“The episode explores how AI is reshaping national security, including the US–China competition, the role of allies, and the challenges of governing AI as a dual use technology.”

“Dan Houser is a legendary creative mind behind Grand Theft Auto (GTA) and Red Dead Redemption series of video games.”

“The episode discusses Trumps barrage of executive orders, cabinet staffing, and denial of security clearances.”

“Fatir explains the challenges of leveraging pre-trained language models for time series forecasting.”

“Utility companies are using AI to ensure secure systems, interact with customers, navigate internal knowledge bases, and design electrical transmission systems.”

“The episode discusses recent videos of Palestinian arms and tactics, the Biden administration’s response to the war, the potential for further regional conflict, and where the new American focus on Israel leaves Ukraine.”

“We begin with the paper Interpretable Subspaces in Image Representations... We also explore GOAT: A Global Transformer on Large-scale Graphs, a scalable global graph transformer.”

“The episode discusses the B-Team's journey and experiences in Jiu Jitsu.”

“The article doesn't contain direct quotes, but it references several research papers and articles.”

“The episode discusses deep learning and artificial general intelligence.”

“The article doesn't contain a direct quote.”

“The episode discusses IQ tests, human intelligence, and group differences.”

“Lukas Biewald is an entrepreneur living in San Francisco. He was the founder and CEO of Figure Eight an Internet company that collects training data for machine learning. In 2018, he founded Weights and Biases, a company that creates developer tools for machine learning.”

“Shayan helps us define “data-centric”, while discussing the main challenges that organizations face when dealing with labeling, how these problems are currently being solved, and how techniques like active learning and weak supervision could be used to more effectively label.”

“The episode discusses Putin's plan for the war and parallels to World War II.”

“Beyond interpretability: developing a language to shape our relationships with AI”

“NLP as we know it has changed, and we’re back into the incremental phase of the science, and NLP is “eating” the rest of machine learning.”

“The episode discusses relationship advice and societal commentary.”

“The article doesn't contain a direct quote.”

“The episode discusses topics like neuromorphic computing, computation vs. communication, and the future of computing.”

“The episode explores the theoretical underpinnings of cognitive science and AI.”

“The episode discusses Newton's contributions to science and his philosophical views.”

“The episode discusses various aspects of sleep and related topics.”

“The article doesn't contain a direct quote, but summarizes the topics discussed.”

“Watch the film through the Santa Barbara International Film Festival at www.sbiff.org”

“The episode discusses a first principles approach to martial arts.”

“Adriana then describes how these techniques fit into her broader goal of trying to understand the rhetoric of visual advertisements.”

“We’re back gettin’ hot ‘n greasy in the Beltway Garage, gauging the pressure on SCOTUS appointments, kicking the remarkably stable tires on the presidential race, and selling you a slew of useless upgrades on this year’s contested Senate races.”

“In this episode of Machine Learning Street Talk, Tim Scarfe, Yannic Kilcher and Connor Shorten chat about Large-scale Transfer Learning in Natural Language Processing.”

“Thanks to Luke and Dotscience for their sponsorship of this Democast and their continued support of TWIML.”

“Using the full spectrum of data science to drive business decisions”

“In our conversation, we explore Alex’s journey to implement machine learning at Experteer, the Experteer NLP pipeline and how it’s evolved, Alex’s work with deep learning based ML models, including models like VDCNN and Facebook’s FastText offering and a few recent papers that look at transfer learning for NLP.”

“The episode discusses two of Adji Bousso Dieng's papers: "Noisin: Unbiased Regularization for Recurrent Neural Networks" and "TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency."”

“In our discussion, we cover what exactly a “goodness of fit” test is, and how it can be used to determine how well a statistical model applies to a given real-world scenario.”

“Solmaz gave a great talk at the GPPC focused on her team’s experiences applying machine learning to fight fraud and improve merchant satisfaction.”