The biggest hurdle for data science teams isn't building the model; it's proving its dollar value. This presentation shows how a dental group could translate a no-show prediction model into a clear business case worth $$$

It's about shifting the conversation from abstract metrics to tangible ROI.

Henry Castellanos is a data scientist extraordinaire. He goes beyond establishing a strong technical performance for his ML models to also maximizing their business value. Let this sink in: Most data scientists don't do that – most ML projects don't plan and sell predictive AI deployment according to the the explicit business value.

Interestingly, Henry points out that using Gooder AI (www.gooder.ai) to do this even bucks up his own confidence in his models and their business value.

Listen to Henry's presentation to see exactly how to bridge the gap from ML to real-world value.

To view this presentation as a video, go to: https://youtu.be/BT-GnnuN3jA

In this episode, listen to a narration of Eric Siegel's article in Forbes:

Predictive AI Usually Fails Because It’s Not Usually Valuated

Most predictive AI deployments are scrubbed. Why? They didn't forecast the potential value in business terms like profit or savings.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/11/18/predictive-ai-usually-fails-because-its-not-usually-valuated/

In this episode, listen to a narration of Eric Siegel's article in Forbes:

AI Drives Alphabet’s Moonshot To Save The World’s Electrical Grid

AI is pivotal as global utilities tackle a looming crisis with the electrical grid. Here's how Alphabet uses AI to help the world keep the lights on.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/10/07/why-we-need-ai-alphabets-moonshot-to-save-the-worlds-electrical-grid/

In this episode, listen to a narration of Eric Siegel's article in Forbes:

To Deploy Predictive AI, You Must Navigate These Tradeoffs

Before deploying predictive AI, you must strike a balance between competing business factors. Here's how.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/08/27/to-deploy-predictive-ai-you-must-navigate-these-tradeoffs/

• One compelling reason to focus on predictive AI more than genAI.
• Why it's a safe bet that some consumer-facing LLMs will eventually be given too much "power," resulting in unexpected exposed vulnerabilities and costly lessons – and one way in which we can now work against that.
• How Michael's team created a pilot AI assistant in less than a day – and then launched it into wide-scale production in less than a week.

Excuse my furious typing noises (as I absorbed Michael’s compelling input) and I hope you find his insights as exciting as I did!

In this episode, listen to a narration of Eric Siegel's article in Forbes:

How Generative AI Helps Predictive AI

Large language models can act as predictive models. Here's an example for misinformation detection—and an introduction to savings curves.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/08/21/how-generative-ai-helps-predictive-ai/

In this episode, listen to a narration of Eric Siegel's article in Forbes:

The Quant's Dilemma: Subjectivity In Predictive AI's Value

When machine learning fails to detect misinformation, medical conditions or spam, the cost of each error is subjective. Here’s how to apply predictive AI nonetheless.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/09/30/the-quants-dilemma-subjectivity-in-predictive-ais-value/