Menu

Post image 1
Post image 2
Post image 3
Post image 4
Post image 5
Post image 6
Post image 7
Post image 8
Post image 9
Post image 10
Post image 11
Post image 12
Post image 13
Post image 14
Post image 15
Post image 16
Post image 17
Post image 18
Post image 19
Post image 20
Post image 21
Post image 22
Post image 23
Post image 24
Post image 25
Post image 26
Post image 27
Post image 28
Post image 29
Post image 30
Post image 31
Post image 32
Post image 33
Post image 34
Post image 35
Post image 36
Post image 37
Post image 38
Post image 39
Post image 40
Post image 41
Post image 42
1 / 42
0

Language Models for Text Classification: From Bag-of-Words to Jev

Hacker News·about 16 hours ago
#P5jggCFw
#magazine#jev#llm#classifier#article#ama
Reading 0:00
15s threshold

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.” Figure 1: Quick overview of the Jev API; more details on that later. 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.…

Continue reading — create a free account

Join HashtagPLUS to read full articles, follow hashtags, vote, and join the conversation.

Read More