The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Latest Episodes:

Productizing ML at Scale at Twitter with Yi Zhuang - TWIML Talk #271 Jun 03, 2019

Show notes

Today we continue our AI Platforms series joined by Yi Zhuang, Senior Staff Engineer at Twitter. In our conversation, we cover: • The machine learning landscape at Twitter, including with the history of the Cortex team • Deepbird v2, which is used for model training and evaluation solutions, and it's integration with Tensorflow 2.0. • The newly assembled “Meta” team, that is tasked with exploring the bias, fairness, and accountability of their machine learning models, and much more!

Snorkel: A System for Fast Training Data Creation with Alex Ratner - TWiML Talk #270 May 30, 2019

Show notes

Today we’re joined by Alex Ratner, Ph.D. student at Stanford, to discuss: • Snorkel, the open source framework that is the successor to Stanford's Deep Dive project. • How Snorkel is used as a framework for creating training data with weak supervised learning techniques. • Multiple use cases for Snorkel, including how it is used by companies like Google. The complete show notes can be found at twimlai.com/talk/270. Follow along with AI Platforms Vol. 2 at twimlai.com/aiplatforms2.

Advancing Autonomous Vehicle Development Using Distributed Deep Learning with Adrien Gaidon - TWiML Talk #269 May 28, 2019

Show notes

In this, the kickoff episode of AI Platforms Vol. 2, we're joined by Adrien Gaidon, Machine Learning Lead at Toyota Research Institute. Adrien and I caught up to discuss his team’s work on deploying distributed deep learning in the cloud, at scale. In our conversation, we discuss: • The beginning and gradual scaling up of TRI's platform. • Their distributed deep learning methods, including their use of stock Pytorch, and much more!

Are We Being Honest About How Difficult AI Really Is? w/ David Ferrucci - TWiML Talk #268 May 23, 2019

Show notes

Today we’re joined by David Ferrucci, Founder, CEO, and Chief Scientist at Elemental Cognition, a company focused on building natural learning systems that understand the world the way people do, to discuss: • The role of “understanding” in the context of AI systems, and the types of commitments and investments needed to achieve even modest levels of understanding. • His thoughts on the power of deep learning, what the path to AGI looks like, and the need for hybrid systems to get there.

Gauge Equivariant CNNs, Generative Models, and the Future of AI with Max Welling - TWiML Talk #267 May 20, 2019

Show notes

Today we’re joined by Max Welling, research chair in machine learning at the University of Amsterdam, and VP of Technologies at Qualcomm, to discuss: • Max’s research at Qualcomm AI Research and the University of Amsterdam, including his work on Bayesian deep learning, Graph CNNs and Gauge Equivariant CNNs, power efficiency for AI via compression, quantization, and compilation. • Max’s thoughts on the future of the AI industry, in particular, the relative importance of models, data and com

Can We Trust Scientific Discoveries Made Using Machine Learning? with Genevera Allen - TWiML Talk #266 May 16, 2019

Show notes

Today we’re joined by Genevera Allen, associate professor of statistics in the EECS Department at Rice University. Genevera caused quite the stir at the American Association for the Advancement of Science meeting earlier this year with her presentation “Can We Trust Data-Driven Discoveries?" In our conversation, we discuss the goal of Genevera's talk, the issues surrounding reproducibility in Machine Learning, and much more!

Creative Adversarial Networks for Art Generation with Ahmed Elgammal - TWiML Talk #265 May 13, 2019

Show notes

Today we’re joined by Ahmed Elgammal, a professor in the department of computer science at Rutgers, and director of The Art and Artificial Intelligence Lab. We discuss his work on AICAN, a creative adversarial network that produces original portraits, trained with over 500 years of European canonical art. The complete show notes for this episode can be found at twimlai.com/talk/265.

Diagnostic Visualization for Machine Learning with YellowBrick w/ Rebecca Bilbro - TWiML Talk #264 May 10, 2019

Show notes

Today we close out our PyDataSci series joined by Rebecca Bilbro, head of data science at ICX media and co-creator of the popular open-source visualization library YellowBrick. In our conversation, Rebecca details: • Her relationship with toolmaking, which led to the eventual creation of YellowBrick. • Popular tools within YellowBrick, including a summary of their unit testing approach. • Interesting use cases that she’s seen over time.

Librosa: Audio and Music Processing in Python with Brian McFee - TWiML Talk #263 May 09, 2019

Show notes

Today we continue our PyDataSci series joined by Brian McFee, assistant professor of music technology and data science at NYU, and creator of LibROSA, a python package for music and audio analysis. Brian walks us through his experience building LibROSA, including: • Detailing the core functions provided in the library • His experience working in Jupyter Notebook • We explore a typical LibROSA workflow & more! The complete show notes for this episode can be found at twimlai.com/talk/26

Practical Natural Language Processing with spaCy and Prodigy w/ Ines Montani - TWiML Talk #262 May 07, 2019

Show notes

In this episode of PyDataSci, we’re joined by Ines Montani, Cofounder of Explosion, Co-developer of SpaCy and lead developer of Prodigy. Ines and I caught up to discuss her various projects, including the aforementioned SpaCy, an open-source NLP library built with a focus on industry and production use cases. The complete show notes for this episode can be found at twimlai.com/talk/262. Check out the rest of the PyDataSci series at twimlai.com/pydatasci.

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