Data Science Leaders

Wouldn’t it be great if there was a commonly agreed-upon framework for executing all AI projects successfully? Well, there isn’t one. However, there is CRISP-DM, the antediluvian “Cross-Industry Standard Process for Data Mining”, but you need to expand, modernize and adapt this framework for success at your organization.In this episode from the archive, Dave Cole interviews David Von Dollen, former Head of AI at Volkswagen of America, about how they integrated CRISP-DM into an Agile process to drive more rapid iteration and, ultimately, more successful AI projects.

What’s just as important as the government keeping us safe from AI? Government leveraging AI to keep us safe!In this episode, we interview Joel Meyer – former head of strategy at the Department of Homeland Security (DHS) and the person who drove the creation of the DHS AI Task Force. Joel shares how they identified key areas where they could apply AI to improve national safety and security, such as combating fentanyl and child sexual exploitation and abuse, and the steps that the federal government is taking to build AI capabilities across the public sector.Join us as we discuss:Key areas where US government agencies are looking to leverage AI to improve mission effectivenessThe people, process, and technology steps that government agencies are implementing to scale AI and how they apply to the private sectorThe importance and value of Responsible AI in public sector use cases and beyond

AI is disrupting drug discovery and development, driving the next wave of new treatments. The podcast discusses the exciting opportunities in this field and the need for frameworks, standards, and best practices. It also explores unifying systems and platforms in data science and the role of transformers in generative AI. Additionally, it addresses change management problems through relevant books and highlights the speaker's plans to contribute to industry publications.

Eric Siegel discusses the challenges of ML deployment and the importance of the BizML framework. He compares BizML to the CRISP-DM framework and highlights the shift towards real-time decision-making. The value of data engineering, leveraging humor in teaching, and the use of generative models are also explored.

Rowan Curran, Forrester Analyst, shatters myths surrounding GenAI. Topics include: differences between generative AI and predictive AI, limitations of large language models, role of ML engineers and MLOps in deploying GenAI, misconceptions in adopting generative AI at scale, and evolving model ops and the role of gender AI.

Imagine Generative AI handling tens of thousands of conversations with your customers daily. Science fiction? Not at Bolt where this has been in production since the summer of 2023. In this episode, Mikhail Korolev – head of the data science team at Bolt’s food delivery service – shares the challenges and hard earned best practices for operationalizing a GenAI application that dramatically lowers cost while also increasing customer satisfaction. Join us as we discuss:How to leverage GenAI to automate customer service conversationsHow to manage inconsistency and mitigate risk in GenAI appsHow to protect sensitive data and comply with regulatory requirements with GenAI

2023 has been an exciting year for AI, but it’s nothing in comparison to what we will see in 2024! Expect to see sensational successes amid the debris of projects that were set up for failure, a flowering of predictive AI, and the emergence of the scariest thing in AI to date (EU regulation). Tune in to this episode where Dr. Kjell Carlsson shares his top predictions for AI in 2024 and get ready for a year of scandal, fraud, plummeting processor prices, and ascendant AI leaders. Also, goodbye quantum computing! Happy holidays from all of us at Domino Data Lab and the Data Science Leaders podcast.

ChatGPT wasn’t the beginning of generative AI, but it did spark the GenAI revolution. Now, one year since it was launched, how much progress have we made, what impact is GenAI delivering, what are the real risks, and what developments are just around the corner? Join this session with the titan of the data science community, Anaconda CEO Peter Wang, and Dr. Kjell Carlsson, Head of AI Strategy at Domino Data Lab, where we will cover:The state of GenAI: where GenAI is delivering and missing expectationsThe challenges: the real risks and remaining barriers to impactThe future: what advances are underway and what can we expect over the next year

How do you achieve success as a Chief Data Officer? It is a role that is more important, yet more challenging, than it has ever been, with a rapidly expanding set of expectations from stakeholders in every part of the business.Here to help us understand the CDO role, its evolution, and the keys to success is Gary Barr, Global Chief Data Officer at Legal & General Investment Management (LGIM). Drawing from his wealth of experience, Gary speaks about the three incarnations of the CDO – from data governance champion to air traffic-controller of AI-driven transformation – as well as the dangers of dividing teams into “offense” and "defense”, the goal of the data mesh, and why AI regulation should be welcomed, not feared.Join us as we discuss:The rapid evolution of the CDO mandate and its responsibilitiesChanging the operating model for data and AI adoptionThe importance of qualitative and sentimental measures of ROI

Stephen Kosslyn, cognitive scientist and education innovator who led programs at Harvard, Stanford, and Minerva, and now heads Active Learning Sciences. He discusses AI as a cognitive amplifier. He outlines active learning by doing, scalable AI-driven role-play and assessments, personalization and deliberate practice, plus tools to prevent misuse and protect student data.