The unwilling star of this month’s trends is clearly Facebook. Between reports that they knew about the damage that their applications were causing long before that damage hit the news, their continued denials and apologies, and their attempts to block researchers from studying the consequences of their products, they’ve been in the news almost every … Read moreRadar trends to watch: October 2021 – O’Reilly
Kevlin Henney and I were riffing on some ideas about GitHub Copilot, the tool for automatically generating code base on GPT-3’s language model, trained on the body of code that’s in GitHub. This article poses some questions and (perhaps) some answers, without trying to present any conclusions. First, we wondered about code quality. There are … Read moreThe Quality of Auto-Generated Code – O’Reilly
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 best practices for developing and deploying data-intensive applications. This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like … Read moreWhy Data Makes It Different – O’Reilly
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 our businesses. Specifically, data science has introduced rigorous methods for measuring the outcomes of business ideas. These are the strategic ideas that we implement in … Read moreThe Sobering Truth About the Impact of Your Business Ideas – O’Reilly
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. I’m fascinated by the use of large language models to analyze the “speech” of whales, and to preserve endangered human languages. It’s also important that … Read moreRadar trends to watch: November 2021 – O’Reilly
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 similar story. When companies ask for my help in building their ML/AI teams, I often recommend that they consider remote hires. Sometimes I’ll even suggest … Read moreRemote Teams in ML/AI – O’Reilly
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 and business analytics to application building and automation. As more companies look to integrate low-code and no-code solutions into their digital transformation plan, the question … Read moreLow-Code and the Democratization of Programming – O’Reilly
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, everybody wants to build their own version of the metaverse. There are several takes on having avatar-filled meetings in virtual spaces. Unfortunately, this solves the … Read moreRadar trends to watch: December 2021 – O’Reilly
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, and about 25% said that their companies planned to move all of their applications to the cloud in the coming year. This year, we wanted … Read moreThe Cloud in 2021: Adoption Continues – O’Reilly