Shows

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AI Innovation at CES – Video Exclusive!!

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Self-Tuning Services via Real-Time Machine Learning with Vladimir Bychkovsky

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Building a Recommender System from Scratch at 20th Century Fox with JJ Espinoza

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Legal and Policy Implications of Model Interpretability with Solon Barocas

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Trends in Computer Vision with Siddha Ganju

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Trends in Reinforcement Learning with Simon Osindero

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Trends in Natural Language Processing with Sebastian Ruder

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Trends in Machine Learning with Anima Anandkumar

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Trends in Deep Learning with Jeremy Howard

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Training Large-Scale Deep Nets with RL with Nando de Freitas

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Making Algorithms Trustworthy with David Spiegelhalter

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Designing Computer Systems for Software with Kunle Olukotun

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Operationalizing Ethical AI with Kathryn Hume

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Approaches to Fairness in Machine Learning with Richard Zemel

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Trust and AI with Parinaz Sobhani

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Unbiased Learning from Biased User Feedback with Thorsten Joachims

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Language Parsing and Character Mining with Jinho Choi

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re:Invent Roundup Roundtable 2018 with Dave McCrory and Val Bercovici

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Knowledge Graphs and Expert Augmentation with Marisa Boston

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ML/DL for Non-Stationary Time Series Analysis in Financial Markets and Beyond with Stuart Reid

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Industrializing Machine Learning at Shell with Daniel Jeavons

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Resurrecting a Recommendations Platform at Comcast with Leemay Nassery

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Productive Machine Learning at LinkedIn with Bee-Chung Chen

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Scaling Deep Learning on Kubernetes at OpenAI with Christopher Berner

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Bighead: Airbnb’s Machine Learning Platform with Atul Kale

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Facebook’s FBLearner Platform with Aditya Kalro

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Geometric Statistics in Machine Learning w/ geomstats with Nina Miolane

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Milestones in Neural Natural Language Processing with Sebastian Ruder

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Natural Language Processing at StockTwits with Garrett Hoffman

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Advanced Reinforcement Learning & Data Science for Social Impact with Vukosi Marivate

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AI Ethics, Strategic Decisioning and Game Theory with Osonde Osoba

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Acoustic Word Embeddings for Low Resource Speech Processing with Herman Kamper

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Learning Representations for Visual Search with Naila Murray

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Evaluating Model Explainability Methods with Sara Hooker

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Graph Analytic Systems with Zachary Hanif

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Diversification in Recommender Systems with Ahsan Ashraf

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The Fastai v1 Deep Learning Framework with Jeremy Howard

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Federated ML for Edge Applications with Justin Norman

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Exploring Dark Energy & Star Formation w/ ML with Viviana Acquaviva

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Document Vectors in the Wild with James Dreiss

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Applied Machine Learning for Publishers with Naveed Ahmad

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Anticipating Superintelligence with Nick Bostrom

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Can We Train an AI to Understand Body Language? with Hanbyul Joo

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Biological Particle Identification and Tracking with Jay Newby

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AI for Content Creation with Debajyoti Ray

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Deep Reinforcement Learning Primer and Research Frontiers with Kamyar Azizzadenesheli

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OpenAI Five with Christy Dennison

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How ML Keeps Shelves Stocked at Home Depot with Pat Woowong

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Contextual Modeling for Language and Vision with Nasrin Mostafazadeh

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ML for Understanding Satellite Imagery at Scale with Kyle Story

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Generating Ground-Level Images From Overhead Imagery Using GANs with Yi Zhu

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Vision Systems for Planetary Landers and Drones with Larry Matthies

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Learning Semantically Meaningful and Actionable Representations with Ashutosh Saxena

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AI Innovation for Clinical Decision Support with Joe Connor

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Dynamic Visual Localization and Segmentation with Laura Leal-Taixé

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Conversational AI for the Intelligent Workplace with Gillian McCann

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Computer Vision and Intelligent Agents for Wildlife Conservation with Jason Holmberg

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Pragmatic Deep Learning for Medical Imagery with Prashant Warier

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Taskonomy: Disentangling Transfer Learning for Perception (CVPR 2018 Best Paper Winner) with Amir Zamir

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Predicting Metabolic Pathway Dynamics w/ Machine Learning with Zak Costello

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Machine Learning to Discover Physics and Engineering Principles with Nathan Kutz

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Automating Complex Internal Processes w/ AI with Alexander Chukovski

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Designing Better Sequence Models with RNNs with Adji Bousso Dieng

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Love Love: AI and ML in Tennis with Stephanie Kovalchik

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Growth Hacking Sports w/ Machine Learning with Noah Gift

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Fine-Grained Player Prediction in Sports with Jennifer Hobbs

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Targeted Ticket Sales Using ML for the Portland Trail Blazers w/ Mike Schumacher & Chenhui Hu

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AI for Athlete Optimization with Sinead Flahive

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Omni-Channel Customer Experiences with Vince Jeffs

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Workforce Intelligence for Automation & Productivity with Michael Kempe

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Data Platforms for Decision Automation at Scotiabank with Jim Saleh

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Towards the Self-Driving Enterprise with Kirk Borne

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How a Global Energy Company Adopts ML & AI with Nicholas Osborn

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Problem Formulation for Machine Learning with Romer Rosales

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AI for Materials Discovery with Greg Mulholland

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Data Innovation & AI at Capital One with Adam Wenchel

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Deep Gradient Compression for Distributed Training with Song Han

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Masked Autoregressive Flow for Density Estimation with George Papamakarios

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Training Data for Computer Vision at Figure Eight with Qazaleh Mirsharif

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Agile Data Science with Sarah Aerni

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Tensor Operations for Machine Learning with Anima Anandkumar

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Deep Learning for Live-Cell Imaging with David Van Valen

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Checking in with the Master with Garry Kasparov

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Exploring AI-Generated Music with Taryn Southern

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Practical Deep Learning with Rachel Thomas

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Kinds of Intelligence: Types, Tests & Meeting the Needs of Society w/ Jose Hernandez-Orallo

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Taming arXiv w/ Natural Language Processing with John Bohannon

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Epsilon Software for Private Machine Learning with Chang Liu

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Scalable Differential Privacy for Deep Learning with Nicolas Papernot

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Differential Privacy at Bluecore with Zahi Karam

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Differential Privacy Theory & Practice with Aaron Roth

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Optimal Transport and Machine Learning with Marco Cuturi

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Collecting and Annotating Data for AI with Kiran Vajapey

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Autonomous Aerial Guidance, Navigation and Control Systems with Christopher Lum

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Infrastructure for Autonomous Vehicles with Missy Cummings

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Hyper-Personalizing the Customer Experience w/ AI with Rob Walker

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Information Extraction from Natural Document Formats with David Rosenberg

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Human-in-the-Loop AI for Emergency Response and More with Robert Munro

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Systems and Software for Machine Learning at Scale with Jeff Dean

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Semantic Segmentation of 3D Point Clouds with Lyne Tchapmi

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Predicting Cardiovascular Risk Factors from Eye Images with Ryan Poplin

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Reproducibility and the Philosophy of Data with Clare Gollnick

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Surveying the Connected Car Landscape with GK Senthil

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Adversarial Attacks Against Reinforcement Learning Agents with Ian Goodfellow & Sandy Huang

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Towards Abstract Robotic Understanding with Raja Chatila

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Discovering Exoplanets with Deep Learning with Chris Shallue

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Learning Active Learning from Data with Ksenia Konyushkova

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Scaling Machine Learning at Uber with Mike Del Balso

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Inverse Programming for Deeper AI with Zenna Tavares

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Statistical Relational Artificial Intelligence with Sriraam Natarajan

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Classical Machine Learning for Infant Medical Diagnosis with Charles Onu

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Learning “Common Sense” and Physical Concepts with Roland Memisevic

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Trust in Human-Robot/AI Interactions with Ayanna Howard

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Data Science for Poaching Prevention and Disease Treatment with Nyalleng Moorosi

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Security and Safety in AI: Adversarial Examples, Bias and Trust with Moustapha Cissé

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Peering into the Home w/ Aerial’s Wifi Motion Analytics with Michel Allegue & Negar Ghourchian

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Physiology-Based Models for Fitness and Training w/ Firstbeat with Ilkka Korhonen

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Machine Learning for Signal Processing Applications with Stuart Feffer & Brady Tsai

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Personalizing the Ferrari Challenge Experience with Andy Keller and Emile Chin-Dickey

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Deep Learning for 3D Sensors and Cameras in Lighthouse with Alex Teichman

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Computer Vision for Cozmo, the Cutest Toy Robot Everrrrr! with Andrew Stein

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Expectation Maximization, Gaussian Mixtures & Belief Propagation, OH MY! with Inmar Givoni

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A Linear-Time Kernel Goodness-of-Fit Test with Wittawat Jitkrittum, Zoltan Szabo, Kenji Fukumizu, Arthur Gretton – NIPS Best Paper ’17

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Safe and Nested Subgame Solving for Imperfect-Information Games with Tuomas Sandholm – NIPS Best Paper ’17

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Separating Vocals in Recorded Music at Spotify with Eric Humphrey

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Accelerating Deep Learning with Mixed Precision Arithmetic with Greg Diamos

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Composing Graphical Models With Neural Networks with David Duvenaud

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Embedded Deep Learning at Deep Vision with Siddha Ganju

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Neuroevolution: Evolving Novel Neural Network Architectures with Kenneth Stanley

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A Quantum Computing Primer and Implications for AI with Davide Venturelli

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Learning State Representations with Yael Niv

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Philosophy of Intelligence with Matthew Crosby

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Geometric Deep Learning with Joan Bruna and Michael Bronstein

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AI at the NASA Frontier Development Lab with Sara Jennings, Timothy Seabrook and Andres Rodriguez

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Using Deep Learning and Google Street View to Estimate Demographics with Timnit Gebru

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Integrative Learning for Robotic Systems with Aaron Ames

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Visual Recognition in the Cloud for Law Enforcement with Chris Adzima

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Embodied Visual Learning with Kristen Grauman

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Real-Time Machine Learning in the Database with Nikita Shamgunov

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re:Invent Roundup Roundtable

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Driving Customer Loyalty with Predictive and Conversational AI with Sherif Mityas

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Innovations Factories for AI in Financial Services with Thierry Derungs

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Block-Sparse Kernels for Deep Neural Networks with Durk Kingma

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AI for Customer Service and Marketing at AeroMexico with Brian Gross

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Scaling AI for the Enterprise with Mazin Gilbert

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Scalable Distributed Deep Learning with Hillery Hunter

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Robotics at OpenAI with Jonas Schneider

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AI Robustness & Safety with Dario Amodei

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Towards Artificial General Intelligence with Greg Brockman

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Explaining Black Box Predictions with Sam Ritchie

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Experimental Creative Writing with the Vectorized Word with Allison Parrish

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The Biological Path Towards Strong AI with Matthew Taylor

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Pytorch: Fast Differentiable Dynamic Graphs in Python with Soumith Chintala

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Accessible Machine Learning for the Enterprise Developer with Ryan Sevey and Jason Montgomery

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Bridging the Gap Between Academic and Industry Careers with Ross Fadely

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The Limitations of Human-in-the-Loop AI with Dennis Mortensen

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Nexus Lab Cohort 2 – Second Mind

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Nexus Lab Cohort 2 – Bite.ai

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Nexus Lab Cohort 2 – Bowtie

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Nexus Lab Cohort 2 – Mt. Cleverest

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Learning to Learn, and other Opportunities in Machine Learning with Graham Taylor

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Building Conversational Applications for Financial Services with Kenneth Conroy

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Fighting Fraud with Machine Learning at Shopify with Solmaz Shahalizadeh

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Modeling Human Drivers for Autonomous Driving with Katie Driggs-Campbell

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Perception Models for Self-Driving Cars with Jianxiong Xiao

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Training Data for Autonomous Vehicles with Daryn Nakhuda

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Human Factors in Machine Intelligence with James Guszcza

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Intel Nervana Devcloud with Naveen Rao & Scott Apeland

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AI-Powered Conversational Interfaces with Paul Tepper

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Topological Data Analysis with Gunnar Carlsson

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ML Use Cases at Think Big Analytics with Mo Patel and Laura Frølich

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Ray: A Distributed Computing Platform for Reinforcement Learning with Ion Stoica

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Bayesian Optimization for Hyperparameter Tuning with Scott Clark

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Symbolic and Sub-Symbolic Natural Language Processing with Jonathan Mugan

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Word2Vec & Friends with Bruno Goncalves

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Evolutionary Algorithms in Machine Learning with Risto Miikkulainen

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Agile Machine Learning at Walmart with Jennifer Prendki

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LSTM’s, plus a Deep Learning History Lesson with Jürgen Schmidhuber

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Machine Teaching for Better Machine Learning with Mark Hammond

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Marrying Physics-Based and Data Driven ML Models with Josh Bloom

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Cognitive Biases in Data Science with Drew Conway

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Data Pipelines at Zymergen with Airflow with Erin Shellman

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Web Scale Engineering for Machine Learning with Sharath Rao

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Deep Learning for Warehouse Operations with Calvin Seward

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Deep Robotic Learning with Sergey Levine

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Smart Buildings & IoT with Yodit Stanton

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Naveen Rao & Hanlin Tang – Intel Nervana Update + Productizing AI Research

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Doug Eck – Expressive AI-Generated Music with Google’s Performance RNN

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Ben Vigoda – The Power of Probabilistic Programming

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Rana el Kaliouby – Enhancing Customer Experiences with Emotional AI

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Reza Zadeh – Video Object Detection at Scale

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Natural Language Understanding for Amazon Alexa with Zornitsa Kozareva

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Robotic Perception and Control with Chelsea Finn

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Reinforcement Learning Deep Dive with Pieter Abbeel

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Intelligent Autonomous Robots with Ilia Baranov

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Global AI Trends with Ben Lorica

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Offensive vs Defensive Data Science with Deep Varma

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Reinforcement Learning: The Next Frontier of Gaming with Danny Lange

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Integrating Psycholinguistics into AI with Dominique (Simmons) Davis

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Deep Neural Nets for Visual Recognition with Matt Zeiler

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Engineering the Future of AI with Ruchir Puri

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Selling AI to the Enterprise with Kathryn Hume

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From Particle Physics to Audio AI with Scott Stephenson

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Introducing the AI NexusLab Startups

Alekh Agarwal Interview - Interactive Machine Learning Systems

Interactive Machine Learning Systems with Alekh Agarwal

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Machine Learning for Cybersecurity with Evan Wright

Stefano Ermon Interview on This Week of Machine Learning & AI

Domain Knowledge in Machine Learning Models for Sustainability with Stefano Ermon

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Scaling Deep Learning: Systems Challenges & More with Shubho Sengupta

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Understanding Deep Neural Networks with Dr. James McCaffrey

Brendan Frey Interview This Week in Machine Learning & AI - Reprogramming the Human Genome with AI

Reprogramming the Human Genome with AI featuring Brendan Frey

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TWiML Talk #11 – Hilary Mason – Building AI Products

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TWiML Talk #10 – Francisco Webber – Statistics vs Semantics for Natural Language Processing

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TWiML Talk #9 – Pascale Fung – Emotional AI: Teaching Computers Empathy

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TWiML Talk #8 – Diogo Almeida – Deep Learning: Modular in Theory, Inflexible in Practice

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TWiML Talk #7 – Carlos Guestrin – Explaining the Predictions of Machine Learning Models

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TWiML Talk #6 – Angie Hugeback – Generating Labeled Training Data for Your ML/AI Models

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TWiML Talk #5 – Joshua Bloom – Machine Learning for the Stars & Productizing AI

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TWiML Talk #4 – Charles Isbell – Interactive AI, Plus Improving ML Education

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TWiML Talk #3 – Xavier Amatriain – Engineering Practical Machine Learning Systems

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TWiML Talk #2 – Siraj Raval – How to Build Confidence as an ML Developer

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Another Huge ML Acquisition, AI in the Olympics + Win a Free Ticket to the O’Reilly AI Conference—TWiML 2016/08/12

Darpa Cyber Grand Challenge

Apple Acquires ML Startup Turi, the DARPA Hacker-Bot Challenge, and Comma.ai’s Autonomous Driving Dataset—TWiML 2016/08/05

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TWiML Talk #1 – Clare Corthell – Open Source Data Science Masters, Hybrid AI, Algorithmic Ethics & More

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Machine Learning for Datacenter Optimization, a ‘Crazy’ New GPU from NVIDIA & Faster RNN Training–TWiML 2016/07/22

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An AI-Powered Wingman for Pokémon Go, and Google’s Wide & Deep Learning Model—TWiML 2016/07/15

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A BS Meter for AI, Predator Robots, and a Free O’Reilly eBook

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Fatal AI Autopilot Crash, EU May Prohibit Machine Learning & More—TWiML 2016/07/01

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Dueling Neural Networks at ICML, Plus Training a Robotic Housekeeper—TWiML 2016/06/24

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ML & AI at Apple, IBM’s Deep Thunder & Exciting New Deep Learning Research—TWiML 2016/06/17

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Self-Motivated AI, Plus A Kill-Switch for Rogue Bots—TWiML 2016/06/10

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Facebook’s DeepText, ML & Art, Artificial Assistants—TWiML 2016/06/03

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The White House on AI & Aggressive Self-Driving Cars—TWiML 2016/05/27

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Google IO, Deep Learning Hardware & an AI to Save You From Conference Call Hell — TWiML 2016/05/20