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

Latest Episodes:

Deep Learning for Earthquake Aftershock Patterns with Phoebe DeVries & Brendan Meade - #311 Oct 25, 2019

Show notes

Today we are joined by Phoebe DeVries, Postdoctoral Fellow in the Department of Earth and Planetary Sciences at Harvard and Brendan Meade, Professor of Earth and Planetary Sciences at Harvard. Phoebe and Brendan’s work is focused on discovering as much as possible about earthquakes before they happen, and by measuring how the earth’s surface moves, predicting future movement location, as seen in their paper: ‘Deep learning of aftershock patterns following large earthquakes'.

Live from TWIMLcon! Operationalizing Responsible AI - #310 Oct 22, 2019

Show notes

An often forgotten about topic garnered high praise at TWIMLcon this month: operationalizing responsible and ethical AI. This important topic was combined with an impressive panel of speakers, including: Rachel Thomas, Director, Center for Applied Data Ethics at the USF Data Institute, Guillaume Saint-Jacques, Head of Computational Science at LinkedIn, and Parinaz Sobahni, Director of Machine Learning at Georgian Partners, moderated by Khari Johnson, Senior AI Staff Writer at VentureBeat.

Live from TWIMLcon! Scaling ML in the Traditional Enterprise - #309 Oct 18, 2019

Show notes

Machine learning and AI is finding a place in the traditional enterprise - although the path to get there is different. In this episode, our panel analyzes the state and future of larger, more established brands. Hear from Amr Awadallah, Founder and Global CTO of Cloudera, Pallav Agrawal, Director of Data Science at Levi Strauss & Co., and Jürgen Weichenberger, Data Science Senior Principal & Global AI Lead at Accenture, moderated by Josh Bloom, Professor at UC Berkeley.

Live from TWIMLcon! Culture & Organization for Effective ML at Scale (Panel) - #308 Oct 15, 2019

Show notes

TWIMLcon brought together so many in the ML/AI community to discuss the unique challenges to building and scaling machine learning platforms. In this episode, hear about changing the way companies think about machine learning from a diverse set of panelists including Pardis Noorzad, Data Science Manager at Twitter, Eric Colson, Chief Algorithms Officer Emeritus at Stitch Fix, and Jennifer Prendki, Founder & CEO at Alectio, moderated by Maribel Lopez, Founder & Principal Analyst at Lopez Research.

Live from TWIMLcon! Use-Case Driven ML Platforms with Franziska Bell - #307 Oct 10, 2019

Show notes

Today we're Franziska Bell, Ph.D., the Director of Data Science Platforms at Uber, who joined Sam on stage at TWIMLcon last week. Fran provided a look into the cutting edge data science available company-wide at the push of a button. Since joining Uber, Fran has developed a portfolio of platforms, ranging from forecasting to conversational AI. Hear how use cases can strategically guide platform development, the evolving relationship between her team and Michelangelo (Uber’s ML Platform) and much more!

Live from TWIMLcon! Operationalizing ML at Scale with Hussein Mehanna - #306 Oct 08, 2019

Show notes

The live interviews from TWIMLcon continue with Hussein Mehanna, Head of ML and AI at Cruise. From his start at Facebook to his current work at Cruise, Hussein has seen first hand what it takes to scale and sustain machine learning programs. Hear him discuss the challenges (and joys) of working in the industry, his insight into analyzing scale when innovation is happening in parallel with development, his experiences at Facebook, Google, and Cruise, and his predictions for the future of ML platforms!

Live from TWIMLcon! Encoding Company Culture in Applied AI Systems - #305 Oct 04, 2019

Show notes

In this episode, Sam is joined by Deepak Agarwal, VP of Engineering at LinkedIn, who graced the stage at TWIMLcon: AI Platforms for a keynote interview. Deepak shares the impact that standardizing processes and tools have on a company’s culture and productivity levels, and best practices to increasing ML ROI. He also details the Pro-ML initiative for delivering machine learning systems at scale, specifically looking at aligning improvement of tooling and infrastructure with the pace of innovation and more

Live from TWIMLcon! Overcoming the Barriers to Deep Learning in Production with Andrew Ng - #304 Oct 01, 2019

Show notes

Earlier today, Andrew Ng joined us onstage at TWIMLcon - as the Founder and CEO of Landing AI and founding lead of Google Brain, Andrew is no stranger to knowing what it takes for AI and machine learning to be successful. Hear about the work that Landing AI is doing to help organizations adopt modern AI, his experience in overcoming challenges for large companies, how enterprises can get the most value for their ML investment as well as addressing the ‘essential complexity’ of software engineering.

The Future of Mixed-Autonomy Traffic with Alexandre Bayen - #303 Sep 27, 2019

Show notes

Today we are joined by Alexandre Bayen, Director of the Institute for Transportation Studies and Professor at UC Berkeley. Alex's current research is in mixed-autonomy traffic to understand how the growing automation in self-driving vehicles can be used to improve mobility and flow of traffic. At the AWS re:Invent conference last year, Alex presented on the future of mixed-autonomy traffic and the two major revolutions he predicts will take place in the next 10-15 years.

Deep Reinforcement Learning for Logistics at Instadeep with Karim Beguir - #302 Sep 25, 2019

Show notes

Today we are joined by Karim Beguir, Co-Founder and CEO of InstaDeep, a company focusing on building advanced decision-making systems for the enterprise. In this episode, we focus on logistical problems that require decision-making in complex environments using deep learning and reinforcement learning. Karim explains the InstaDeep process and mindset, where they get their data sets, the efficiency of RL, heuristic vs learnability approaches and how explainability fits into the model.

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