Jev is a new type of AI classifier ingesting natural language and outputting probabilities of three types: choices, scores, and yes/no. It promises similar performance to frontier LLMs but roughly two orders of magnitude faster and cheaper.
(Jev has been the talk of the town since it dropped on September 15, but I was travelling in the North when it came out. I first heard about it when a friend texted me, “oh they’re not talking about Jev in the Canadian Arctic?” I assumed “Jev” was the perfect joke name for whatever new thing in AI everyone was suddenly talking about, until I Googled it and discovered that Jev was, in fact, the new thing in AI everyone was suddenly talking about.)
Conspirador Norteño is a fun follow, an anonymous account sniffing out inauthentic social media accounts and bot networks. They used to focus on Twitter, but since that website shut off API access, they have focused on Bluesky. Not long ago, they posted their particular use case for Jev: semi-automated identification of contradictory biographical statements from dubious Bluesky accounts.
Sensational accounts on social media frequently lie about their personal and professional lives (Reddit story accounts are perhaps the most extreme example of this phenomenon), and what Conspirador did was pull posts from a list of Bluesky accounts, use Jev to classify whether they contained biographical claims, then use Jev again to compare claims pairwise to determine if they contradicted each other. For example, inconsistencies in work history or claiming to have good knees in one post and bad knees in another.
The experiment seemed to be fairly successful, despite producing a number of false positives and false negatives.
Remember, it’s always easiest to tell the truth, because then you don’t have to keep two parallel backstories straight: what happened and what you told people happened.