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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...
Where Programming, Ops, AI, and the Cloud are Headed in 2021 – O’Reilly
In this report, we look at the data generated by the O’Reilly online learning platform to discern trends in the technology industry—trends technology leaders...
Patterns – O’Reilly
A few months ago, I said that “making everything into a design pattern is a sign that you don’t know what design patterns really...
Radar trends to watch: October 2021 – O’Reilly
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...
The Quality of Auto-Generated Code – 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...
The Sobering Truth About the Impact of Your Business Ideas – 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...
Seven Legal Questions for Data Scientists – O’Reilly
“he threats to consumers arising from data abuse, including those posed by algorithmic harms, are mounting and urgent.”
FTC Commissioner Rebecca K. Slaughter
Variants of artificial...
Radar trends to watch: November 2021 – 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...
