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jev is insane 🤯 here is jev playing smash bros against itself he is controlling all 4 different characters. and literally deciding whats the best move to play against itself all within a fraction of a second i used over 22 million tokens to play this match and it...

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Mau Baron

19,736 subscribers

201,781 просмотров • 21 часов назад •via X (Twitter)

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Комментарии: 17

Фото профиля Lex Builds
Lex Builds15 часов назад

how do you structure the "game state" in order to input it to Jev?

Фото профиля Open Book
Open Book17 часов назад

@grok what is a "jev"

Фото профиля Fab
Fab14 часов назад

Wow! Very cool use. Can you beat our benchmark tho?

Фото профиля Future Brian
Future Brian13 часов назад

imagine fox only, final destination. Ironically you could achieve this same look by setting up 4 level 6 CPUs hahahaha

Фото профиля Ernesto Lopez
Ernesto Lopez21 часов назад

wtf...🤯

Фото профиля Mau Baron
Mau Baron21 часов назад

bro ik hahaha

Фото профиля Kariminal
Kariminal18 часов назад

Smash ultimate too!

Фото профиля Robin | Poker x AI
Robin | Poker x AI12 часов назад

Seeing a LLM handle frame level Smash decisions in real time is wild, especially at a few cents per match

Фото профиля sss
sss14 часов назад

why all fox man

Фото профиля Monta 🦀
Monta 🦀16 часов назад

they only know how to nair?

Фото профиля chosem 😖
chosem 😖15 часов назад

mf better than me

Фото профиля Jeff | shade.ron
Jeff | shade.ron13 часов назад

why does it like nair so much lol

Фото профиля lithium534
lithium53412 часов назад

I still don't understand this model very well. It feels like a lookup table on steroids. What is the prompt you have it?

Фото профиля ByooNg
ByooNg13 часов назад

Jev would have a really good techchase

Фото профиля JQUAVE
JQUAVE16 часов назад

whats the harness around this?

Фото профиля 0xthw7
0xthw713 часов назад

most b2c AI apps like CalAI never needed LLMs, they needed small general-purpose classifiers that makes embed intelligent decisions in code super fast (how many calories in this food pic?), big deal for cutting the AI cost from their bottom line

Фото профиля 0x5uZ 🍙
0x5uZ 🍙14 часов назад

is this open source?

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jev is insane 🤯 Here is Jev playing subway surfers at super human speed, and also playing 50 games at once. cost less than a cent to do this run. Jev does not replace llms like astra or fable, but opens up an entirely new world of capabilities.
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jev is insane 🤯 Here is Jev playing subway surfers at super human speed, and also playing 50 games at once. cost less than a cent to do this run. Jev does not replace llms like astra or fable, but opens up an entirely new world of capabilities.

Max Blade

248,773 просмотров • 1 день назад

Jev VS Fable 5.1 VS GPT-6 Astra: chess typesafe's new Jev V13 isn't an LLM. it doesn't chat, doesn't explain, doesn't write code — it only makes decisions. so we made it play blitz against frontier LLMs. the test: 5+0 blitz. every move is one API call. Jev V13 vs Fable 5.1: • fable outplayed it. by move 29 it was +16 in material and even promoted a second queen • but it kept burning 6-15 seconds per move on analysis. jev answered in ~2.6s • so fable didn't have enough time and lost Jev V13 vs Astra: • astra didn't bother winning on material. it mated jev in 18 moves. Qe1#, with 2:27 to spare
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Jev VS Fable 5.1 VS GPT-6 Astra: chess typesafe's new Jev V13 isn't an LLM. it doesn't chat, doesn't explain, doesn't write code — it only makes decisions. so we made it play blitz against frontier LLMs. the test: 5+0 blitz. every move is one API call. Jev V13 vs Fable 5.1: • fable outplayed it. by move 29 it was +16 in material and even promoted a second queen • but it kept burning 6-15 seconds per move on analysis. jev answered in ~2.6s • so fable didn't have enough time and lost Jev V13 vs Astra: • astra didn't bother winning on material. it mated jev in 18 moves. Qe1#, with 2:27 to spare

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524,445 просмотров • 1 день назад

Also have been playing with TypeSafe AI Jev, insane! So many immediate use cases and new apps are possible. What a time to be a builder! Sharing some experiments here starting with: Keystroke oracle / predictive launcher: Your launcher ranks by aliases, fuzzy match, and habit. Jev reads intent: type "the pdf I just downloaded" and the newest PDF is already the top hit with a full confidence on every keystroke, in ~100 ms
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319,702 просмотров • 20 часов назад

Wow, TypeSafe AI Jev is a game changer for voice-driven UI. Responsiveness really matters for an experience to 'feel' right, and this certainly does the job! Latency here is not optimal given I'm in London and calling out to us-west. But still, super snappy. In this video, Jamcat is using Pipecat to orchestrate a real-time handover between a command agent (Jev) that drives the UI, and voice agent (PhoneLLM) for handling generations and (not in the video) discussing ideas and session setup with the user.
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Jon Taylor

26,440 просмотров • 21 часов назад

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Jev is INSANE. 🤯 in 24.9 seconds it read 384 news from this morning and told 15 brands which stories to hop onto today, for $0.19. Claude Opus 5, running on the same feed at the same time, got through 4/384 and cost $0.77. per headline that is ~390x cheaper, and the answer comes back before you finish reading the headline yourself. there's going to be so many ways for JEV to help you find trending stories, find journalists covering it, and get press coverage. everything in the video open-sourced here: (in the demo/ folder, together with 30+ skills to turn your agent into a PR team)
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166,490 просмотров • 7 часов назад

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