We've all done RAG, now what?
Longtime friend of the show Rajiv Shah returns to unpack lessons from a year of building retrieval-augmented generation (RAG) pipelines and reasoning models integrations. We dive into why so many AI pilots stumble, why evaluation and error analysis remain essential data science skills, and why not every enterprise challenge calls for a large language model.
Featuring:
Rajiv Shah – LinkedIn
Daniel Whitenack – Website, GitHub, X
Upcoming Events:
Join us at the Midwest AI Summit on November 13 in Indianapolis to hear world-class speakers share how they’ve scaled AI solutions. Don’t miss the AI Engineering Lounge, where you can sit down with experts for hands-on guidance. Reserve your spot today!
Register for upcoming webinars here!
598: Getting Kids Excited about STEM Subjects
Ben Taylor makes a fourth appearance on Five-Minute Friday to discuss the best ways to introduce STEM to children. Tune in to hear the many ways in which he thinks STEM education will evolve in the future.
Additional materials: www.superdatascience.com/598
596: The A.I. Platforms of the Future
Ben Taylor returns for a third Five-Minute Friday episode! This week, he looks ahead and digs into what we can expect from the A.I. platforms of the future.
Additional materials: www.superdatascience.com/596
594: Why CEOs Care About A.I. More than Other Technologies
This week, Jon Krohn and A.I. industry veteran Ben Taylor discuss the driving factors that push CEOs to prioritize A.I. over other technologies.
Additional materials: www.superdatascience.com/594
592: How to Sell a Multimillion Dollar A.I. Contract
In this episode, Jon Krohn welcomes A.I. industry veteran Ben Taylor to discuss how to sell multimillion dollar A.I. contracts. Tune in to hear why trust and proof of value are some of the critical steps in his sales process.
Additional materials: www.superdatascience.com/592
433: Data Science Trends for 2021
Ben Taylor joins us for the fourth time to discuss the upcoming 2021 trends in the world of data science as well as the post-COVID world.
In this episode you will learn:
Ben’s passion for AI [9:41]
Delivering results and KPIs [12:43]
DataRobot and AutoML [20:38]
Transparent storytelling [24:29]
Federated learning [31:37]
ML productionization [37:01]
AI ethics [46:01]
Emerging software packages/tools [54:39]
Remote work [1:02:44]
Additional materials: www.superdatascience.com/433
When data leakage turns into a flood of trouble
Rajiv Shah teaches Daniel and Chris about data leakage, and its major impact upon machine learning models. It’s the kind of topic that we don’t often think about, but which can ruin our results. Raj discusses how to use activation maps and image embedding to find leakage, so that leaking information in our test set does not find its way into our training set.
Sponsors:
DigitalOcean – DigitalOcean’s developer cloud makes it simple to launch in the cloud and scale up as you grow. They have an intuitive control panel, predictable pricing, team accounts, worldwide availability with a 99.99% uptime SLA, and 24/7/365 world-class support to back that up. Get your $100 credit at do.co/changelog.
Changelog++ – You love our content and you want to take it to the next level by showing your support. We’ll take you closer to the metal with no ads, extended episodes, outtakes, bonus content, a deep discount in our merch store (soon), and more to come. Let’s do this!
Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com.
Featuring:
Rajiv Shah – Website, GitHub, LinkedIn, X
Chris Benson – Website, GitHub, LinkedIn, X
Daniel Whitenack – Website, GitHub, X
Show Notes:
Rajiv Shah | University of Illinois at Chicago
Rajiv Shah | DataRobot Blog
DataRobot
Upcoming Events:
Register for upcoming webinars here!
AI for Good: clean water access in Africa
Chandler McCann tells Daniel and Chris about how DataRobot engaged in a project to develop sustainable water solutions with the Global Water Challenge (GWC). They analyzed over 500,000 data points to predict future water point breaks. This enabled African governments to make data-driven decisions related to budgeting, preventative maintenance, and policy in order to promote and protect people’s access to safe water for drinking and washing. From this effort sprang DataRobot’s larger AI for Good initiative.
Sponsors:
DigitalOcean – DigitalOcean’s developer cloud makes it simple to launch in the cloud and scale up as you grow. They have an intuitive control panel, predictable pricing, team accounts, worldwide availability with a 99.99% uptime SLA, and 24/7/365 world-class support to back that up. Get your $100 credit at do.co/changelog.
The Brave Browser – Browse the web up to 8x faster than Chrome and Safari, block ads and trackers by default, and reward your favorite creators with the built-in Basic Attention Token. Download Brave for free and give tipping a try right here on changelog.com.
AI Classroom – An immersive, 3 day virtual training in AI with Practical AI co-host Daniel Whitenack. Get 10% off using the code PRACTICALAI10. To learn more and purchase tickets go to datadan.io.
Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com.
Featuring:
Chandler McCann – LinkedIn
Chris Benson – Website, GitHub, LinkedIn, X
Daniel Whitenack – Website, GitHub, X
Show Notes:
Worldwide Water Access: Tapping into a Well of Data
AI for Good with DataRobot: Saving the World One Use Case at a Time
AI for Good: Powered by DataRobot
DataRobot
Upcoming Events:
Register for upcoming webinars here!
289: AI, Deepfakes and Call of Duty
In this episode of the SuperDataScience Podcast, I chat with top AI influencer, Ben Taylor. You will learn some very cool concepts about artificial intelligence such as active adverse impact mitigation, what that means and how that can help train on your dataset without bias. You will hear about AI ethics, deepfakes and Ben's current passion project, building an artificial intelligence that plays Call of Duty, which he will actually demonstrate at DataScienceGO this year at the end of September.
If you enjoyed this episode, check out the video, show notes, resources, and more at www.superdatascience.com/289
201: Emerging Technologies: Challenges and Opportunities in a Revolutionized World
In this episode of the SuperDataScience Podcast, we will listen to the Panel Discussion on emerging technologies during the DataScienceGO 2018 event in San Diego California, last October 12-14. Our panelists were 4 valuable persons in the space of Data Science, we have the Senior Solution Architect at NVIDIA - Mark Skinner, Manager of Data Science at TrueCar - Rachel Wang, Chief AI Officer at Ziff, Inc - Ben Taylor, and the world-renowned speaker, inventor, hacker, and entrepreneur - Pablos Holman. You will listen to a very insightful panel discussion we had during DSGO where we covered many topics including Blockchain, AI, Deep Learning, Machine Learning and disruption, startups, and a lot more.
If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/201
105: DataScienceGO’s Discussion Panel on Careers
In this episode of the SuperDataScience Podcast, we will listen to the Panel Discussion during the DataScienceGO 2017 event in San Diego California, last November 11-12. You will hear one of the insightful sessions that we had during the event - the Panel Discussion, together with our 3 guests - Ben Taylor, Urie Suhr and Hadelin de Ponteves. It was conducted during the second day of the event where everyone was able to submit their questions through Twitter using a special hashtag.
If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/105
085: The AI Revolution – What the Future Will Look Like
In this episode of the SuperDataScience Podcast, I chat with the Chief Data Officer at Ziff, Ben Taylor. You will hear about the future of AI & what the world could look like in future, learn about the different approaches to Deep Learning revolution, and also get to know the consequences of the oncoming AI developments.
If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/85
029: Dive Into Deep Learning and Find Out Where Machines Can Outperform Humans With Ben Taylor
In this episode of the SuperDataScience Podcast, I chat with Chief Data Scientist Ben Taylor. You will learn about the role of AI in recruitment, know about a crash course in deep learning and discuss on where machines can outperform humans.
If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/29
