Communal Computing
How do we build devices that are shared by default?
Deep Dive
Exploration and insight on topics that sit at the intersection of business and technology.
AI Powered Misinformation and Manipulation at Scale #GPT-3
Risks of autoregressive language models and the future of prompt engineering
The End of Silicon Valley as We Know It?
Four ways the party may be coming to an end
Product Management for AI
Seven Legal Questions for Data Scientists
AI Product Management After Deployment
The AI product manager’s job isn’t over when the product is released. PMs need to remain engaged after deployment.
How to Set AI Goals
Identifying AI opportunities and setting appropriate goals are critical to AI success, and yet can be difficult to do in practice. Some reasons for this include lack of AI literacy, maturity, and many other factors.
Why Best-of-Breed is a Better Choice than All-in-One Platforms for Data Science
All-in-one platforms built from open source software make it easy to perform certain workflows, but make it hard to explore and grow beyond those boundaries.
Bringing an AI Product to Market
Previous articles have gone through the basics of AI product management. Here we get to the meat: how do you bring a product to market?
Automated Coding and the Future of Programming
How automation is likely to change professional software development.
Reclaiming the stories that algorithms tell
Getting curious about the numbers attached to other people can help us to use data wisely—and to see others clearly.
What to Do When AI Fails
Practical Skills for The AI Product Manager
When models are everywhere
How data privacy leader Apple found itself in a data ethics catastrophe
Companies that succeed will protect, fight for, and empower their users
What you need to know about product management for AI
A product manager for AI does everything a traditional PM does, and much more.
The unreasonable importance of data preparation
Your models are only as good as your data.
3 ways to confront modern business challenges
Leaders highlight the importance of continuous improvement, applying lessons from technology processes, and striving for humility.