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Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders.

Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader.

Apr 29, 2019

Today we kick off our AI conference NY series with Pankaj Goyal, VP for AI & HPC product management at HPE, and Rochna Dhand, director of product management for HPE InfoSight.


Today we get things kicked off with Pankaj Goyal, VP for AI & HPC product management at HPE, and Rochna Dhand, director of product management...


Apr 26, 2019

For the final episode of our Strata Data series, we’re joined by Eric Colson, Chief Algorithms Officer at Stitch Fix, whose presentation at the conference explored “How to make fewer bad decisions.”

Our discussion focuses in on the three key organizational principles for data science teams that he’s developed at...


Apr 24, 2019

In this episode of our Strata Data conference series, we’re joined by Burcu Baran, Senior Data Scientist at LinkedIn.

At Strata, Burcu, along with a few members of her team, delivered the presentation “Using the full spectrum of data science to drive business decisions,” which outlines how LinkedIn manages their...


Apr 22, 2019

Today, in the first episode of our Strata Data conference series, we’re joined by Shioulin Sam, Research Engineer with Cloudera Fast Forward Labs.

Shioulin and I caught up to discuss the newest report to come out of CFFL, “Learning with Limited Label Data,” which explores active learning as a means to build...


Apr 19, 2019

Today we're joined by Paul Mahler, senior data scientist and technical product manager for machine learning at NVIDIA.

In our conversation, Paul and I discuss NVIDIA's RAPIDS open source project, which aims to bring GPU acceleration to traditional data science workflows and machine learning tasks. We dig into...