Four short links: 17 September 2019
Trust in Assistants, Cache your CI's Dependencies, Reproducibility Checklist, and False Positives
All Articles
Four short links: 16 September 2019
Decentralized Challenges, D3 Deconstructor, Text Extraction, and The Great Reckoning
Radar trends to watch: September 2019
We’re tracking notable developments in the democratization of AI, open source supply chain attacks, brain-computer interfaces, and more.
Four short links: 13 September 2019
Attacking NLPs, Data Kit, Quantum Computing and Computation, and What-If Question Archive
Safe and smarter driving, powered by AI
Lei Pan explores how Nauto uses AWS to continually evolve smarter data for driver behavior.
On gradient-based methods for finding game-theoretic equilibria
Michael Jordan details several recent results that blend gradient-based methodology with game-theoretic goals.
Accelerate with purpose
Ananth Sankaranarayanan discusses three three key shifts in the AI landscape, how to navigate them, and when to explore hardware acceleration.
Practical insights into deep reinforcement learning
Sahika Genc dives deep into state-of-the-art techniques in deep reinforcement learning for a variety of use cases.
Open-endedness: A new grand challenge for AI
Kenneth Stanley discusses how open-ended algorithms can offer an entirely different level of automated creation.
Four short links: 12 September 2019
Bayesian Philosophy, Combining Features, Quantum INTERCAL, and Universal Decay of Memory
AI for ophthalmology: Doing what doctors can’t
Daniel Russakoff discusses how AI is being used to predict age-related macular degeneration progression.
Enabling AI’s potential through wafer-scale integration
Andrew Feldman discusses the Wafer Scale Engine, the largest chip ever built.
Getting from A to AI
Eric Gardner shares a four-step journey that all kinds of organizations can use to evaluate their unique paths from data to insights.
Highlights from the O’Reilly Artificial Intelligence Conference in San Jose 2019
Experts discuss new trends, tools, and issues in artificial intelligence and machine learning.
Going beyond fully supervised learning
Srinivas Narayanan takes a deep look into the next change we’re seeing in AI—going beyond fully supervised learning techniques.
Developing AI responsibly
Sarah Bird discusses the major challenges of responsible AI development and examines promising new tools and technologies to help enable it in practice.
Unlocking the value of your data
Dinesh Nirmal examines how organizations can unlock the value of their data for AI with a unified, prescriptive information architecture.
Four short links: 11 September 2019
Distributed Consistency, Face Anonymization, Game Mechanic Discovery, and Images of Images