![]() ![]() Filming took place at Nimoy's home on September 5, 2001, and Billy West narrated the title sequence. Mind Meld was produced to advertise Shatner's personal website. Shatner talks about the death of his third wife, Nerine Kidd, who accidentally drowned in a pool in 1999 after suffering from alcoholism. It was in this film that Nimoy first publicly revealed that he had struggled with alcoholism while he was acting in the original television series. They talk about differences they had with Gene Roddenberry, the creator of Star Trek, and about the strained relationships between Shatner and some of the other cast members. Kirk and Spock respectively in the 1960s Star Trek television series, the 1970s animated television series, and their film sequels. Shatner and Nimoy portrayed the characters James T. The Android app cleverly uses the OS’s Accessbility feature (it’s where you might put, for example, a text-to-speech app for the visually impaired) to overlay Dango on top of any app, but it’s not quite so straightforward on iOS.Mind Meld: Secrets Behind the Voyage of a Lifetime is a 2001 American documentary film in which actors William Shatner and Leonard Nimoy discuss the Star Trek science fiction franchise and its effects on their lives. In a separate email, he told me that the functionality in the demo box on the website (producing strings of related emoji) was yet to come, and that there’s no timing on the iOS side of things. Now that we’re publicly launched we’re also looking at adding a way for people to report problematic results. We’ve in the past blacklisted certain associations and we’ll keep doing this - not unlike what Google does for its search suggestions - but it will be an ongoing challenge to get right. Unfortunately, there’s no API to call just yet, though Dango co-founder Will Walmsley told TechCrunch they were open to it if people are interested.Īnother potential issue I asked about was the ever-present threat when you look at data from real people: What happens when the system internalizes racist, sexist and generally bad data?Ĭlearly sensing this is a sore point among AIs that interact with humans, Walmsley gave a more thorough response:īad associations are a real, and subtle, concern since AI tools like Dango reflect back our human best and our worst. ![]() I love the visualization they created of how various emoji are associated with one another:ĭango’s database is being regularly updated to keep up with the latest slang and memes, too, but you’ll have to wait for app updates to get access to them the associational database is local so there’s no lag or call-outs to a server. This deeper dive into the way emoji are used - and combinations thereof that can create entirely new meanings - would seem to produce quite a powerful data set. I had a little trouble finding a place where the cake piece wouldn’t block any text or critical buttons in my messaging apps, but your mileage may vary.Īutomatic emoji suggestions exist, of course, but the ones out there generally rely on something basic but functional: suggesting the storm or snow emoji when you use words like “snow,” “snowy,” “snowflake” and so on. Mainly it automatically suggests a top emoji for the situation, with others available as runners-up, as well as stickers and GIFs (thankfully you can tell it not to load them until you tap the cake thing). The app itself doesn’t translate entire phrases yet, though. ![]() Others don’t turn out so well, but you get the idea. Translate that semantic space into a more practically designed database - and boom, you’re done! Simple, right? Assemble the data into a huge, many-dimensional “semantic space” where emoji are closer or more distant from certain concepts and ideas and phrases. Repeat millions of times, checking those guesses against a huge amount of data gathered from the web. The network started by just guessing which emoji go with which words and phrases, then would check that against real-world examples, and every time it got something wrong, it adjusted its parameters. The Dango team (many of the folks who made Minuum) used a recurrent neural network to perform a deep learning task (it’s just something you can do now) examining how emoji are used. It’s free for Android right now, with an iOS version coming out eventually. Its icon is a weird piece of cute cake, which sits above your keyboard watching you type. So not only can it suggest an appropriate one, but it can translate entire sentences. Okay, so Dango is one of those virtual assistants that lives in your chat apps, and this one is based on a neural network that has been trained with millions of examples to understand what emoji mean. Dango is an emoji suggestion chatbot - wait, where are you going? Stay with me, this is actually pretty cool. ![]()
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