• Jun 02, 2025* TL;DR: Infinite scroll, emoji tags, email digests, and more! Hi friends, First off, I’d love your feedback on Scour! Please email me at evan at scour.ing if you’d be willing to get on a quick call with me to talk about your experience with and opinions on Scour. As always, you can also leave suggestions on the feedback board. Now, on to the update! In May, Scour scoured 458,947 posts from 4,323 feeds looking for great content for you. Here are the new features I added in the past month: Scour now uses infinite scroll instead of pagination, which should make it easier to keep reading. Thanks Vahe for the suggestion!

🎯 Inline Interest Recommendations

Topic recommendations are interspersed into the main feed to make them easier to see and add (you can also find them on the Interests page). Let me know what you think of these suggestions!

😊 Emojis

Every interest is assigned an emoji and those are used to identify which topics are most closely related to any given post. This should make it easier to visually scan through the feed. Thanks Vahe for this suggestion as well! If you haven’t tried it already, you can click on any one of your interests to see all of the posts related to that specific interest.

📨 Email Digests

Email digests have landed! They’re currently sent out every week on Fridays. The contents are made up of the first 10 results from the weekly feed view (which is why you’ll see different items if you go to your feed and have it set to Hot mode or another timeframe). Let me know if you find these useful – or if you’d prefer to get them at another day or time! Thanks to Allen and Laurynas for this suggestion, and to Alex for his feedback on the styling!

🌗 Light/Dark Mode Toggle

Previously, Scour would use light or dark mode based on your browser settings. Now, you can toggle it for yourself using the switch in the dropdown menu. Thanks to u/Hary06 on Reddit for the suggestion!

📡 Interest Feeds

For those of you that use Scour along with an RSS reader, you can now consume each of your interest pages as a separate feed. You can also export all of your interest feeds as an OPML file on your Interests page or via this link. This idea came out of a great feedback call I had with Connor Taffe. Thanks Connor for the idea and for taking the time to chat!

🗺️ Finding New Feeds

The Browse Popular Feeds and Browse Newest Feeds pages now hide feeds you are already subscribed to by default. This should make it easier to use those to find new feeds you want to subscribe to. If you haven’t tried these out yet, you can also find personalized feed recommendations on your Feeds page. Scour has been using Mixedbread’s embedding model, mxbai-embed-large-v1, since its inception and I have been a happy user of the company’s hosted embeddings API for the past 7 months. This month, I chatted with one of their co-founders, they liked Scour, and they offered to sponsor Scour’s embeddings. I think they’re doing interesting work on embeddings, search, and information retrieval, so I was happy to take them up on the offer.

👷‍♂️ Bug Fix

I fixed a bug that caused some posts to have the wrong embedding assigned, which meant that some posts would be shown as being related to the wrong interests. If you noticed some strange post recommendations before, sorry about that! Shouldn’t happen anymore.

📝 My Blog Posts

I wrote two posts in May, one about Scour and the other not:

• Announcing Scour on r/rss
• New Life Hack: Using LLMs to Generate Constraint Solver Programs for Personal Logistics Tasks

🔖 Some of My Favorite Posts

Finally, here were a couple of my favorite posts that I found on Scour in May:

• Through this Twitter thread, All Embedding Models Learn the Same Thing, I came across the paper Harnessing the Universal Geometry of Embeddings and The Platonic Representation Hypothesis. It’s pretty wild that different models converge on similar representations of the same data, and that you could potentially translate directly between them!
• Through the post Bring Vector Compression to the Extreme, I came across the RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search paper. As someone interested in binary vector embeddings (which Scour uses), this was another great read.
• Using ‘Slop Forensics’ to Determine Model Ancestry
• Better Air Purifiers (You can also save posts that you find on Scour using the love / like icons next to each post’s title.) Happy Scouring!
• Evan #scour