How to Stay Up to Date with Trends in Tech (Revisited)

Almost three years ago I wrote about how I keep up with industry trends. My habits have changed quite a bit, so I thought I’d write another post about it, as it can be daunting to find pertinent information in a timely manner that is not overwhelming, especially when you are starting out in your technology career.

Below are the tools I use to stay on top of the latest developments in data, machine learning, tech leadership, quantum computing, and the technology industry in general.

Feedly

Yes, RSS is alive and well! I have two sections in Feedly dedicated to technology-related news: general news from reputable sources and various research and engineering blogs.

News

• Hacker News Daily, which provides the top stories for each day, which minimizes the temptation to spend hours on Hacker News with little to show for it.
• Financial Times’ Quantum Technologies section to learn about the latest titbits on quantum computing
• MIT Technology Review’s content is mostly solid, although I avoid any sponsored contributions.
• Quanta Magazine’s Computer Science section.
• Seeking Alpha’s technology news for the intersection of business, finance, and technology.
• The Economist’s Technology section.

Note that anything from Business Insider I actively avoid.

R&D Blogs

The Morning Paper by Adrian Colyer is by far the best investment in broadening your technical horizon, and quite frankly a must-read for professionals with a penchant for research. I have called it out separately because it’s a great way to learn about research in computer science you may not otherwise know about.

Beyond that, I present you my feeds in alphabetical order:

• Airbnb engineering and data science blog.
• AWS Architecture blog.
• Disney Streaming Services technology blog.
• Dropbox blog.
• Etsy’s Code as Craft blog
• Facebook AI blog.
• Google AI blog.
• Google Cloud blog for the latest official information on GCP products.
• IBM’s AI Research blog.
• Intel AI blog, although it contains very little actual research.
• Microsoft Research blog.
• Netflix Tech blog.
• NVIDIA RAPIDS AI blog.
• Spotify Labs.
• Uber Engineering blog.

I tend to avoid blogs that are mostly announcement boards for companies’ products, or organizations that write multiple posts a day. It’s rare for quality content to pop up that frequently. Such blogs are often extensions of company career pages, which is not what I care to read regularly.

Newsletters

There are a few newsletters delivered to my inbox:

• Scala Times, enough said.
• Patrick Kua’s Level Up, a curated newsletter about topics in technology leadership. If you do not know who Patrick Kua is, have a look at Talking with Tech Leads, which is a great resource for those who want to slip into the role of tech lead.
• Nature briefings. While these are not specific to my area of interest, they are easy to skim, and it may be enlightening to read about occasional breakthroughs in archaeology or medicine.
• The ML Engineer from The Institute for Ethical AI & ML.
• Data Elixer, which usually contains news, industry insights, tutorials, projects, code, tools, resources, and reviews.
• MIT Technology Review’s The Algorithm, especially for the ‘Bits and Bytes’ section with plenty of links to AI in media.
• Fortune’s Eye on AI, which complements The Algorithm nicely.
• The Batch, although it’s mostly a badly formatted selection of ML-related ramblings by Andrew Ng.
• Papers with Code, which is about ML research articles accompanied by code.
• Morning Brew for news on emerging technologies.
• The Tech Memo, which is a 1-minute summary of technology news.
• O’Reilly’s latest run-down of data and artificial intelligence.
• Quiet Revolution about the quiet power of introverts and leadership advice that embraces all personalities.

You can have a look here, too, for additional inspiration.

Researcher: ML Research

I used to have RSS feeds for various journals and of course arXiv, but that quickly turns into an avalanche of papers you cannot possibly stay on top of. It was therefore with great pleasure I discovered Researcher, which solves that problem neatly. While you can follow journals, you can also set up (Boolean search) filters on top of your followed resources. This means that you can avoid seeing the research you are not interested in.

Below are two screenshots of what the app looks like on iOS. The left image shows the filtered feed, in this case for machine learning, where I ignore many medical papers that make use of machine learning, because it is not something I am interested in or in most cases qualified to understand. The right image is available from the search menu (middle button) and it shows the most viewed articles in a particular field.

When you discover an interesting article, you can simply bookmark it by tapping on the button that looks like a red bookmark in a circle.

Paperpile: Research Organizer

So, what do you do with all those bookmarked papers? The Researcher app currently supports Zotero and Mendeley, but I prefer Paperpile. It syncs PDFs (including highlights and notes) to Google Drive and it lives in a browser, so it’s wherever there is an internet connection. Its in-browser annotation plug-in is nifty and I use it a lot. Paperpile is a no-nonsense organizer for scientific articles, and it is absolutely worth the $2.99 per month.