A look at the landscape of tools for building and deploying robust, production-ready machine learning models.
To successfully implement AI technologies, companies need to take a holistic approach toward retraining their workforces.
We shouldn't ask our AI tools to be fair; instead, we should ask them to be less unfair and be willing to iterate until we see improvement.
Experts explore the future of hiring, AI breakthroughs, embedded machine learning, and more.
A look at how guidelines from regulated industries can help shape your ML strategy.
Tim Kraska outlines ways to build learned algorithms and data structures to achieve “instance optimality” and unprecedented performance for a wide range of applications.
Michael James examines the fundamental drivers of computer technology and surveys the landscape of AI hardware solutions.
Mikio Braun takes a look at Zalando and the retail industry to explore how AI is redefining the way ecommerce sites interact with customers.
Haoyuan Li offers an overview of a data orchestration layer that provides a unified data access and caching layer for single cloud, hybrid, and multicloud deployments.
Abigail Hing Wen discusses some of the most exciting recent breakthroughs in AI and robotics.
Ion Stoica outlines a few projects at the intersection of AI and systems that UC Berkeley's RISELab is developing.
Pete Warden digs into why embedded machine learning is so important, how to implement it on existing chips, and some of the new use cases it will unlock.
Maria Zheng examines AI and its impact on people’s jobs, quality of work, and overall business outcomes.
Neural-backed generators are a promising step toward practical program synthesis.
From data quality to personalization, to customer acquisition and retention, and beyond, AI and ML will shape the customer experience of the future.
We now are in the implementation phase for AI technologies.
Drawing insights from recent surveys, Ben Lorica analyzes important trends in machine learning.
From basic BI to using AI to automate and augment human endeavors, data-driven systems are increasingly powerful and pervasive in the enterprise.