to their own data sources.

Todd Olson joins me to talk about making analytics worth paying for and relevant in the age of AI. The CEO of Pendo, an analytics SAAS company, Todd shares how the company evolved to support a wider audience by simplifying dashboards, removing user roadblocks, and leveraging AI to both generate and explain insights. We also talked about the roles of product management at Pendo. Todd views AI product management as a natural evolution for adaptable teams and explains how he thinks about hiring product roles in 2025. Todd also shares how he thinks about successful user adoption of his product around “time to value” and “stickiness” over vanity metrics like time spent. 

Highlights/ Skip to:

How Todd has addressed analytics apathy over the past decade at Pendo (1:17) Getting back to basics and not barraging people with more data and power (4:02) Pendo’s strategy for keeping the product experience simple without abandoning power users (6:44) Whether Todd is considering using an LLM (prompt-based) answer-driven experience with Pendo's UI (8:51) What Pendo looks for when hiring product managers right now, and why (14:58) How Pendo evaluates AI product managers, specifically (19:14) How Todd Olson views AI product management compared to traditional software product management (21:56) Todd’s concerns about the probabilistic nature of AI-generated answers in the product UX (27:51) What KPIs Todd uses to know whether Pendo is doing enough to reach its goals (32:49)   Why being able to tell what answers are best will become more important as choice increases (40:05)

Quotes from Today’s Episode

“Let’s go back to classic Geoffrey Moore Crossing the Chasm, you’re selling to early adopters. And what you’re doing is you’re relying on the early adopters’ skill set and figuring out how to take this data and connect it to business problems. So, in the early days, we didn’t do anything because the market we were selling to was very, very savvy; they’re hungry people, they just like new things. They’re getting data, they’re feeling really, really smart, everything’s working great. As you get bigger and bigger and bigger, you start to try to sell to a bigger TAM, a bigger audience, you start trying to talk to the these early majorities, which are, they’re not early adopters, they’re more technology laggards in some degree, and they don’t understand how to use data to inform their job. They’ve never used data to inform their job. There, we’ve had to do a lot more work.” Todd (2:04 - 2:58) “I think AI is amazing, and I don’t want to say AI is overhyped because AI in general is—yeah, it’s the revolution that we all have to pay attention to. Do I think that the skills necessary to be an AI product manager are so distinct that you need to hire differently? No, I don’t. That’s not what I’m seeing. If you have a really curious product manager who’s going all in, I think you’re going to be okay. Some of the most AI-forward work happening at Pendo is not just product management. Our design team is going crazy. And I think one of the things that we’re seeing is a blend between design and product, that they’re always adjacent and connected; there’s more sort of overlappiness now.” Todd (22:41 - 23:28) “I think about things like stickiness, which may not be an aggregate time, but how often are people coming back and checking in? And if you had this companion or this agent that you just could not live without, and it caused you to come into the product almost every day just to check in, but it’s a fast check-in, like, a five-minute check-in, a ten-minute check-in, that’s pretty darn sticky. That’s a good metric. So, I like stickiness as a metric because it’s measuring [things like], “Are you thinking about this product a lot?” And if you’re thinking about it a lot, and like, you can’t kind of live without it, you’re going to go to it a lot, even if it’s only a few minutes a day. Social media is like that. Thankfully I’m not addicted to TikTok or Instagram or anything like that, but I probably check it nearly every day. That’s a pretty good metric. It gets part of my process of any products that you’re checking every day is pretty darn good. So yeah, but I think we need to reframe the conversation not just total time. Like, how are we measuring outcomes and value, and I think that’s what’s ultimately going to win here.” Todd (39:57)

Links

LinkedIn: https://www.linkedin.com/in/toddaolson/  X: https://x.com/tolson  [email protected] 

Today, we’re joined Marne Martin, the CEO of Emburse whose innovative travel and expense solutions power forward-thinking organizations. We talk about:  Building fast-moving & scalable businesses that can lastHow to finance and grow profitable companies to reach an exitThe challenges of finding a competitive edge as GenAI accelerates innovationTesting monetizing AI alongside conventional SaaS monetization

Tired of spending money on data courses you never finish? Here are 7 essential books that will actually boost your analytical skills, with no subscription required! Plus, make sure to tune in till the end as one lucky listener will get a free book from this list! Get the books here! DISCLAIMER: Some of the links in this video are affiliate links, meaning if you click through and make a purchase, I may earn a commission at no extra cost to you. Storytelling with Data by Cole Nussbaumer Knaflic 👉 https://amzn.to/3ZYHhsG Ace the Data Science Interview by Nick Singh and Kevin Huo 👉 https://amzn.to/3XZ9IaB Moneyball by Michael Lewis 👉 https://amzn.to/44fy4OD The StatQuest Illustrated Guide To Machine Learning by Josh Starmer 👉 https://amzn.to/40hRgu2 Fundamentals of Data Engineering by Joe Reis and Matt Housley 👉 https://amzn.to/3W84K8K Data Science for Business by Foster Provost and Tom Fawcett 👉 https://amzn.to/4k7jkaD The Big Book of Dashboards by Steve Wexler, Jeffrey Shaffer, and Andy Cotgreave 👉 https://amzn.to/462GJVj 💌 Join 10k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://www.datacareerjumpstart.com/newsletter 🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://www.datacareerjumpstart.com/training 👩‍💻 Want to land a data job in less than 90 days? 👉 https://www.datacareerjumpstart.com/daa 👔 Ace The Interview with Confidence 👉 https://www.datacareerjumpstart.com/interviewsimulator ⌚ TIMESTAMPS 00:16 Book 1: The Big Book of Dashboards 02:52 Book 2: Data Science for Business 04:38 Book 3: Fundamentals of Data Engineering 06:05 Book 4: The StatQuest Illustrated Guide To Machine Learning 07:52 Book 5: Moneyball 10:09 Book 6: Ace the Data Science Interview 11:24 Book 7: Storytelling With Data I've interviewed some of these awesome data authors! Check out these episodes! Stats You Need to Know as a Data Analyst (w/ StatQuest) 👉 https://datacareerpodcast.com/episode/105-do-you-have-to-be-good-at-statistics-to-be-a-data-analyst-w-statquest-josh-starmer-phd How to Ace The Data Science & Analytics Interview w/ Nick Singh 👉 https://datacareerpodcast.com/episode/74-how-to-ace-the-data-science-analytics-interview-w-nick-singh Meet The Woman Who Changed Data Storytelling Forever (Cole Knaflic) 👉 https://datacareerpodcast.com/episode/142-meet-the-woman-who-changed-data-storytelling-forever-cole-knafflic

🔗 CONNECT WITH AVERY 🎥 YouTube Channel: https://www.youtube.com/@averysmith 🤝 LinkedIn: https://www.linkedin.com/in/averyjsmith/ 📸 Instagram: https://instagram.com/datacareerjumpstart 🎵 TikTok: https://www.tiktok.com/@verydata 💻 Website: https://www.datacareerjumpstart.com/ Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

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Technology and human consciousness are converging in ways that challenge our fundamental understanding of creativity and connection. As AI systems become increasingly sophisticated at mimicking human thought patterns, we're entering uncharted territory where machines don't just assist creative work—they actively participate in it. But what does this mean for the future of human creativity and our relationship with technology? How do we maintain meaningful human connections in a world where emotional labor is increasingly commoditized? As we navigate this rapidly evolving landscape, the question isn't just whether machines can think, but how their thinking will transform our own. Ken Liu is an American author of speculative fiction. A winner of the Nebula, Hugo, and World Fantasy awards, he wrote the Dandelion Dynasty, a silkpunk epic fantasy series, as well as short story collections The Paper Menagerie and Other Stories and The Hidden Girl and Other Stories. His latest book is All that We See or Seem, a techno-thriller starring an AI-whispering hacker who saves the world. He also translated Cixin Liu’s seminal book series, the Three-Body Problem.  He’s often involved in media adaptations of his work. Recent projects include “The Regular,” under development as a TV series; “Good Hunting,” adapted as an episode in season one of Netflix’s breakout adult animated series Love, Death + Robots; and AMC’s Pantheon, with Craig Silverstein as executive producer, adapted from an interconnected series of Liu’s short stories.  Prior to becoming a full-time writer, Liu worked as a software engineer, corporate lawyer, and litigation consultant. Liu frequently speaks on a variety of topics, including futurism, machine-augmented creativity, history of technology, bookmaking, and the mathematics of origami. In the episode, Adel and Ken explore the intersection of technology and storytelling, how sci-fi can inform AI's trajectory, the role of AI in reshaping human relationships and creativity, how AI is changing art, and much more. Links Mentioned in the Show: Ken’s BooksKen on Substack, Ken on XSkill Track: AI FundamentalsRelated Episode: What History Tells Us About the Future of AI with Verity Harding, Author of AI Needs YouRewatch RADAR AI  New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Eager to learn AI and machine learning but unsure where to start? Laurence Moroney's hands-on, code-first guide demystifies complex AI concepts without relying on advanced mathematics. Designed for programmers, it focuses on practical applications using PyTorch, helping you build real-world models without feeling overwhelmed. From computer vision and natural language processing (NLP) to generative AI with Hugging Face Transformers, this book equips you with the skills most in demand for AI development today. You'll also learn how to deploy your models across the web and cloud confidently. Gain the confidence to apply AI without needing advanced math or theory expertise Discover how to build AI models for computer vision, NLP, and sequence modeling with PyTorch Learn generative AI techniques with Hugging Face Diffusers and Transformers