Differential Privacy at Bluecore with Zahi Karam - TWiML Talk #133

Differential Privacy at Bluecore with Zahi Karam - TWiML Talk #133

In this episode of our Differential Privacy series, I'm joined by Zahi Karam, Director of Data Science at Bluecore, whose retail marketing platform specializes in personalized email marketing. I sat down with Zahi at the Georgian Partners portfolio conference last year, where he gave me my initial exposure to the field of differential privacy, ultimately leading to this series. Zahi shared his insights into how differential privacy can be deployed in the real world and some of the technical and cultural challenges to doing so. We discuss the Bluecore use case in depth, including why and for whom they build differentially private machine learning models. The notes for this show can be found at twimlai.com/talk/133

Jaksot(774)

AI at the Edge at Qualcomm with Gary Brotman - TWiML Talk #223

AI at the Edge at Qualcomm with Gary Brotman - TWiML Talk #223

Today we’re joined by Gary Brotman, Senior Director of Product Management at Qualcomm Technologies, Inc. Gary, who got his start in AI through music, now leads strategy and product planning for the company’s AI and ML technologies, including those that make up the Qualcomm Snapdragon mobile platforms. In our conversation, we discuss AI on mobile devices and at the edge, including popular use cases, and explore some of the various acceleration technologies offered by Qualcomm and others that enable th

24 Tammi 201951min

AI Innovation at CES - TWiML Talk #222

AI Innovation at CES - TWiML Talk #222

A few weeks ago, I made the trek to Las Vegas for the world’s biggest electronics conference, CES. In this special visual only episode, we’re going to check out some of the interesting examples of machine learning and AI that I found at the event. Check out the video at https://twimlai.com/ces2019, and be sure to hit the like and subscribe buttons and let us know how you like the show via a comment! For the show notes, visit https://twimlai.com/talk/222.

21 Tammi 20192min

Self-Tuning Services via Real-Time Machine Learning with Vladimir Bychkovsky - TWiML Talk #221

Self-Tuning Services via Real-Time Machine Learning with Vladimir Bychkovsky - TWiML Talk #221

Today we’re joined by Vladimir Bychkovsky, Engineering Manager at Facebook, to discuss Spiral, a system they’ve developed for self-tuning high-performance infrastructure services at scale, using real-time machine learning. In our conversation, we explore how the system works, how it was developed, and how infrastructure teams at Facebook can use it to replace hand-tuned parameters set using heuristics with services that automatically optimize themselves in minutes rather than in weeks.

17 Tammi 201946min

Building a Recommender System from Scratch at 20th Century Fox with JJ Espinoza - TWiML Talk #220

Building a Recommender System from Scratch at 20th Century Fox with JJ Espinoza - TWiML Talk #220

Today we’re joined by JJ Espinoza, former Director of Data Science at 20th Century Fox. In this talk we dig into JJ and his team’s experience building and deploying a content recommendation system from the ground up. In our conversation, we explore the design of a couple of key components of their system, the first of which processes movie scripts to make recommendations about which movies the studio should make, and the second processes trailers to determine which should be recommended to users.

14 Tammi 201934min

Legal and Policy Implications of Model Interpretability with Solon Barocas - TWiML Talk #219

Legal and Policy Implications of Model Interpretability with Solon Barocas - TWiML Talk #219

Today we’re joined by Solon Barocas, Assistant Professor of Information Science at Cornell University. Solon and I caught up to discuss his work on model interpretability and the legal and policy implications of the use of machine learning models. In our conversation, we explore the gap between law, policy, and ML, and how to build the bridge between them, including formalizing ethical frameworks for machine learning. We also look at his paper ”The Intuitive Appeal of Explainable Machines.”

10 Tammi 201946min

Trends in Computer Vision with Siddha Ganju - TWiML Talk #218

Trends in Computer Vision with Siddha Ganju - TWiML Talk #218

In the final episode of our AI Rewind series, we’re excited to have Siddha Ganju back on the show. Siddha, who is now an autonomous vehicles solutions architect at Nvidia shares her thoughts on trends in Computer Vision in 2018 and beyond. We cover her favorite CV papers of the year in areas such as neural architecture search, learning from simulation, application of CV to augmented reality, and more, as well as a bevy of tools and open source projects.

7 Tammi 201932min

Trends in Reinforcement Learning with Simon Osindero - TWiML Talk #217

Trends in Reinforcement Learning with Simon Osindero - TWiML Talk #217

In this episode of our AI Rewind series, we introduce a new friend of the show, Simon Osindero, Staff Research Scientist at DeepMind. We discuss trends in Deep Reinforcement Learning in 2018 and beyond. We’ve packed a bunch into this show, as Simon walks us through many of the important papers and developments seen this year in areas like Imitation Learning, Unsupervised RL, Meta-learning, and more. The complete show notes for this episode can be found at https://twimlai.com/talk/217.

3 Tammi 201952min

Trends in Natural Language Processing with Sebastian Ruder - TWiML Talk #216

Trends in Natural Language Processing with Sebastian Ruder - TWiML Talk #216

In this episode of our AI Rewind series, we’ve brought back recent guest Sebastian Ruder, PhD Student at the National University of Ireland and Research Scientist at Aylien, to discuss trends in Natural Language Processing in 2018 and beyond. In our conversation we cover a bunch of interesting papers spanning topics such as pre-trained language models, common sense inference datasets and large document reasoning and more, and talk through Sebastian’s predictions for the new year.

31 Joulu 201852min

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