In this episode, Eric Siegel narrates his article in Forbes, "Meta’s New GenAI Is Theatrical. Here’s How To Make It Valuable."Concern about a generative AI bubble is growing. To defend against disillusionment, measure its concrete value.Acces

Forbes Article: Artificial General Intelligence Is Pure Hype

13 days ago 9m 24s

In this episode, Eric Siegel narrates his article in Forbes, "Artificial General Intelligence Is Pure Hype."The belief that we’re gaining ground on AGI is misguided—reports of the human mind's looming obsolescence have been greatly exaggerated

Forbes Article: AI Success Depends On How You Choose This One Number

28 days ago 9m 9s

In this episode, Eric Siegel narrates his article in Forbes, "AI Success Depends On How You Choose This One Number."AI can drive millions of operational decisions, but first the business must strategically select a single number that different

Where FICO Gets Its Data for Screening Two-Thirds of All Card Transactions

28 days ago 16m 50s

In this episode, Eric Siegel narrates his article in The European Business Review, "Where FICO Gets Its Data for Screening Two-Thirds of All Card Transactions."The detection of fraudulent credit card transactions is an ideal candidate for the

Forbes Article: 3 Ways Predictive AI Delivers More Value Than Generative AI

Mar 11th, 2024 11m 29s

In this episode, Eric Siegel narrates his article in Forbes, "3 Ways Predictive AI Delivers More Value Than Generative AI."Generative AI attracts headlines, but predictive AI delivers greater value. This article covers three ways predictive AI

SMR Article: The Rare, Crucial Move to Business Metrics for Establishing ML's Value

Feb 26th, 2024 18m 52s

In this episode, Eric Siegel narrates his article in MIT Sloan Management Review, "What Leaders Should Know About Measuring AI Project Value."Most AI/machine learning projects report only on technical metrics that don’t tell leaders how much b

Five insights from "The AI Playbook"

Feb 13th, 2024 18m 3s

This episode covers five insights from the new book, The AI Playbook, which come from a piece originally published by The Next Big Idea Club.On a related note, the book has been included as a Next Big Idea Club Must Read.Also, here is the boo

The AI Playbook – book launch, early reviews, FAQ

Feb 6th, 2024 23m 31s

I'm excited to announce that today, my new book has published!The AI Playbook: Mastering the Rare Art of Machine Learning DeploymentInfo at: http://www.bizML.comIn my first book, Predictive Analytics, I explained how machine learning works.

HBR Article: The AI Hype Cycle Is Distracting Companies

Jan 31st, 2024 14m 54s

In this episode, Eric Siegel narrates his article in The Harvard Business Review, "The AI Hype Cycle Is Distracting Companies."Access the original article here: https://hbr.org/2023/06/the-ai-hype-cycle-is-distracting-companiesLearn more abou

HBR Article Narration: Getting Machine Learning Projects from Idea to Execution

Jan 23rd, 2024 15m 57s

In this episode, Eric narrates his new Harvard Business Review article, "Getting Machine Learning Projects from Idea to Execution," adapted from his new book, The AI Playbook.Access the article: https://hbr.org/2024/01/getting-machine-learning

THE AI PLAYBOOK – Announcement and Free Audiobook Offer

Jan 2nd, 2024 11m 56s

Announcing Eric Siegel's new book:The AI Playbook: Mastering the Rare Art of Machine Learning DeploymentInfo: www.bizML.comThis podcast episode includes a book overview, book sample – the opening of the book's Introduction – and a free audio

Five Reasons to Go to Machine Learning Week, June 19-24 2022 in Vegas

Apr 4th, 2022 19m 8s

In this special episode, rather than the usual conceptual coverage of machine learning, Eric Siegel will pitch you on the machine learning conference series he founded in 2009, the leading cross-vendor, cross-industry event covering the commerc

Four Things the Machine Learning Industry Must Learn from Self-Driving Cars

Mar 21st, 2022 28m 24s

When it comes to deploying machine learning, we must learn from the self-driving car movement – both to gain inspiration as to what it takes and as a major cautionary tale as to what mistakes to avoid. This episode covers four things the entire

Why Deep Learning Could Expedite the Next AI Winter

Feb 28th, 2022 28m 24s

Deep learning, the most important advancement in machine learning, could inadvertently expedite the next AI winter. The problem is that, although it increases value and capabilities, it may also be having the effect of increasing hype even more

P-Hacking: How to Know Your Predictive Discovery Is Conclusive

Feb 10th, 2022 41m 9s

“An orange used car is least likely to be a lemon.” At least that’s what was claimed by The Seattle Times, The Huffington Post, The New York Times, NPR, and The Wall Street Journal. However, this discovery has since been debunked as inconclusiv

Real-Time Machine Learning: Why It’s Vital and How to Do It

Jan 31st, 2022 33m 11s

Organizations often miss the greatest opportunities that machine learning has to offer because tapping them requires real-time predictive scoring. In order to optimize the very largest-scale processes – which is a vital endeavor for your busine

The Accuracy Fallacy and the Media’s Bogus Coverage of AI

Jan 24th, 2022 30m 41s

Misleading headlines abound, claiming that machine learning can "accurately" predict criminality, psychosis, sexual orientation, and bestselling books. But, when practitioners claim their model achieves "high accuracy," it's often bogus. Can AI

Models Are Rarely Deployed – an Industrywide Failure in Machine Learning Leadership

Jan 15th, 2022 26m

Our latest industry poll reconfirms today's dire industry buzz: Very few machine learning models actually get deployed. In this episode, I summarize the poll results and argue that this pervasive failure of machine learning projects comes from

Trailer

Trailer for The Dr. Data Show with Eric Siegel

Jan 15th, 2022 3m 28s

Eric Siegel covers why machine learning is the most important, most potent, most screwed up, most misunderstood, and most dangerous technology. And did I mention most important?

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