Everyone is Getting Jev WRONG

There's a lot of buzz going on around Jev right now and almost everyone's getting it completely wrong. So hopefully we can just break it down to why you would want to use why this model is so exciting and what practical use cases you could actually use with this model. My name is Jeff Command AI. After co-inventing chat GBT, I kept asking myself why have superhuman chat models has not led to AG. I spent the last 2 years in stealth building a new way to train models RLCD and a new type of frontier model that we are releasing today called Jev. 20 to 200 times faster, 40 to 400 times cheaper with output tokens being free and Frontier Composible Intelligence optimized for decisions. 042 uh per million tokens in and then output tokens are free because they're too cheap to meter with how uh with their new architecture. But Jev is named after Jeban's paradox. You know what that is? So they're going to release two models, right? System system one and system two, which is this idea that your brain has two systems. It's from a book called thinking fast and slow. System one is like your immediate gut instinct feeling. No, no thought, no anything. It's not a thinking model, right? And this first release is about the system one thinking. They're going to be releasing uh a system two thinking thinking one which does do that secondary level of thought and intelligence. What is a type safe model? So remember I said it out outputs JSON. Yeah, you can ask it to like respond in the JSON in the type that you want it. Whether it's an enum, whether it's a string, whether it's a um you know a URL or whatever, like it it returns, this is my understanding. I'm not an expert. I'm not an expert at Jev, but my understanding of type safety is when you actually say this is a string and that thing can only ever be a string, you know. So it's very it's and this is the key word it's as deterministic as you could possibly get with an AI using Jev when you talk about type safety you're saying I want a string it will give you back a string that's deterministic so that's what it means here I've seen people build UIs with Jev and it's not really demonstrating what Jev is an assessment model it's a it calculates and and um compares is data as opposed to a generative model which produces tokens and outputs what output stuff this outputs but it's it's a way of taking a subset two sets of data or or a set of data a set of predetermined outputs and comparing and reasoning about what the return data should be. So, this could be a huge database of things where you want to um tag give me all of the it's an advanced filtering system like give me all of the items that are tagged with the color yellow or something like this. You know, a practical example of this might be what we spoke about with, you know, um Reloom's AI or Web Flow's AI, right? They're not they're not really generating stuff out of the box like Reeloom's AI is a perfect example cuz they have all of their components. And what their system does, their little builder does, it generates pages, wireframes for for you based on their component library that is in of itself based on deep user experience, research and design fundamentals, right? So they have a subset already of these components. Now, Jev would be perfect for them and much cheaper and much faster if they say, "Take this user's response and generate a page that uses the best, you know, or most um sensible components uh based on their request basically." And that would be a great use case for for using Jev. It's not a new it's not a thinking model. It's not it's not doing any sort of it's not producing facts or or things from nothing. It it's literally it needs data to work well. So that's why this is quite exciting and and as I say deterministic is the key word there because this is as deterministic as you could probably get with an AI. So that's kind of Jev in a nutshell. And it does sound a bit boring to us creative folk because it's not really doing anything. It's mostly from a data like organization standpoint, but it's a it's an interesting progression and it's uh again things being deterministic is is always a win. This is part of a larger conversation on my show Command AI which we stream live every single week. We discuss the news and all things related to AI in the world of design and web. Catch us next week and join in the banter. Command AI.