Conversations with the people building AI
Today we’re joined by Jürgen Schmidhuber, Co-Founder and Chief Scientist of NNAISENSE, the Scientific Director at IDSIA, as well as a Professor of AI at USI and SUPSI in Switzerland. Jürgen’s lab is well known for creating the Long Short-Term Memory (LSTM) network, and in this conversation, we discuss some of the…
34 MinutesThe TWIML AI Podcast
Beidi Chen is part of the team that developed a cheaper, algorithmic, CPU alternative to state-of-the-art GPU machines. They presented their findings at NeurIPS 2019 and have since gained a lot of attention for their paper, SLIDE: In Defense of Smart Algorithms Over Hardware Acceleration for Large-Scale Deep Learning…
32 MinutesThe TWIML AI Podcast
Today we're joined by Sergey Levine, an Assistant Professor at UC Berkeley. We last heard from Sergey back in 2017, where we explored Deep Robotic Learning. Sergey and his lab’s recent efforts have been focused on contributing to a future where machines can be “out there in the real world, learning continuously…
43 MinutesThe TWIML AI Podcast
Matt Brems from General Assembly joins us to explain what “data science” actually means these days and how that has changed over time. He also gives us some insight into how people are going about data science education, how AI fits into the data science workflow, and how to differentiate yourself career-wise.…
49 MinutesPractical AI
Imagine spending years learning ML from the ground up, from its theoretical foundations, but still feeling like you didn’t really know how to apply it. That’s where David Odaibo found himself in 2015, after the second year of his PhD. David’s solution was Kaggle, a popular platform for data science competitions. Fast…
41 MinutesThe TWIML AI Podcast
Predicting the future of science, particularly physics, is the task that Matteo Chinazzi, an associate research scientist at Northeastern University focused on in his paper Mapping the Physics Research Space: a Machine Learning Approach. In addition to predicting the trajectory of physics research, Matteo is also…
35 MinutesThe TWIML AI Podcast
Craig Wiley, from Google Cloud, joins us to discuss various pieces of the TensorFlow ecosystem along with TensorFlow Enterprise. He sheds light on how enterprises are utilizing AI and supporting AI-driven applications in the Cloud. He also clarifies Google’s relationship to TensorFlow and explains how TensorFlow…
48 MinutesPractical AI
The unfortunate reality is that many of the most commonly used machine learning metrics don't account for the complex trade-offs that come with real-world decision making. This is one of the challenges that Sanmi Koyejo, assistant professor at the University of Illinois, has dedicated his research to address. Sanmi…
56 MinutesThe TWIML AI Podcast
Today we’re joined by Ilias Diakonikolas, faculty in the CS department at the University of Wisconsin-Madison, and author of the paper Distribution-Independent PAC Learning of Halfspaces with Massart Noise, recipient of the NeurIPS 2019 Outstanding Paper award. The paper is regarded as the first progress made around…
36 MinutesThe TWIML AI Podcast
Expanding AI technology to the local languages of emerging markets presents huge challenges. Good data is scarce or non-existent. Users often have bandwidth or connectivity issues. Existing platforms target only a small number of high-resource languages. Our own Daniel Whitenack (data scientist at SIL International)…
55 MinutesPractical AI
Today we’re joined by Kamran Khan, founder & CEO of BlueDot, and professor of medicine and public health at the University of Toronto. BlueDot has been the recipient of a lot of attention for being the first to publicly warn about the coronavirus that started in Wuhan. How did the company’s system of algorithms and…
51 MinutesThe TWIML AI Podcast
Today we’re joined by Emmanuel Ameisen, machine learning engineer at Stripe, and author of the recently published book “Building Machine Learning Powered Applications; Going from Idea to Product.” In our conversation, we discuss structuring end-to-end machine learning projects, debugging and explainability in the…
42 MinutesThe TWIML AI Podcast
