At this point, I am finding it extremely hard to believe that Jev team is not on a massive astroturfing campaign. This is happening all over reddit too. All LLM subreddits are getting flooded by Jev posts, many of which are made by new accounts that only talk about Jev, many obviously advertising in guide of sharing knowledge (e.g. https://www.reddit.com/r/LocalLLaMA/comments/1wn4cni/removed...)
Multiple posts on HN, including this one, are from accounts that only ever talked about Jev. Each get unusually high number of upvotes early on, enough to put them on frontpage. A multitude of commenters on such posts also seem to talk about only 1 topic.
Can all this happen organically? Yes but with vanishingly low probability, from my vantage point.
Initial personal use case (on my side project https://mealplannr.io/lists) is lists have a "smart categorise" button to group items into 20 or so preset lists.
Previously this took up to ~30-60 seconds using deepseek v4 flash (even with a medium list size) - Jev is <1 second @ same cost with typesafe guarantee
As a bonus I can also instantly categorise new items - rather than sending them into an "unknown" category (and waiting for user to have to click "categorise" again)
https://x.com/dWeaths/status/2102415625301717065 - Here's my use case of jev, being able to accurately detect nouns (with adverbs, adjectives etc.) in realtime as the user is typing it, genuinely feels like it's running locally with how fast it comes back. I've sent over 1000 requests to Jev and its cost me $0.01 (probably rounded up!).
I had an idea for a 'write without space, basicallylikethis' and Jev (given how cheap it is) just being asked after every key press where inserting spaces (or making typo correction) would make sense.
Honestly just getting it integrated into mobile phone swipe keyboards would be a godsend. If I type "We need to get going " and then swipe the word "now", I really do not think "mower" should be the word it chooses. Present a set of swipe-based likely words and the preceding text message to Jev, or similar model, and pick its highest prob word.
i built wellposed as a plugin/skill which works with any agent (https://github.com/suraj-phanindra/wellposed) to ensure your agent understands how to choose the right kind of jev request and format it correctly not just for syntax but for completeness and correctness. it is well-documented in the "jagged-ness" docs (https://docs.typesafe.ai/model-jaggedness/jev-1.13) that typesafe include on their docs page that the absence of essential options can cause jev to choose the wrong option with high confidence (it cannot choose what it cannot see in the request) - so the responsibility to ensure whatever the intent behind your jev request is - it is captured correctly with the right states and options for jev to pick from falls on the user. wellposed should ideally make your agent better at converting NL intent into jev requests. please try and give me feedback. appreciate it!
Don't want to be a conspiracy theorist, but these past two weeks have seen what looks to be a coordinated campaign to boost Jev. Am I out of the loop or is this so revolutionary it warrants getting so much coverage on HN and other professional sites?
It's definitely revolutionary, considering AI news is ~50% of the front page at any given time, and the frontier models are all pretty much doing the same thing and just getting slightly better. This is a whole different technology, it's cheap and fast, and it's usefulness at different tasks is still being established. Amazing for hackers!
At this point, I am finding it extremely hard to believe that Jev team is not on a massive astroturfing campaign. This is happening all over reddit too. All LLM subreddits are getting flooded by Jev posts, many of which are made by new accounts that only talk about Jev, many obviously advertising in guide of sharing knowledge (e.g. https://www.reddit.com/r/LocalLLaMA/comments/1wn4cni/removed...)
Multiple posts on HN, including this one, are from accounts that only ever talked about Jev. Each get unusually high number of upvotes early on, enough to put them on frontpage. A multitude of commenters on such posts also seem to talk about only 1 topic.
Can all this happen organically? Yes but with vanishingly low probability, from my vantage point.
Initial personal use case (on my side project https://mealplannr.io/lists) is lists have a "smart categorise" button to group items into 20 or so preset lists.
Previously this took up to ~30-60 seconds using deepseek v4 flash (even with a medium list size) - Jev is <1 second @ same cost with typesafe guarantee
As a bonus I can also instantly categorise new items - rather than sending them into an "unknown" category (and waiting for user to have to click "categorise" again)
https://x.com/dWeaths/status/2102415625301717065 - Here's my use case of jev, being able to accurately detect nouns (with adverbs, adjectives etc.) in realtime as the user is typing it, genuinely feels like it's running locally with how fast it comes back. I've sent over 1000 requests to Jev and its cost me $0.01 (probably rounded up!).
I had an idea for a 'write without space, basicallylikethis' and Jev (given how cheap it is) just being asked after every key press where inserting spaces (or making typo correction) would make sense.
The demo is here: https://levmiseri.com/nospace
This one is cool as hell
And so, I typed "Thisoneiscoolashell", and got "This one is cool a shell" hahaha
Great idea, and it's really quick
Thanks! Made some updates to it to strengthen the corrections/splits. Should work substantially better now.
Honestly just getting it integrated into mobile phone swipe keyboards would be a godsend. If I type "We need to get going " and then swipe the word "now", I really do not think "mower" should be the word it chooses. Present a set of swipe-based likely words and the preceding text message to Jev, or similar model, and pick its highest prob word.
i built wellposed as a plugin/skill which works with any agent (https://github.com/suraj-phanindra/wellposed) to ensure your agent understands how to choose the right kind of jev request and format it correctly not just for syntax but for completeness and correctness. it is well-documented in the "jagged-ness" docs (https://docs.typesafe.ai/model-jaggedness/jev-1.13) that typesafe include on their docs page that the absence of essential options can cause jev to choose the wrong option with high confidence (it cannot choose what it cannot see in the request) - so the responsibility to ensure whatever the intent behind your jev request is - it is captured correctly with the right states and options for jev to pick from falls on the user. wellposed should ideally make your agent better at converting NL intent into jev requests. please try and give me feedback. appreciate it!
Don't want to be a conspiracy theorist, but these past two weeks have seen what looks to be a coordinated campaign to boost Jev. Am I out of the loop or is this so revolutionary it warrants getting so much coverage on HN and other professional sites?
It's definitely revolutionary, considering AI news is ~50% of the front page at any given time, and the frontier models are all pretty much doing the same thing and just getting slightly better. This is a whole different technology, it's cheap and fast, and it's usefulness at different tasks is still being established. Amazing for hackers!
Chrome extension to filter Twitter posts for AI slop, promotions, or based on custom rules - https://chromewebstore.google.com/detail/clean-twitter/oflan...
https://github.com/midplane/clean-twitter
I built hn4me.xyz - Hacker News stories curated by Jev based on your interests
Demo here: https://x.com/RaahelSaidWhat/status/2102162969656475973
Did anyone do prompt injection detection?
marketing blitz in progress
"Stop trying to make" Jev "happen, it's not going to happen!"
"has_happened": { "type": "noul", "noul": 0.96 }