I'm not a computer science guy, but I had a play with Jev and found it impressive. It allowed me to offer non-technical researchers the ability to classify arbitrary things their participants enter, without prior training or classification, at near instant speed, and negligible cost. My users may find that very helpful in the qualitative research world.
I showed them an innocuous working example of how they could classify thousands of participant entries as "mentioning Italian food" whether it mentioned "pasta", "penne", "rigatone", etc etc. Jev did this task with high confidence, and showed it could differentiate between the inverse, eg had very low confidence when I switch entry to mentioning "hamburgers". I find that a very useful tool to pass on to non-technical colleagues.
But on HN, there are lots of much more qualified people saying Jev is a con, a step backwards, or bonkers that people are impressed. Will one of them tell me plainly what software was doing this prior to Jev, and the like? I don't doubt it existed, but I never came across it. I'm interested to hear from people more expert than myself.
To be precise, software must be able to:
- Classify thousands of entries with arbitrary themes or topics, even if entry doesn't mention that theme or topic directly, with high enough confidence to be useful.
- Do it with thousands of entries in 0-3seconds.
- Do it at negligible cost, eg sub 0.1cents
BeRT, BART and FLAN-T5, for text classification. All of those models are ~half a decade old now, are based on the transformer model, and small enough to run locally. They're not perfectly SOTA, but perform quite well in embedded applications. Fine for low-stakes stuff, I think.
Image classifiers are a hugely competitive space. You've got BeiT, DeiT, MobileOne, ConvNext, FastViT and several more models that all support image classification pipelines.
Thanks for quick reply. I downloaded FLAN for comparison and you are quite right, gives similar results, with the benefit of privacy and self-sovereignty in serving the model.
So other than untestable claims of _how_ Jev generates responses, it's main feature right now is its API design?
A lot of the hate is in the same spirit of the infamous hacker news comment discounting Dropbox because you can just setup an FTP server to do the same thing[1]
In this case, its people who have built BERT classifiers for years, pointing out you can just fine-tune some model to classify. Of course that's true, and still have value, but its not exactly turnkey. And Jev is surprisingly high quality at what its built for.
I frequently have found myself saying, "People pay for that?! But xyz already exists," in the past, but overtime I've learned that (1) marketing is important and (2) if something reduces friction enough to get the wheels turning on something you're trying to achieve, there's always someone (actually a lot of people) out there willing to pay for it even if it's measurably worse than a self-scaffolded solution or even a really good solution that requires a lot of tinkering to get things rolling.
But on HN, there are lots of much more qualified people saying Jev is a con, a step backwards, or bonkers that people are impressed.
As William Gibson said, the future is already here, it’s just not evenly distributed.
So people get excited about existing technologies because they are new to them.
Wrapping an existing technology in a new package is a common way to introduce it to new people…there are many wrappers around ffmpeg, html2pdf, etc. that are marketed as products.
And they seem like magic…hell cassette tapes feel like magic to me even though I had a cassette player in 1973.
Often but not always, the best tool is the one in your hand or the one you know of because then you can just get to the work you are trying to do.
I showed them an innocuous working example of how they could classify thousands of participant entries as "mentioning Italian food" whether it mentioned "pasta", "penne", "rigatone", etc etc. Jev did this task with high confidence, and showed it could differentiate between the inverse, eg had very low confidence when I switch entry to mentioning "hamburgers". I find that a very useful tool to pass on to non-technical colleagues.
But on HN, there are lots of much more qualified people saying Jev is a con, a step backwards, or bonkers that people are impressed. Will one of them tell me plainly what software was doing this prior to Jev, and the like? I don't doubt it existed, but I never came across it. I'm interested to hear from people more expert than myself.
To be precise, software must be able to: - Classify thousands of entries with arbitrary themes or topics, even if entry doesn't mention that theme or topic directly, with high enough confidence to be useful. - Do it with thousands of entries in 0-3seconds. - Do it at negligible cost, eg sub 0.1cents
You're allowed to be excited about new technology.
What are you allowed to feel when it's old technology?
Anything you want. Do as you please, stop waiting for the internet to tell you how to feel about things.
Excited or not.
You don’t need permission to feel how you feel.
BeRT, BART and FLAN-T5, for text classification. All of those models are ~half a decade old now, are based on the transformer model, and small enough to run locally. They're not perfectly SOTA, but perform quite well in embedded applications. Fine for low-stakes stuff, I think.
Image classifiers are a hugely competitive space. You've got BeiT, DeiT, MobileOne, ConvNext, FastViT and several more models that all support image classification pipelines.
Thanks for quick reply. I downloaded FLAN for comparison and you are quite right, gives similar results, with the benefit of privacy and self-sovereignty in serving the model.
So other than untestable claims of _how_ Jev generates responses, it's main feature right now is its API design?
A lot of the hate is in the same spirit of the infamous hacker news comment discounting Dropbox because you can just setup an FTP server to do the same thing[1]
In this case, its people who have built BERT classifiers for years, pointing out you can just fine-tune some model to classify. Of course that's true, and still have value, but its not exactly turnkey. And Jev is surprisingly high quality at what its built for.
1 - https://news.ycombinator.com/item?id=9224
Beware of “just.”
I frequently have found myself saying, "People pay for that?! But xyz already exists," in the past, but overtime I've learned that (1) marketing is important and (2) if something reduces friction enough to get the wheels turning on something you're trying to achieve, there's always someone (actually a lot of people) out there willing to pay for it even if it's measurably worse than a self-scaffolded solution or even a really good solution that requires a lot of tinkering to get things rolling.
But on HN, there are lots of much more qualified people saying Jev is a con, a step backwards, or bonkers that people are impressed.
As William Gibson said, the future is already here, it’s just not evenly distributed.
So people get excited about existing technologies because they are new to them.
Wrapping an existing technology in a new package is a common way to introduce it to new people…there are many wrappers around ffmpeg, html2pdf, etc. that are marketed as products.
And they seem like magic…hell cassette tapes feel like magic to me even though I had a cassette player in 1973.
Often but not always, the best tool is the one in your hand or the one you know of because then you can just get to the work you are trying to do.
First make it work, then make it good. Good luck.