Understanding Collective Insect Communication with ML, w/ Orit Peleg - #590

Understanding Collective Insect Communication with ML, w/ Orit Peleg - #590

Today we’re joined by Orit Peleg, an assistant professor at the University of Colorado, Boulder. Orit’s work focuses on understanding the behavior of disordered living systems, by merging tools from physics, biology, engineering, and computer science. In our conversation, we discuss how Orit found herself exploring problems of swarming behaviors and their relationship to distributed computing system architecture and spiking neurons. We look at two specific areas of research, the first focused on the patterns observed in firefly species, how the data is collected, and the types of algorithms used for optimization. Finally, we look at how Orit’s research with fireflies translates to a completely different insect, the honeybee, and what the next steps are for investigating these and other insect families. The complete show notes for this episode can be found at twimlai.com/go/590

Jaksot(777)

Live from TWIMLcon! Operationalizing ML at Scale with Hussein Mehanna - #306

Live from TWIMLcon! Operationalizing ML at Scale with Hussein Mehanna - #306

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!

8 Loka 201933min

Live from TWIMLcon! Encoding Company Culture in Applied AI Systems - #305

Live from TWIMLcon! Encoding Company Culture in Applied AI Systems - #305

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

4 Loka 201932min

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

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

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.

1 Loka 201934min

The Future of Mixed-Autonomy Traffic with Alexandre Bayen - #303

The Future of Mixed-Autonomy Traffic with Alexandre Bayen - #303

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.

27 Syys 201944min

Deep Reinforcement Learning for Logistics at Instadeep with Karim Beguir - #302

Deep Reinforcement Learning for Logistics at Instadeep with Karim Beguir - #302

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.

25 Syys 201943min

Deep Learning with Structured Data w/ Mark Ryan - #301

Deep Learning with Structured Data w/ Mark Ryan - #301

Today we're joined by Mark Ryan, author of the upcoming book Deep Learning with Structured Data. Working on the support team at IBM Data and AI, he saw a lack of general structured data sets people could apply their models to. Using the streetcar network in Toronto, Mark gathered an open data set that started the research for his latest book. In this episode, Mark shares the benefits of applying deep learning to structured data, details of his experience with a range of data sets, and details his new book.

19 Syys 201939min

Time Series Clustering for Monitoring Fueling Infrastructure Performance with Kalai Ramea  - #300

Time Series Clustering for Monitoring Fueling Infrastructure Performance with Kalai Ramea - #300

Today we're joined by Kalai Ramea, Data Scientist at PARC, a Xerox Company. In this episode we discuss her journey buying a hydrogen car and the subsequent journey and paper that followed assessing fueling stations. In her next paper, Kalai looked at fuel consumption at hydrogen stations and used temporal clustering to identify signatures of usage over time. As the number of fueling stations is planned to increase dramatically in the future, building reliability on their performance is crucial.

18 Syys 201930min

Swarm AI for Event Outcome Prediction with Gregg Willcox - TWIML Talk #299

Swarm AI for Event Outcome Prediction with Gregg Willcox - TWIML Talk #299

Today we're joined by Gregg Willcox, Director of Research and Development at Unanimous AI. Inspired by the natural phenomenon called 'swarming', which uses the collective intelligence of a group to produce more accurate results than an individual alone, ‘Swarm AI’ was born. A game-like platform that channels the convictions of individuals to come to a consensus and using a behavioral neural network trained on people’s behavior called ‘Conviction’, to further amplify the results.

13 Syys 201941min

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