Intelligence and Comprehension
What does it mean to say a computer model “understands”?
AI & ML
Few technologies have the potential to change the nature of work and how we live as artificial intelligence (AI) and machine learning (ML).
What’s ahead for AI, VR, NFTs, and more?
Here are some predictions for tech in 2022.
MLOps and DevOps: Why Data Makes It Different
Machine Learning’s deployment stack is maturing
The Quality of Auto-Generated Code
When Copilot writes your code, will you care whether it’s good or bad?
2021 Data/AI Salary Survey
Communal Computing’s Many Problems
Where user-centric computing goes wrong
Communal Computing
How do we build devices that are shared by default?
AI Powered Misinformation and Manipulation at Scale #GPT-3
Risks of autoregressive language models and the future of prompt engineering
AI Adoption in the Enterprise 2021
InfoTribes, Reality Brokers
The InfoLandscape is fractured and shared reality is breaking down: who have become our Reality Brokers?
The Next Generation of AI
Is a new generation of AI systems arising from cross-fertilization between different AI disciplines?
Product Management for AI
5 things on our data and AI radar for 2021
Where Programming, Ops, AI, and the Cloud are Headed in 2021
Following O'Reilly online learning trends to see what's coming next.
Our Favorite Questions
Asking very simple questions often leads to discussions that give much more insight than more complex, technical questions.
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.
Pair Programming with AI
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?
Power, Harms, and Data
Data is often biased. But that isn’t the real issue. Why is it biased? How do we build teams that are sensitive to that bias?
AI, Protests, and Justice
COVID-19 and Complex Systems
Decision-Making in a Time of Crisis
A Bad Outcome Doesn't Mean a Bad Decision