Jev Fever: Predictive AI Is Superhot Again

The more AI changes, the more it stays the same.

For decades, we data scientists and machine learning professionals were in a long-term, exclusive relationship with predictive AI (aka predictive analytics or enterprise ML).

Then LLMs came along and tempted us almost to the point of divorce – only to now bring us back to our original love: predictive AI.

In the last few weeks, a new industry-darling model called Jev has caught on like wildfire, leaving myriad generative AI users questioning whether chatbots and language generation should reign as the most economically-viable form of “intelligent” tech.

In textbook Silicon Valley rebranding fashion, Jev isn’t framed as “predictive AI” – but that’s exactly what it is. The model drives decisions by way of classifying: Will this customer cancel, is this transaction or network activity malicious, will this LLM fail? And beyond binary “yes/no” prediction, it also performs multi-class classification. More specifically, it renders “judgements” by calculating the probability of each class. If you’re experiencing déjà vu, that’s because this has been the mainstay of standard ML models since the 1970s. Been there, done that.

But a rose by any other name would smell as sweet. Prediction is back, baby!

And wow is this movement strong. Jev took over the social-media geek scene, instigating an instantaneous rush of competitors. In only the last two or three weeks, many new judgement models launched, including ones by OpenAI, Amazon, Nvidia, Databricks and Cloudflare – as well as open source models like Kev, Nimble, Laya (which actually predated Jev’s splash by a year) and others.

What’s Old Is New Again

Just like Meryl Streep in It’s Complicated, AI professionals are exuberantly cheating on their lover... with their ex. But unlike Streep, they often don’t realize it.