Twitter has just rolled out an update to its mobile apps for iOS, Android, and the mobile web.

The new apps bring us Twitter users “a single stream of content in each tab,” writes Twitter product management director Esteban Kozak today on the Twitter blog.

The update also includes overall bug fixes and a new way to view links from within the service.

The new versions of the apps gives Twitter on mobile a better interface for the Discover and Search features.

Now, the Discover tab will show a single stream of all content types, including tweets, trends, suggested accounts, and activity. “You can also dive into Activity and Trends from new previews at the top of the Discover tab,” Kozak wrote.

The one-stream-for-all-content approach also carries over to search, which now shows photos, users, and accounts in a single stream. And remember, Twitter content is now being sorted in real time by Mechanical Turk human employees, not just servers and databases — a move Twitter promises will make finding content on its service better and better over time.

In minor tweaks, links now open immediately in your mobile browser when you click them; previously, they expand in Twitter and would require a second tap to actually open the link. Also, the Connect tab will now open to Interactions by default rather than Mentions.

All this comes on the heels of a U.I. upgrade to the Twitter web app just a week ago; that refresh brought bigger photos and a new conversation-threading style to the app.

Top image via Flickr

Twitter has just upgraded the machinery behind its search, this time with added real-time human computation!

Since machines are terrible at things like irony and instantly forming new associations and contexts between seemingly unrelated terms (e.g., “binders of women” and “presidential debate”), the company’s brilliant engineers have decided to call in the big guns: Actual. People.

Although the prevailing wisdom would have it that we meatbags are ridiculously underpowered in the computational power category, Twitter devs Edwin Chen and Alpa Jain write this morning on the company’s engineering blog that meatbags will be used to create annotations for newly trending search terms.

From the blog:

First, we monitor for which search queries are currently popular. Behind the scenes: we run a Storm* topology that tracks statistics on search queries. … As soon as we discover a new popular search query, we send it to our human evaluators, who are asked a variety of questions about the query [via a custom pool of specialized workers from Amazon's Mechanical Turk service]. … Finally, after a response from an evaluator is received, we push the information to our backend systems, so that the next time a user searches for a query, our machine learning models will make use of the additional information. For example, suppose our evaluators tell us that [Big Bird] is related to politics; the next time someone performs this search, we know to surface ads by @barackobama or @mittromney, not ads about Dora the Explorer.”

* Storm is Twitter’s trend-spotting software that quickly identifies spikes in search queries as they occur. You can check it out on GitHub if that sounds interesting to you. Storm, an open-source project, was built at BackType, which Twitter acquired.

Twitter says it uses the meatbag method for other tasks and also focuses on making its machine learning better with human input. For those worried about the quality of said input, Twitter assures the public that only the finest of Mechanical Turk workers are being tapped to handle these kinds of tasks. As the blog notes, “Having highly trusted workers means we don’t need to wait for multiple annotations on a single search query to confirm validity, so we can send responses to our backend as soon as a single judge responds. This entire pipeline is designed for real-time, after all, so the lower the latency on the human evaluation part, the better.”

If all that up there was too wordy for ya, here’s the news in singing telegram form:

Image credit: Shutterstock

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Twitter’s Chief Scientist Abdur Chowdhury, who was responsible for implementing Twitter search and recommendations, confirmed his departure yesterday.

“So Long, and Thanks for All the Fish. Twitter was an amazing experience & even greater set of people,” Chowdhury wrote in a Tweet.

Chowdhury originally joined the company after its acquisition of Twitter-search site Summize, which he co-founded in 2008 with former Twitter CTO Greg Pass. Before that, he was chief architect of search product at AOL and currently co-founder of math- and science-focused independent elementary school Alta Vista in San Francisco.

While its unclear exactly why Chowdhury left, it could have something to do with all the big changes taking place over at Twitter. The company recently closed a second $400 million round of funding and is poised to launch a new advertising platform.

Twitter was unavailable for immediate comment about Chowdhury’s departure.