Scaling Deep Learning: Systems Challenges & More with Shubho Sengupta — TWiML Talk #14

The show you’re about to hear is part of a series of shows recorded in San Francisco at the Artificial Intelligence Conference. In this episode, I talk with Ion Stoica, professor of computer science & director of the RISE Lab at UC Berkeley. Ion joined us after he gave his talk “Building reinforcement learning applications with Ray.” We dive into Ray, a new distributed computing platform for RL, as well as RL generally, along with some of the other interesting projects RISE Lab is working on, like Clipper & Tegra. This was a pretty interesting talk. Enjoy! The notes for this show can be found at twimlai.com/talk/55

5 Loka 201728min

The show you’re about to hear is part of a series of shows recorded in San Francisco at the Artificial Intelligence Conference. My guest for this show is Gunnar Carlsson, professor emeritus of mathematics at Stanford University and president and co-founder of machine learning startup Ayasdi. Gunnar joined me after his session at the conference on “Topological data analysis as a framework for machine intelligence.” In our talk, we take a super deep dive on the mathematical underpinnings of TDA and its practical application through software. Nerd Alert! The notes for this show can be found at twimlai.com/talk/53

3 Loka 201733min

As you all know, a few weeks ago, I spent some time in SF at the Artificial Intelligence Conference. While I was there, I had just enough time to sneak away and catch up with Scott Clark, Co-Founder and CEO of Sigopt, a company whose software is focused on automatically tuning your model’s parameters through Bayesian optimization. We dive pretty deeply into that process through the course of this discussion, while hitting on topics like Exploration vs Exploitation, Bayesian Regression, Heterogeneous Configuration Models and Covariance Kernels. I had a great time and learned a ton, but be forewarned, this is most definitely a Nerd Alert show! Notes for this show can be found at twimlai.com/talk/50

2 Loka 201747min

Like last week’s interview with Bruno Goncalves, this week’s interview was also recorded at the last O’Reilly AI Conference back in New York in June. Also like last week’s show, this week’s is also focused on Natural Language Processing and I think you’ll enjoy it. I’m joined by Jonathan Mugan, co-founder and CEO of Deep Grammar, a company that is building a grammar checker using deep learning and what they call deep symbolic processing. This interview is a great complement to my conversation with Bruno, and we cover a variety of topics from both the sub-symbolic and symbolic schools of NLP, such as attention mechanisms like sequence to sequence, and ontological approaches like WordNet, synsets, FrameNet, and SUMO. You can find the notes for this show at twimlai.com/talk/49

25 Syys 201743min

This week i'm bringing you an interview from Bruno Goncalves, a Moore-Sloan Data Science Fellow at NYU. As you’ll hear in the interview, Bruno is a longtime listener of the podcast. We were able to connect at the NY AI conference back in June after I noted on a previous show that I was interested in learning more about word2vec. Bruno graciously agreed to come on the show and walk us through an overview of word embeddings, word2vec and related ideas. He provides a great overview of not only word2vec, related NLP concepts such as Skip Gram, Continuous Bag of Words, Node2Vec and TFIDF. Notes for this show can be found at twimlai.com/talk/48.

19 Syys 201732min

My guest this week is Risto Miikkulainen, professor of computer science at UT-Austin and vice president of Research at Sentient Technologies. Risto came locked and loaded to discuss a topic that we've received a ton of requests for -- evolutionary algorithms. During our talk we discuss some of the things Sentient is working on in the financial services and retail fields, and we dig into the technology behind it, evolutionary algorithms, which is also the focus of Risto’s research at UT. I really enjoyed this interview and learned a ton, and I’m sure you will too! Notes for this show can be found at twimlai.com/talk/47.

11 Syys 201758min

My guest this week is Jennifer Prendki. That name might sound familiar, as she was one of the great speakers from my Future of Data Summit back in May. At the time, Jennifer was senior data science manager and principal data scientist at Walmart Labs, but she's since moved on to become head of data science at Atlassian. Back at the summit, Jennifer gave an awesome talk on what she calls Data Mixology, the slides for which you can find on the show notes page. My conversation with Jennifer begins with a recap of that talk. After that, we shift our focus to some of the practices she helped develop and implement at Walmart around the measurement and management of machine learning models in production, and more generally, building agile processes and teams for machine learning. The notes for this show can be found at twimlai.com/talk/46

5 Syys 201748min

This week we have a very special interview to share with you! Those of you who’ve been receiving my newsletter for a while might remember that while in Switzerland last month, I had the pleasure of interviewing Jurgen Schmidhuber, in his lab IDSIA, which is the Dalle Molle Institute for Artificial Intelligence Research in Lugano, Switzerland, where he serves as Scientific Director. In addition to his role at IDSIA, Jurgen is also Co-Founder and Chief Scientist of NNaisense, a company that is using AI to build large-scale neural network solutions for “superhuman perception and intelligent automation.” Jurgen is an interesting, accomplished and in some circles controversial figure in the AI community and we covered a lot of very interesting ground in our discussion, so much so that I couldn't truly unpack it all until I had a chance to sit with it after the fact. We talked a bunch about his work on neural networks, especially LSTM’s, or Long Short-Term Memory networks, which are a key innovation behind many of the advances we’ve seen in deep learning and its application over the past few years. Along the way, Jurgen walks us through a deep learning history lesson that spans 50+ years. It was like walking back in time with the 3 eyed raven. I know you’re really going to enjoy this one, and by the way, this is definitely a nerd alert show! For the show notes, visit twimlai.com/talk/44

28 Elo 20171h 3min