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Podcast Season 3

DataOps – Putting the Data in Data Science

The quality of an AI application depends on the quality of the data that feeds it

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Podcast Season 3

The Unique Challenges of ML Training Data with Bin Fan

Machine learning is unlike any other enterprise application, demanding massive datasets  from distributed sources

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Podcast Season 3

Challenges of Building Successful ML Programs

With so many AI tools available, it can be a challenge to integrate everything into a productive platform

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Podcast Season 3

How Algorithmic Bias in ML Affects Marketing

As machine learning is used to market and sell, we must consider how biases in models and data can impact society

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Podcast Season 3

The State of AI and the Enterprise

With AI technology changing so quickly, we often need to step back and take a big picture look at the market

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Podcast Season 3

Under the Hood of the Data Engine with Speedb

Data is the most important element of artificial intelligence, but how is that data managed and stored? In this episode of Utilizing AI, Adi Gelvan of Speedb goes deep under the hood to take a look at the data engine along with Frederic Van Haren and Stephen Foskett

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Podcast Season 3

GPU’s and AI accelerators – What is the difference?

AI is everywhere, and so are AI accelerators, from CPU to GPU to special-purpose hardware

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Podcast Season 3

Utilizing AI in 2022 with Chris Grundemann and Frederic Van Haren

AI is now widespread, and companies are starting to look at the real-world impact of machine learning

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Podcast Season 3

Utilization of Shadow AI with Run: AI

Shadow IT is as old as our profession, so it’s no surprise that shadow AI is becoming a major issue

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Podcast Season 3

AI is a Creativity Maximizer with Ben Taylor of DataRobot

Many of the tasks we perform on a daily basis are beneath our abilities, and these are the ideal targets for AI