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

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Inspiring New Machine Learning Platforms w/ Bioelectric Computation with Michael Levin - TWiML Talk #282

Inspiring New Machine Learning Platforms w/ Bioelectric Computation with Michael Levin - TWiML Talk #282

Today we’re joined by Michael Levin, Director of the Allen Discovery Institute at Tufts University. In our conversation, we talk about synthetic living machines, novel AI architectures and brain-body plasticity. Michael explains how our DNA doesn’t control everything and how the behavior of cells in living organisms can be modified and adapted. Using research on biological systems dynamic remodeling, Michael discusses the future of developmental biology and regenerative medicine.

15 Juli 201925min

Simulation and Synthetic Data for Computer Vision with Batu Arisoy - TWiML Talk #281

Simulation and Synthetic Data for Computer Vision with Batu Arisoy - TWiML Talk #281

Today we’re joined by Batu Arisoy, Research Manager with the Vision Technologies & Solutions team at Siemens Corporate Technology. Batu’s research focus is solving limited-data computer vision problems, providing R&D for business units throughout the company. In our conversation, Batu details his group's ongoing projects, like an activity recognition project with the ONR, and their many CVPR submissions, which include an emulation of a teacher teaching students information without the use of memorizatio

9 Juli 201941min

Spiking Neural Nets and ML as a Systems Challenge with Jeff Gehlhaar - TWIML Talk #280

Spiking Neural Nets and ML as a Systems Challenge with Jeff Gehlhaar - TWIML Talk #280

Today we’re joined by Jeff Gehlhaar, VP of Technology and Head of AI Software Platforms at Qualcomm. Qualcomm has a hand in tons of machine learning research and hardware, and in our conversation with Jeff we discuss: • How the various training frameworks fit into the developer experience when working with their chipsets. • Examples of federated learning in the wild. • The role inference will play in data center devices and much more.

8 Juli 201952min

Transforming Oil & Gas with AI with Adi Bhashyam and Daniel Jeavons - TWIML Talk #279

Transforming Oil & Gas with AI with Adi Bhashyam and Daniel Jeavons - TWIML Talk #279

Today we’re joined by return guest Daniel Jeavons, GM of Data Science at Shell, and Adi Bhashyam, GM of Data Science at C3, who we had the pleasure of speaking to at this years C3 Transform Conference. In our conversation, we discuss: • The progress that Dan and his team has made since our last conversation, including an overview of their data platform. • Adi gives us an overview of the evolution of C3 and their platform, along with a breakdown of a few Shell-specific use cases.

1 Juli 201946min

Fast Radio Burst Pulse Detection with Gerry Zhang - TWIML Talk #278

Fast Radio Burst Pulse Detection with Gerry Zhang - TWIML Talk #278

Today we’re joined by Yunfan Gerry Zhang, a PhD student at UC Berkely, and an affiliate of Berkeley’s SETI research center. In our conversation, we discuss:  • Gerry's research on applying machine learning techniques to astrophysics and astronomy. • His paper “Fast Radio Burst 121102 Pulse Detection and Periodicity: A Machine Learning Approach”. • We explore the types of data sources used for this project, challenges Gerry encountered along the way, the role of GANs and much more.

27 Juni 201938min

Tracking CO2 Emissions with Machine Learning with Laurence Watson - TWIML Talk #277

Tracking CO2 Emissions with Machine Learning with Laurence Watson - TWIML Talk #277

Today we’re joined by Laurence Watson, Co-Founder and CTO of Plentiful Energy and a former data scientist at Carbon Tracker. In our conversation, we discuss: • Carbon Tracker's goals, and their report “Nowhere to hide: Using satellite imagery to estimate the utilisation of fossil fuel power plants”. • How they are using computer vision to process satellite images of coal plants, including how the images are labeled. •Various challenges with the scope and scale of this project.

24 Juni 201941min

Topic Modeling for Customer Insights at USAA with William Fehlman - TWIML Talk #276

Topic Modeling for Customer Insights at USAA with William Fehlman - TWIML Talk #276

Today we’re joined by William Fehlman, director of data science at USAA, to discuss: • His work on topic modeling, which USAA uses in various scenarios, including member chat channels. • How their datasets are generated. • Explored methodologies of topic modeling, including latent semantic indexing, latent Dirichlet allocation, and non-negative matrix factorization. • We also explore how terms are represented via a document-term matrix, and how they are scored based on coherence.

20 Juni 201944min

Phronesis of AI in Radiology with Judy Gichoya - TWIML Talk #275

Phronesis of AI in Radiology with Judy Gichoya - TWIML Talk #275

Today we’re joined by Judy Gichoya an interventional radiology fellow at the Dotter Institute at Oregon Health and Science University. In our conversation, we discuss: • Judy's research on the paper “Phronesis of AI in Radiology: Superhuman meets Natural Stupidy,” reviewing the claims of “superhuman” AI performance in radiology. • Potential roles in which AI can have success in radiology, along with some of the different types of biases that can manifest themselves across multiple use c

18 Juni 201943min

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