Comment by BoorishBears
14 hours ago
Jev is creating a sort of identity crisis for me, because the number of absolutely clueless folks parroting the classifier thing is the first time I've seen this sort of mass psychosis in CS upfront.
Like even 5 minutes of tinkering captures why this isn't anymore like BERT or any past classification model than ChatGPT is like those old Markov Chain generators, yet folks cannot shut up about how this is nothing new.
Absolutely scary and makes me wonder how much of the field is just people super confidently discrediting otherwise promising/interesting directions for development for a cheap dunk!
Show me a single example how is this jev thing better than a modern Bert solution?
Or even llm if you claim about versatility. You can easily modify the llm inference code to make it predict a single token represent the classification choice and extract the probability that way.
Sure jev will still be faster, but a local deployed Bert model is way faster than both.
And to get the most out of it you still need to fine tune the models anyway, unless your classification task is just one of those mainstream ones.
I did a GRPO run (multiple now actually) with a per sample rubric that leans heavily on subjective preference judgements that BERT wouldn't have the learning capacity for: not to metion you'd need to finetune hundreds of instances and host them somewhere.
And even if BERT wasn't woefully underintelligent for the task... have 100+ instances of BERT running locally faster than Jev API response times? Sweet rig you must have...
LLMs would not be fast enough without constrained decoding tricks that people fundamentally don't seem to understand make the models much dumber, and sure wouldn't be cheaper or faster.
Again I feel this deep discomfort because presumably you're somewhat intelligent but your opening salvo made it hard not to scream DO YOU EVEN HAVE A SINGLE CLUE WHAT IT DOES instead of giving you my actual answer... yet you're speaking from the chest! If I didn't try it for myself I would have been 100% sucked into you and this ocean of clueless negativity.
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I apologize if that sounds harsh but it angers me because why should I have to deal with this kind of noise in an already insanely noisy environment? What do you gain from being cluelessly pessimistic?
And dwelling a but more I think it breaks one of my most used filters which was assuming people who know the "old world" of AI/ML are better at judging the "new world" full of hype and noise. Maybe my frustration is also just fear that things moved so quickly that the "old world" is becoming increasingly irrelevant. That'd be really disappointing.
> And even if BERT wasn't woefully underintelligent for the task... have 100+ instances of BERT running locally faster than Jev API response times? Sweet rig you must have...
why the heck do you need 100+ instances of bert. do you even attempt to research about this before?
the laya paper show that you can do the similar stuff with jev using modern bert only: https://laya.convaiinnovations.com/
and even without the newer wave of applying llm techniques to the older bert models, even flan-t5 was trained for handling 1800+ tasks.
1 reply →
Hey I am clueless, how do I learn more?
Why is Jev fundamentally better than classification models like BERT or traditional ML?
Happy to read a written response or if you suggest a prompt to put into my LLM to get it to research and explain the relevant details.
You already wrote the prompt, no? What I'd do, if I were you, is run the question through a LLM and then come back with targeted questions that it didn't answer.
I did the first part yesterday, jumped down the rabbit hole, and have 3 product ideas in my head now.
"Why is Jev fundamentally better than classification models like BERT or traditional ML?"
Please see my other reply, I was not exaggerating when I said this feels like asking why ChatGPT is different than a Markov Chain.
You're going to post-train 100s of instances of BERT? Traditional ML had world knowledge more than a fart?
The closest/fairest comparison is still an LLM, but no one has actually chucked enough compute at post-training to make a better Jev yet.
I'm sure in more time that'll happen, and so my excitement is expanded to Jev-like things... but so far most Jev like things are this weirdly reactionary attempts to steal thunder: is it so bad if we have some team actually invest in a quality post-training receipe to compete?