Moritz Kremb ✓
@moritzkremb · Community → · joined 06 Feb 2019
I tinker with AI and share what I learn along the way | German, Engineer, Ex-PM, now helping businesses master AI | Free resources→ https://t.co/M4zkbzIBlc
72 147Followers
670Following
10 107Posts total
6.8MViews on collected posts
Derniers posts
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All of the coolest Jev projects I could find on X today 🧵 https://t.co/2QUxMRM4pm
20.9K views · 265 likes
· 14 reposts · 14 replies
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Jev gave me $5 of API credit when i signed up
when i die, i will pass what's left of it to my son
101.3K views · 4.2K likes
· 161 reposts · 104 replies
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@moritzkremb @typesafeai Someone should make a site of Jev use cases and examples.
1.2K views · 3 likes
· 0 reposts · 1 replies
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Full Jev Tutorial
What it is, how you can build with it and what new applications it can unlock
→ 0:00 Intro
→ 0:34 Jev explained
→ 4:06 API setup
→ 5:59 Demo 1: Voice-controlled browser
→ 11:33 Demo 2: AI memory
→ 17:27 Demo 3: YouTube predictor https://t.co/V7iK3jZTLZ
64.6K views · 1.2K likes
· 124 reposts · 24 replies
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22:41
whoa this actually worked! Jev lets me control my browser in real time with my voice now
> i talk
> transcript sent to Jev
> jev returns probabilities in ~300ms
> browser clicks
costs: $0.0002 per decision
i'm stunned how fast this is. when i asked it to "go back", it even htt
186.4K views · 2.8K likes
· 134 reposts · 82 replies
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0:39
I'll be testing Jev extensively this week and figuring out how exactly this new technology can be used in my business
sharing all my learnings here
join my newsletter for more
https://t.co/bFMVFbldGF
4.3K views · 7 likes
· 0 reposts · 1 replies
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Example 3: Browser Use
https://t.co/59a2feK8jp
8.3K views · 7 likes
· 2 reposts · 1 replies
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Example 2: Trading Bot
https://t.co/dipkbcOcQc
9.2K views · 8 likes
· 1 reposts · 1 replies
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Example 1: Rebuilding Tesla Self Driving
https://t.co/u2nMllEd30
11K views · 10 likes
· 2 reposts · 1 replies
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If you still don't understand what Jev by @typesafeai is, I put together this thread for you 🧵
It has all of the best explanations and examples I could find on X
https://t.co/V4PP5YUY80
152.9K views · 537 likes
· 46 reposts · 16 replies
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Prediction: millionaires will be made using custom Jev style models (parallel constrained decoding) to make the agent systems companies already run more token efficient.
Let me explain with a scenario:
Imagine a company already has an agent workflow running where an llm reviews
181.8K views · 1.4K likes
· 81 reposts · 33 replies
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Breaking: Browser Use + Jev = Ultrafast ⚡
Findings flights took 7s and cost only $0.0039 🤯
> new action space every step
> DOM state space
> small LLM fallback to type
(this video is at 1x speed btw)
Built a tiny open source browser agent. try it below ↓ https://t.co/AplCBRYC
2.2M views · 7.9K likes
· 542 reposts · 232 replies
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0:07
I built a trading bot with Jev!
Jev decides if it should "buy" or "sell", given the price feed of an asset pair, and executes real trades.
It uses Monad to place the orders on Kuru's on-chain order book in every 300ms block.
Demo link → https://t.co/vwl2SUu4jm https://t.co/Sda
973.4K views · 4.6K likes
· 188 reposts · 256 replies
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0:10
I rebuilt Tesla Full Self Driving with Jev in less than an hour.
This model is a total unlock. https://t.co/mUrvaFrlQ7
508.8K views · 4.4K likes
· 245 reposts · 206 replies
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1:59
Here's a 45-second TL;DR on Jev.
I find the core idea beautifully simple, but the video made it really hard to understand.
Hope you find it helpful. https://t.co/KtSKlEMVL3
1.3M views · 8.5K likes
· 604 reposts · 192 replies
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0:46
this is the easiest way to understand Jev:
LLMs generate answers.
Jev makes decisions.
that sounds like a small difference, but it actually changes the entire use case.
say you give a normal LLM this:
“here’s a user, their account history, payment behavior, support chats,
318.7K views · 2.3K likes
· 138 reposts · 82 replies
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hype-free explanation of jev:
jev does not replace gpt / claude
jev is just a *really* smart switch statement
like if 2016 ml classifiers got 2026 levels of intelligence
it's a new* type of tool that will make a lot of workloads insanely fast, cheap, and accurate
* = and by
645.5K views · 7.4K likes
· 400 reposts · 227 replies
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Face aux comptes de taille comparable
23 posts des 90 derniers jours, à côté de la tranche de 10K–100K abonnés. diffusé largement, mais peu de ces spectateurs réagissent.
Vues médianes20 891ce compte927médiane pour 10K–100K
Portée, %28.96%ce compte3.40%médiane pour 10K–100K
Engagement, %0.40%ce compte1.54%médiane pour 10K–100K
| Indicateur | Ce compte | Médiane pour 10K–100K | Rapport |
|---|---|---|---|
| Vues médianes par post | 20 891 | 927 | 22.5× |
| Portée (vues ÷ abonnés) | 28.96% | 3.40% | 8.52× |
| Taux d'engagement | 0.40% | 1.54% | 0.26× |
Autres comptes de cette tranche → Comparer avec un autre compte → Comment ces repères sont établis →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
15.1K17 Sep
14K
12.8K
11K
9.2K
8.3K
4.3K
186.4K
64.6K
1.2K18 Sep
101.3K
2K
1.4K
20.9K
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.09%17 Sep
0.04%
0.05%
0.12%
0.11%
0.12%
0.19%
1.64%
2.05%
0.33%18 Sep
4.46%
0.15%
0.50%
1.42%
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.54%.
What the audience does
Likes51.5%45 521 in total
Reposts3.0%2 689 in total
Replies1.7%1 477 in total
Quotes1.0%915 in total
Bookmarks42.8%37 808 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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