Building and deploying AI applications and systems at scale
Ben Lorica and Roger Chen review how companies are building AI applications today.
Roger Chen
Roger Chen is Co-Founder & CEO of Computable Labs, and he serves as Program Chair for the Artificial Intelligence Conference. Previously, he was a Principal at O'Reilly AlphaTech Ventures (OATV), where he invested in and worked with early-stage startups primarily in the realm of data, machine learning, and robotics. Roger has a deep and hands-on history with technology. Before startups and venture capital, he was an engineer at Oracle, EMC, and Vicor. He also developed novel nanoscale and quantum optics technology as a Ph.D. researcher at UC Berkeley. Roger holds a BS from Boston University and a Ph.D. from UC Berkeley, both in electrical engineering..
Radar
Checking in on AI tools
Ben Lorica and Roger Chen assess the state of AI technologies and adoption in 2019.
The state of automation technologies
Ben Lorica and Roger Chen highlight recent trends in data, compute, and machine learning.
Unlocking innovation in AI
Ben Lorica and Roger Chen provide a glimpse into tools and trends poised to accelerate AI innovation.
Understanding automation
Ben Lorica and Roger Chen discuss the state of reinforcement learning and automation.
The state of AI adoption
AI Conference chairs Ben Lorica and Roger Chen reveal the current AI trends they've observed in industry.
Content
2019 Emerging AI Pioneers Showcase winners
AI startups vied for awards at the O’Reilly Artificial Intelligence Conference in San Jose.
Setting benchmarks in machine learning
Dave Patterson and other industry leaders discuss how MLPerf will define an entire suite of benchmarks to measure performance of software, hardware, and cloud systems.
Data liquidity in the age of inference
Probabilistic computation holds too much promise for it to be stifled by playing zero sum games with data.
Intelligent Bits: 16 June 2017
AI fighting extremism, intuitive physics, and schema networks.
Intelligent Bits: 9 June 2017
Drawing with AI, Apple AI API, United Nations and AI for good, and smart oil and gas.
Intelligent Bits: 26 May 2017
Sukiyaki in French style, brick-and-mortar conversion tracking, route-based pricing, and technological productivity.
Intelligent Bits: 19 May 2017
AutoML, AI photo editing, AI product studio, and Apple and dark data.
Intelligent Bits: 12 May 2017
Medical ImageNet, NVIDIA GTC, corporate responsibility in tech, online pricing
Personalizing fashion with human-in-the-loop machine intelligence
How Stitch Fix systematizes collaboration between stylists and AI software.
Intelligent Bits: 05 May 2017
Caffe2, deep learning best practices, intelligent design and wizard hats
Intelligent Bits: 28 April 2017
Creative deep neural networks, AI black box, robot food delivery, and brute force productivity.
Deep learning: Modular in theory, inflexible in practice
Diogo Almeida examines the capabilities and challenges in deep learning.
Practicalities of employing deep learning at scale
Kenny Daniel on implementing neural networks in production.
Shrinking and accelerating deep neural networks
Song Han on compression techniques and inference engines to optimize deep learning in production.
Making telecommunications infrastructure smarter
Turning physical resource management into a data and learning problem.
Emerging technology has a definition problem
The next big technologies are defined by their emerging market value.