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I built non-autoregressive decision models with RL a year ago

1363 points · 319 comments · nandakishor_ml

prometheus1992 · 1789830629 · focus · HN ↗
I think the main gripe that people had with Jev and Typesafe was the language used when they launched. To me personally it seemed like a parody/con/shady at first.
"Breakthrough", "our research went in another direction" , "Two years in stealth", "System One thinking model", "Jev can't hallucinate", "RLCD","We are doing very cool stuff, but we will have to hire you to tell you", - these are some of the things that they said on their website on the launch blog.
I had used versions of bert to achieve the same functionality years ago. But to me it seems like they were able to trick the VCs with "can't hallucinate" etc.
To the above author, kudos for sharing your work and making it open. Something like this shouldn't be closed in the first place when it has been available for so many years
1. wild_egg · 1789830928 · focus · HN ↗
  Last time I did anything with a BERT, you had to train or fine-tune. Is that not still true?
  For me the cool bit is that it's all in-context learning or whatever so you can use it in any domain with zero setup.
  Maybe bert and co. could do all the same things before, but the way in which you use them is quite different and that helps a lot.
  1. prometheus1992 · 1789831202 · focus · HN ↗
    It depends on your usecase but the models do show general capabilities. check this model out.
    <a href="https://huggingface.co/MoritzLaurer/deberta-v3-large-zeroshot-v2.0?candidate_labels=True%2C+False&multi_class=false&text=The+request+says+the+production+service+is+currently+unavailable.%0A%0AThis+request+is+time-sensitive" rel="nofollow">https://huggingface.co/MoritzLaurer/deberta-v3-large-zerosho....
    baobabKoodaa · 1789834481 · focus · HN ↗
    So you're not even trying to defend your claim? Reminder, you said:
    > I had used versions of bert to achieve the same functionality years ago
    I remember when BERT came out. I played with it. Other people played with it. You couldn't really get it to do useful stuff, unless you put a ton of effort into it, and even then, it would BARELY do anything useful.
    The promise of Jev is that it's FRONTIER INTELLIGENCE, not the intelligence of a pre-chatGPT era model.
    If you are trying to claim that BERT is somehow on par with frontier models, that is laughably false. (Whether Jev is on par with frontier models can be questioned as well.)
    prometheus1992 · 1789835575 · focus · HN ↗
    I am not sure I understand what you're trying to say. We fine tuned bert for a specific usecase to build essentially what jev is but for that particular domain. We did this in last 2, 2.5 years ago. A lot of people did that. There are tons of bert fine tuned versions available on HF.
    >>The promise of Jev is that it's FRONTIER INTELLIGENCE,
    - capitalizing won't do much for your claim if it's wrong. Promise of Jev is it can't hallucinate, it took 2 years to develop in stealth mode, it's funded with $30 million. None of that makes sense, if you can get 90% of the performance from an open source model that's been available for years.
    [deleted] · 1789837141 · focus · HN ↗
    [deleted]

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