Why you should care about debugging machine learning models
Understanding and fixing problems in ML models is critical for widespread adoption.
Understanding and fixing problems in ML models is critical for widespread adoption.
It’s clear that AI can and will have a big influence on how we develop software.
Five strategies to harness the power of your company's talent pool.
Dean Wampler discusses the challenges and opportunities businesses face when moving AI from discussions to production.
A look into what robotic process automation (RPA) is, why it matters, and why it’s garnered so much recent interest.
Andrew Smith talks about why he learned to code, and the unexpected pleasures he encountered along the way.
Ankur Patel discusses challenges and opportunities in enterprise machine learning and AI applications.
Eric Jonas on AI hype and questions of ethics.
Noah Firth on giving service members and their families a more friendly user experience, and how his team recruits and measures success.
We need to remember that creating fakes is an application, not a tool—and that malicious applications are not the whole story.
Pamela Rucker talks about designing an organization optimized for employee growth.
In this moment of increasing discontent, we’re entering the dawn of the blockchain era.
Growing adoption of microservices, cloud, containers, and orchestration signal a paradigm shift that we're calling Next Architecture.