What’s ahead for AI, VR, NFTs, and more?
Every year starts with a round of predictions for the new year, most of which end up being wrong. But why fight against tradition? Here are my predictions for 2022.…
Radar trends to watch: January 2022
All things considered, December was a short month: I’m writing this on December 20, with a week and a half left until January. But it hasn’t been inactive. We’ve seen…
Why it’s too early to get excited about Web3
There’s been a lot of talk about Web3 lately, and as the person who defined “Web 2.0” 17 years ago, I’m often asked to comment. I’ve generally avoided doing so…
The Cloud in 2021: Adoption Continues
Last year, our report on cloud adoption showed that companies were moving quickly to adopt the cloud: 88% of our respondents from January 2020 said that they used the cloud,…
Radar trends to watch: December 2021
The last month had a few surprises. Three items about quantum computing—all of which appeared on the same day. You’d think they were coordinating with each other. And of course,…
Low-Code and the Democratization of Programming
In the past decade, the growth in low-code and no-code solutions—promising that anyone can create simple computer programs using templates—has become a multi-billion dollar industry that touches everything from data…
Remote Teams in ML/AI
I’m well-versed in the ups and downs of remote work. I’ve been doing some form thereof for most of my career, and I’ve met plenty of people who have a…
Radar trends to watch: November 2021
While October’s news was dominated by Facebook’s (excuse me, Meta’s) continued problems (you’d think they’d get tired of the apology tour), the most interesting news comes from the AI world.…
The Sobering Truth About the Impact of Your Business Ideas
The introduction of data science into the business world has contributed far more than recommendation algorithms; it has also taught us a lot about the efficacy with which we manage…
MLOps and DevOps: Why Data Makes It Different
Much has been written about struggles of deploying machine learning projects to production. As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or…
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