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…Right? Completely. Like I'm, I, I, I love code. I don't like typing into a text editor that's not funded. I wanna recognize Alex also the creator, copilot and Alex, have you have played with code yet? Thanks. Yeah, I, I'm just here to listen. I played with it a little bit. I think it's very promising. I think the, the process that you're describing that people are, who are, have been using it more actively or describing that's like, it's like the most valuable training data in the entire world is like you know, because before you know, when you would generate some code with either Codex or with or whatever open, I didn't know if the code worked, whereas now you're, they're, they're getting signals from that because they're trying to run it and they're critiquing it and then regenerating it, and then you, maybe you're critiquing it. So like the end result is that they're going to get way, way, way better at writing code. So I think it's very interesting. Yeah, definitely. I wanna get to some folks, Gabriel and then Carl. Hey just wanted to update on something that we had discussed earlier regarding context window for code interpreter. So I just tested it out and code interpreter has AK context window same as the plug-in model, and same as G chatt three five. Do, do you mind sharing the, the technique, how you measured it? Oh, just, you know, grab the piece of text that's, you know, measured the tokens with the open ai token and, and just played around with some different lengths and right around the AK mark. You know, just above eight K it fails. It just tells you it's too much when you paste it in and, and try to get an answer. And under eight k it works. So for the plug-in model for for the code interpreter and for chat gpt 3.5 all of them have an eight K context window chat, GPT4 default has a 4K context window. Awesome, thanks. Thanks for the update. This is a great update. for for the code interpreter and for chat gpt 3.5 all of them have an eight K context window chat, GPT4 default has a 4K context window. Awesome, thanks. Thanks for the update. This is a great update. I wanna hear from Carl next. Hey, Carl, what's your code interpreter use case? What have you used it for? Let us know. Carl, you have a hand up? Yeah. How about chaps? Yeah, loving the, the spaces that you, Alex and Swix are hosting recently. It's amazing and it's it's wonderful hearing all of the all of the little hacks and workarounds and everything you guys do, and the people on the, on the stage have been doing with like context windows and memory management and stuff. It's making me very jealous. Far beyond what found the time to do. I haven't played directly with Code interpreter yet, but more about sort of what you were saying with feature requests or ideas or potential things down the pipeline. I know that Ben talks about how this would be implemented in an api, how that would even work as an API for certain things. Because a lot of the benefit of what Code interpreter seems to give you back is the magic of the open AI ui, right? Like it can render graphs, it can render sort of statistical graphical sort of results and stuff like that, and charts and everything else. And that's difficult to potentially utilize to its full extent if you're coming across from an api. So my thing that actually that. I don't even know if code interpreter would be useful for this, but I have seen a lot of image processing people points where people have been using sort of gpt for the window where they've been able to, especially when sort of like the plugins were more enabled and the internet access was sort of more working a little bit better where image captioning and image passing and stuff like that. But as of yet that I've seen, there still isn't a really fully supported fluid way to be able to do anything like that via any of their APIs. So via sort of like the, the completion endpoint or, or the chat endpoint or anything like that. And that's sort of a thing that we are focusing on at the moment. The company I work with we do a lot of sort of media handling and everything, and we've currently got a system in place that can index through. An enterprise clients content across multiple platforms and be able to cut it up into scenes, detect all the scenes and everything else, and then detect all the, the content and the context of what's happening in each scene. So you end up with this super, super powerful sort of content management system, enterprise level content management system that allows you to search all of your footage and all of your scenes via nlp, which is super, super, super exciting. A lot of people interested. Now, at the moment we're using Salesforce split models because it does a, a re, it does a good enough image captioning like a description and processing of the images. But, you know, open AI just seems to, whenever they put their minds to these things, they just seem to knock it outta the park. It just seems to be the embeddings just seem to be faster, cheaper, you know, harder, stronger, all of the other d punks sort of adjectives.…

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