AI Music, Mind-Controlled Robot Hands, Uber's Repo Tools, and Career Resilience
Rajendra Prasad explains how leaders in large enterprises can make AI adoption successful.
Ruchir Puri discusses the next revolution in automating AI, which strives to deploy AI to automate the task of building, deploying, and managing AI tasks.
How can machine learning decode the mysteries of life? Olga Troyanskaya explores this and other big questions through the prism of deep learning.
Kim Hazelwood discusses the hardware and software Facebook has designed to meet its scale needs.
Carlos Humberto Morales offers an overview of Nauta, an open source multiuser platform that lets data scientists run complex deep learning models on shared hardware.
Nick Curcuru explains how Mastercard is using AI to improve security without sacrificing the customer experience.
Christopher Ré discusses Snorkel, a system for fast training data creation.
Sean Gourley considers the repercussions of AI-generated content that blurs the line between what's real and what's fake.
Geospatial Feature Engineering, 3D Reconstruction, Fast NLP, and Learning the Zork Interpreter Language
Kurt Muehmel explores AI within a broader discussion of the ethics of technology, arguing that inclusivity and collaboration are necessary.
Joleen Liang explains how AI and precise knowledge points can help students learn.
Martial Hebert offers an overview of challenges in AI for robotics and a glimpse at the exciting developments emerging from current research.
Aleksander Madry discusses roadblocks preventing AI from having a broad impact and approaches for addressing these issues.
Watch highlights from expert talks covering AI, machine learning, deep learning, ethics, and more.
Ben Lorica and Roger Chen assess the state of AI technologies and adoption in 2019.
Danielle Dean explains how cloud, data, and AI came together to help build Automated ML.
Gadi Singer discusses the major questions organizations confront as they integrate deep learning.
Tony Jebara explains how Netflix is personalizing and optimizing the images shown to subscribers.
Thomas Henson considers how AI will shape the experiences of future generations.
Infocom Source, Twitter Design, New Ways of Seeing, and Software Blowouts
Data Brokers, AI Research Ethics, Overclaimed Science, and Hardware for ML
Making a Group, Robot Arms, Human Contact, and a Personal Archive
Balancing risk and reward is a necessary tension we'll need to understand as we continue our journey into the age of data.
Automating Statistical Analysis, Chinese AI, Data Sovereignty, and Open vs. Government Licensing
The O’Reilly Data Show Podcast: Avner Braverman on what’s missing from serverless today and what users should expect in the near future.
6 Pagers, Ethically Aligned Design, Infrastructure Malware, and IPv6 Scanning
iPhone Dominance, Security Keys, Embedded Systems Course, and Better Slack Client
From Chrome to Edge, Old Web, Public Sans, and The Feedback Fallacy
Or, why science and engineering are still different disciplines.
Chinese Livestreaming, Tech and Teens, YouTube Professionalizing, and Inclusive Meetings
DIY Bio, Perl, Knowledge Graph Learning, and Amazon Memos
Language Creators, Undersea Cable, Open Source Trends, Making Math Questions
Get hands-on training in TensorFlow, cloud computing, blockchain, Python, Java, and many other topics.
HTML DRM, Toxic Incentives, Moral Crumple Zones, and Stats + Symbols
The toughest bias problems are often the ones you only think you’ve solved.
Why companies are turning to specialized machine learning tools like MLflow.
Content Moderation, Speech in 1.6kbps, Science is Hard, and Forensic Typography
Communist RuneScape, API Versioning, Computer Graphics, User Stories
Programming Languages, Asset Graphing, Statistical Tests, and Embeddable WebAssembly
Watch highlights from expert talks covering AI, machine learning, data analytics, and more.
The Strata Data Award is given to the most disruptive startup, the most innovative industry technology, the most impactful data science project, and the most notable open source contribution.
Lauren Kunze discusses lessons learned from an analysis of interactions between humans and chatbots.
Elizabeth Svoboda explains how biosensors and predictive analytics are being applied by political campaigns and what they mean for the future of free and fair elections.
Google BigQuery co-creator Jordan Tigani shares his vision for where cloud-scale data analytics is heading.
Peter Singer explores the new rules of power in the age of social media and how we can navigate a world increasingly shaped by "likes" and lies.
Theresa Johnson outlines the AI powering Airbnb’s metrics forecasting platform.
Mike Olson describes the key capabilities an enterprise data cloud system requires, and why hybrid and multi-cloud is the future.
The O’Reilly Data Show Podcast: Forough Poursabzi Sangdeh on the interdisciplinary nature of interpretable and interactive machine learning.
Data-Oriented Design, Time Zone Hell, Music Algorithms, and Fairness in ML
Amy O'Connor explains how Cloudera applies an "edge to AI" approach to collect, process, and analyze data.
Shafi Goldwasser explains why the next frontier of cryptography will help establish safe machine learning.
Jed Dougherty plots AI examples on a matrix to clarify the various interpretations of AI.
Dinesh Nirmal shares a data asset framework that incorporates current business structures and the elements you need for an AI-fluent data platform.
Linkers and Loaders, Low-Low-Low Power Bluetooth, Voice, and NVC
Software Stack, Gig Economy, Simple Over Flexible, and Packet Radio
Hiring for Neurodiversity, Reprogrammable Molecular Computing, Retro UUCP, and Industrial Go
Explainable AI, Product Management, REPL for Games, and Open Source Inventory
Machines will need to make ethical decisions, and we will be responsible for those decisions.
Newsletters, Confidence Intervals, Reverse Engineering, and Human Scale