The recently released Jev AI model has been quite a cultural phenomenon in technical communities in the past 2 weeks.
While Jev aims to classify things, it’s easy to dismiss Jev as “just a classifier,” and my own view of Jev has evolved quite a bit over the past few days. In particular, my thoughts went from “classifiers used to be my bread & butter; I can easily build this myself” (more on this later) to “wow, this actually works better than I thought.”
Sure, the latest state-of-the-art GPT and open-weight LLMs can do the same kinds of classification tasks as Jev, while also being capable of much more general decision-making. But Jev’s advantage is that it can handle those classification tasks much faster and more cheaply.
At the other end of the spectrum, for a narrow, well-defined problem, Jev probably won’t classify anything better, faster, or cheaper than a special-purpose classifier. But its selling point is that it is far more general than those task-specific models.
Source: Sebastian Raschka - Ahead of AI — Read the full article on the original site ↗