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Looking at the example Jev use cases, it almost feels like Jev's incredible cost/task can make it competitive as a generalized "poor man's ranking" algorithm th
by latteren 17d ago
Looking at the example Jev use cases, it almost feels like Jev's incredible cost/task can make it competitive as a generalized "poor man's ranking" algorithm that can be useful for lean startups or any fast paced development org.
I need to rank 1000 articles and pick the 5 most relevant for the user? Jev.
I need to audit and strip out content because my user is affected by regional privacy laws (without hallucinating)? Jev.
I need to surface the 3 funniest media comments that match the user's sense of humour? Jev.
- Gecko4072 17d agoWonder if this could lead to better recommendation algorithms.
- nullbio 17d agoMore like: I need to ...? -> Open-weight model. I'm sure someones working on this as we speak using an open-weight LLM base (Qwen or something would be a perfect fit). This sort of task is a perfect fit for a very small model capable of semantic parsing. You can get away with a LOT less parameters without all the autoregressive generation and long-context reasoning.
- rana3g 17d agoyou don't say - https://huggingface.co/harshatheg/Qwen-2.5-1B-RLCD https://huggingface.co/harshatheg/Qwen-2.5-1B-RLCD
- latteren 17d agoCrazy, looks like this was just published a few hours after the TypeSafe post!
- smusamashah 17d agohttps://x.com/harshagundal/status/2100044305536889015 https://x.com/harshagundal/status/2100044305536889015 tweet by the author
- DavCreator 17d agohttps://xxcancel.com/harshagundal/status/2100044305536889015 https://xxcancel.com/harshagundal/status/2100044305536889015
- deleted 17d ago[deleted]
- palash76 14d ago[dead]