The Mobile+AI Lab is now 4,000 strong! It is an incredible learning opportunity for us. It feels great to see the community actively participate in the key design decisions.
The most popular feature request from the past 2 weeks is the ability to swipe between open articles.
John took some time this week to enable swiping in the Lab app. Now, when you have an article open, you can swipe to the previous or next article without having to go back to the list.
We are also taking advantage of this build to add some other feature requests and bug fixes.
Questions for the community
Question 1 – What are the missing features or design frustrations preventing you from switching to the Lab app from the old Feedly app? Please let us know in the #general channel of the Lab Slack.
Question 2 – Do you use Feedly on an iPad? Did you join the new #ipad channel on Slack?
Here is the detailed changelog:
Fixed “Edit source settings freeze” Thank you Paul Adams and DCDawg
Fixed “Nav bar is clipped on iPhone SE iOS 12” Thank you curiouscamilo and Heals
Fixed “Long press to open mark-as-read options on iPhone 6”
The Mobile+AI Lab is now 4,000 strong! It is an incredible learning opportunity for us. It feels great to see the community actively participate in the key design decisions.
The most popular feature request from the past 2 weeks is the ability to swipe between open articles.
John took some time this week to enable swiping in the Lab app. Now, when you have an article open, you can swipe to the previous or next article without having to go back to the list.
We are also taking advantage of this build to add some other feature requests and bug fixes.
Questions for the community
Question 1 – What are the missing features or design frustrations preventing you from switching to the Lab app from the old Feedly app? Please let us know in the #general channel of the Lab Slack.
Question 2 – Do you use Feedly on an iPad? Did you join the new #ipad channel on Slack?
Here is the detailed changelog:
Fixed “Edit source settings freeze” Thank you Paul Adams and DCDawg
Fixed “Nav bar is clipped on iPhone SE iOS 12” Thank you curiouscamilo and Heals
Fixed “Long press to open mark-as-read options on iPhone 6”
Newsletters are proving to be a useful tool for team collaboration.
Our teams use them internally, and we will keep building with your feedback in mind.
Thank you to all the teams who have sent questions, feedback, and bug reports!
FAQs
Why didn’t I receive my newsletter? Common problems & solutions:
No new articles saved since the last newsletter sent. It will only send if there are new articles available (ie. saved) in the board.
Solution: For now, we suggest removing and then re-saving some articles to the board. After that, return to the newsletter dashboard and hit “send now” once again.
It works the same way the very first time you activate a newsletter and for your future scheduled newsletters.
Maybe the newsletter is in spam.
Solution: Please check your spam folder and add <teams@feedly.com> to your address book. That will tell your email provider to deliver newsletters to your inbox.
What articles will (or won’t) be included in the newsletter when I hit Send Now?
On-demand newsletters only include new articles saved since the last newsletter sent. This is the most common reason why a newsletter doesn’t send.
To send an on-demand newsletter with specific articles, we suggest removing and then re-saving those articles to the board. After that, return to the newsletter dashboard and hit “send now” once again.
What about analytics?
Coming soon
How do I add newsletters to my Feedly account?
We suggest starting a 30-day free trial of Feedly Teams. The trial gives you full access to newsletters and our support team. We are here to help you and your team get the most out of Feedly.
Thank you for trying newsletters! Have a question not answered here? Ask us in the comments or in the app.
We love the Web because it is an open and distributed network that offers everyone the freedom and control to publish and follow what matters to them.
We also love the web because it has enabled a new generation of content creators (Ben Thompson, Bruce Schneier, Tina Eisenberg, Seth Godin, Maria Popova, etc.). Those independent thinkers continuously explore the edge of the known and share insightful and inspiring ideas with their communities.
Connecting people to the best sources for the topics that matter to them has been core to our mission since the very start of Feedly.
But discovery is a hard problem. The web is organic, a reflection of the global community’s changing needs and priorities. There are millions of sources across thousands of topics and we all have a different appetite when it comes to feeding our minds.
About twelve months ago, we created a machine learning team to see if the latest progress in deep learning and natural language processing could help us crack this nut.
Today, we are excited to give you a preview of the result of that work with the release of the new discovery experience in the Feedly Lab app (Experience 06).
Two thousand topics
The first discovery challenge is to create a taxonomy of topics.
You can think of Feedly as a rich graph of people, topics, and sources. To build the right taxonomy, we started with the raw data on all of Feedly’s sources. We had to create a model to clean, enrich, and organize that data into a hierarchy of topics. Learn more about the data science behind this.
The result is a rich, interconnected network of two thousand English topics. And it’s mapped well with how people expect to explore and read on the Web.
On the discovery homepage, we showcase thirty topics based on popular industries, trends, skills, or passions. You can access all of the topics in Feedly via the search box.
The fifty most interesting sources
The second discovery challenge is to find the fifty most interesting sources someone researching any topic might want to follow.
Ranking sources is hard because not all sources are equal. In tech as an example, you have mainstream publications like The Verge or TechCrunch, expert voices like Ben Thompson, and lots of B-list noisy sources which don’t add much value.
In addition, for niche topics like virtual reality, some sources are specific to VR while others cover a range of related topics.
To solve this challenge, we created a model which looks at sources through three different lenses:
follower count
relevance (how focused is the source on the given topic)
engagement (a proxy for quality and attention)
The outcome is new search result cards. You can explore the fifty most interesting sources for a given topic and sort them using the lens that is most important to you.
Neighborhoods
One of the benefits of the new topic model is that the 2,000 topics are organized in a hierarchy. This makes it easy for you to zoom in or out and explore many different neighborhoods of the Web.
For example, from the cybersecurity topic, you can jump to a list of related topics that let you dig deeper into malware, forensics, or privacy.
One more thing…
We have done a lot of research over the last four years to understand how people discover new sources. One insight we learned is that people often co-read certain sources. For example, if you are interested in art, design, and pop culture and you follow Fubiz, there is a high chance that you also follow Designboom.
With that in mind, we spent some time creating a model that learns what sources are often co-read. The idea is that a user could enter a source that they love and discover another source they could pair it with.
You can learn more about the machine learning model (we call it feed2vec) powering this experience through the article Paul published here.
As a user, you can access this feature by searching in the discover page for a source you love to read. The result will be a list of sources which are often co-read with that source.
Thank you!
I would like to thank Paul, Michelle, Mathieu, and Aymeric for the great research work they did to take this project from zero to one. People who have tried to tackle discovery know that it is a very hard challenge and the results of this project have been very impressive.
We would also like to thank the community for participating in the Battle of the Sources experiment. Your input was key in helping us learn how to model the source ranking. We are going to continue to invest in discovery and we look forward to continuing to collaborate with you.
We would also like to thank Dan Newman, Daron Brewood, Enrico, Joey, Lior, Paul Adams, Ryan Murphy, and Joseph Thornley from the Lab for reviewing an earlier version of this article.
Your turn
Pick a topic you are interested in or a source you love to read and try out the new discovery experience. We’d love to hear your feedback in the channel “06-discover” of the Lab Slack.
Question 1 – What topic or source did you search for?
Question 2 – Is there a topic you were looking for and you did not find?
Question 3 – Is the metadata about each source in the search result useful? Anything missing? Anything we could remove?
Question 4 – Did auto-completion work well for you?
Question 5 – Were you satisfied with the quality of the results?
Question 6 – Did the ranking seem intuitive?
Question 7 – Did the related topics seem relevant?
Question 8 – Is there a feature you would like to see add
We love the Web because it is an open and distributed network that offers everyone the freedom and control to publish and follow what matters to them.
We also love the web because it has enabled a new generation of content creators (Ben Thompson, Bruce Schneier, Tina Eisenberg, Seth Godin, Maria Popova, etc.). Those independent thinkers continuously explore the edge of the known and share insightful and inspiring ideas with their communities.
Connecting people to the best sources for the topics that matter to them has been core to our mission since the very start of Feedly.
But discovery is a hard problem. The web is organic, a reflection of the global community’s changing needs and priorities. There are millions of sources across thousands of topics and we all have a different appetite when it comes to feeding our minds.
About twelve months ago, we created a machine learning team to see if the latest progress in deep learning and natural language processing could help us crack this nut.
Today, we are excited to give you a preview of the result of that work with the release of the new discovery experience in the Feedly Lab app (Experience 06).
Two thousand topics
The first discovery challenge is to create a taxonomy of topics.
You can think of Feedly as a rich graph of people, topics, and sources. To build the right taxonomy, we started with the raw data on all of Feedly’s sources. We had to create a model to clean, enrich, and organize that data into a hierarchy of topics. Learn more about the data science behind this.
The result is a rich, interconnected network of two thousand English topics. And it’s mapped well with how people expect to explore and read on the Web.
On the discovery homepage, we showcase thirty topics based on popular industries, trends, skills, or passions. You can access all of the topics in Feedly via the search box.
The fifty most interesting sources
The second discovery challenge is to find the fifty most interesting sources someone researching any topic might want to follow.
Ranking sources is hard because not all sources are equal. In tech as an example, you have mainstream publications like The Verge or TechCrunch, expert voices like Ben Thompson, and lots of B-list noisy sources which don’t add much value.
In addition, for niche topics like virtual reality, some sources are specific to VR while others cover a range of related topics.
To solve this challenge, we created a model which looks at sources through three different lenses:
follower count
relevance (how focused is the source on the given topic)
engagement (a proxy for quality and attention)
The outcome is new search result cards. You can explore the fifty most interesting sources for a given topic and sort them using the lens that is most important to you.
Neighborhoods
One of the benefits of the new topic model is that the 2,000 topics are organized in a hierarchy. This makes it easy for you to zoom in or out and explore many different neighborhoods of the Web.
For example, from the cybersecurity topic, you can jump to a list of related topics that let you dig deeper into malware, forensics, or privacy.
One more thing…
We have done a lot of research over the last four years to understand how people discover new sources. One insight we learned is that people often co-read certain sources. For example, if you are interested in art, design, and pop culture and you follow Fubiz, there is a high chance that you also follow Designboom.
With that in mind, we spent some time creating a model that learns what sources are often co-read. The idea is that a user could enter a source that they love and discover another source they could pair it with.
You can learn more about the machine learning model (we call it feed2vec) powering this experience through the article Paul published here.
As a user, you can access this feature by searching in the discover page for a source you love to read. The result will be a list of sources which are often co-read with that source.
Thank you!
I would like to thank Paul, Michelle, Mathieu, and Aymeric for the great research work they did to take this project from zero to one. People who have tried to tackle discovery know that it is a very hard challenge and the results of this project have been very impressive.
We would also like to thank the community for participating in the Battle of the Sources experiment. Your input was key in helping us learn how to model the source ranking. We are going to continue to invest in discovery and we look forward to continuing to collaborate with you.
We would also like to thank Dan Newman, Daron Brewood, Enrico, Joey, Lior, Paul Adams, Ryan Murphy, and Joseph Thornley from the Lab for reviewing an earlier version of this article.
Books have the power to inspire, connect, and educate. Today in honor of Book Lovers Day, here are some of the books that have inspired the Feedly team as lifelong learners.
What’s on your must-read list right now? What recent read inspired you to see the world in a new way? Tweet at us, or comment below. We always respond.
Emily says, “I felt a connection to this 67-year-old woman who lived and worked on farms all her life before deciding she needed to hike the 2,050-mile Appalachian Trail. The suffering she happily endured on the trail must have been a welcome relief from the darkness of her past.”
Victoria says, “This is one of my faves because of the empathy and understanding it creates within you as you experience the loss of eviction through the eyes of the evicted. It’s a powerful piece on how to better take care of your neighbors.”
Eduardo says“It’s easily one of my favorite books. The struggle of the guy who was adrift at sea … he never lost hope. You could almost feel what he was feeling. That’s the vividness of the writing.”
Remi says, “Finnegan has a way of pulling his reader into what a life of pursuing their obsession and journeying all over the world really feels like. Bonus points for the years in South Africa which bring it back to a moment in history … beautifully written, permeating passion all the way through.
Guillaume says, It has the best reread value of any book I know. Every piece is incredibly beautiful and well written, and the whole volume oozes a sort of calm melancholy that always gets me.
Books have the power to inspire, connect, and educate. Today in honor of Book Lovers Day, here are some of the books that have inspired the Feedly team as lifelong learners.
What’s on your must-read list right now? What recent read inspired you to see the world in a new way? Tweet at us, or comment below. We always respond.
Emily says, “I felt a connection to this 67-year-old woman who lived and worked on farms all her life before deciding she needed to hike the 2,050-mile Appalachian Trail. The suffering she happily endured on the trail must have been a welcome relief from the darkness of her past.”
Victoria says, “This is one of my faves because of the empathy and understanding it creates within you as you experience the loss of eviction through the eyes of the evicted. It’s a powerful piece on how to better take care of your neighbors.”
Eduardo says“It’s easily one of my favorite books. The struggle of the guy who was adrift at sea … he never lost hope. You could almost feel what he was feeling. That’s the vividness of the writing.”
Remi says, “Finnegan has a way of pulling his reader into what a life of pursuing their obsession and journeying all over the world really feels like. Bonus points for the years in South Africa which bring it back to a moment in history … beautifully written, permeating passion all the way through.
Guillaume says, It has the best reread value of any book I know. Every piece is incredibly beautiful and well written, and the whole volume oozes a sort of calm melancholy that always gets me.
Some of you really love to read Feedly at night, or you prefer to read in night mode all day. In Mobile+AI Lab Experiment 05, we have a new night mode theme that turns Feedly into a friendly low-light experience.
To turn on night mode, open the left navigation bar, scroll to the bottom, and tap on “night mode.”
Two questions for the community:
Question 1. For those of you who like the dark mode, does the contrast we offer in this first iteration align with what you expect?
Question 2. Did you see any theme-related bugs? Any parts we missed that are still displaying day mode when you have night mode selected?
Looking forward to seeing you on channel 05-night-mode of the Feedly Lab Slack.
Some of you really love to read Feedly at night, or you prefer to read in night mode all day. In Mobile+AI Lab Experiment 05, we have a new night mode theme that turns Feedly into a friendly low-light experience.
To turn on night mode, open the left navigation bar, scroll to the bottom, and tap on “night mode.”
Two questions for the community:
Question 1. For those of you who like the dark mode, does the contrast we offer in this first iteration align with what you expect?
Question 2. Did you see any theme-related bugs? Any parts we missed that are still displaying day mode when you have night mode selected?
Looking forward to seeing you on channel 05-night-mode of the Feedly Lab Slack.
We have been using the iPhone X for two weeks and have found the fluidity of the touch-based interface and the beauty of the new OLED screen very inspiring. We just pushed out a new version of Feedly that takes advantage of these new features and more. We hope that you will enjoy using it as much as we enjoyed building it.
New Layout
The new Feedly app is optimized for the iconic iPhone notch and respects the bottom home area.
New iPhone X Layout
New OLED-Friendly Black Theme
The iPhone X comes with an incredible OLED display. We transformed the Feedly dark team to pure black, creating a sharper and more energy efficient experience.
OLED-Friendly Pure Black Theme
Seamless Buffer Integration
Lots of Feedly Pro users use the content they discover in Feedly to mold their digital identity and showcase their expertise on Social Media. Buffer makes sharing on LinkedIn, Twitter, Facebook and other networks easier and more efficient. In this new version of Feedly, we have optimized the user experience for Feedly+Buffer users. In one click, you can jump from reading an article in Feedly to sharing that article in the Buffer app.
Thank you to Andy and the Buffer team for their collaboration on this joint project!
1-Click Buffer Integration
Polish, Polish, Polish…
Upgraded the Twitter and Facebook integrations so that you can easily share articles you find interesting
Improved the Google News keyword alert integration
