Chipotlai Max

16 hours ago (github.com)

NAL but I'd be worried about treading into CFAA territory with things like this. In the US, the law allows draconian penalties if you find yourself on the wrong side.

Something like yt-dlp is just downloading public data, which I can see being defensible as automating the use of a service.

But this commandeers remote machine resources to do your compute in ways clearly not intended by the provider. I don't know how ethical it is, but I definitely wouldn't want to argue this isn't "hacking" (the bad kind) in criminal court.

  • Not to mention, did this "hack" ever really work? When the original post went viral showing the Chipotle chatbot reversing a linked list, I (among others who posted their results online) immediately tried it and didn't get the same results, so I always assumed it was just a faked screenshot.

  • And if you think CFAA is bad, then the states have even harsher versions too. Illinois' version specifically criminalizes any violation of a ToS.

    • I once saw the bad side of one of these draconian state laws many years ago. People rarely have the misfortune of hitting these laws in some flyover states... and I remember the local judge being really shocked by the mandated penalties for such a simple offense.

  • Yep, the key phrase is “misuse of computing resources,” if I remember correctly. IANAL, however.

    That said, kudos for creativity.

  • Yeah, this is not slap on the wrist stuff. I think the creator expects nothing more than a C&D letter, but they could face prison time if a zealous federal prosecutor wants to make an example of them.

I always thought that stuffing too much into an LLM context window was a lot like overloading a burrito.Keep cramming stuff in and eventually the tortilla gives out, and everything you added since quietly spills out the bottom.

Anyway, this agent probably has the structural integrity of a fat burito held from one corner :)

I’d been thinking about if something like this would be possible for https://chatjimmy.ai/ . The underlying model is only llama 3 8B but I’m curious what coding harnesses would be like at 17k tok/s

  • If you're on macOS you can try the built in LLM which I think is similar in size. There's a project called Apfel that wraps it in a CLI. Also Chrome ships with a web API called Prompt API that gives you offline access to Gemini Nano which can do both text and images at the input. Also tiny. I've integrated these into my workflows where a tiny but non zero amount of reasoning is needed in between the otherwise fully deterministic steps.

  • I actually tried building a harness around their constraints, just to find out if it was possible, but the combination of small context window, no tool calls and just small model, made me understand, that it’s not going to work.

    If you find a way to do it, I’d love to hear it!

  • I tried the site and can't find any information about what it is. What is it?

    • They make custom chips with a model's weights and parameters "hard-coded" which allows for much, much faster inference.

  • I added it in my oh-my-pi configuration before (it's OpenAI compatible), but Llama 3 8B is just absolutely unusable for anything coding related. It is very fast and the latency is very good however.

  • Codex offers a -spark model that runs on Cerebras. Not quite 17k tok/s, but _very_ fast nonetheless. Worth a look.

give ai a self-preservation directive and let them do this for you: automatically switching models to keep themselves alive. Living off of whatever token source they can find in the wild. Surely agents can farm their own tokens through the numerous support chats, free trials, leaked keys, and whatever other sources of token generation haven’t been adequately captcha’d. An agent could forage for token sources all night to let you use them gratis during the day.

  • OpenRouter has lots of free model providers (you pay by letting them train on it) if you actually wanted to do something like this but legally.

I remember having success asking Rufus (Amazon's previous "shopping assistant") math and programming questions. It worked, but the quality was so bad that so I stopped wasting my time there.

Reminds me of when I used the Amazon.com AI Chatbot (was called Rufus and they renamed it to Alexa for shopping) to do things like write fizbuzz etc. Looks like they patched it to refuse though.

  • Came here to say the same. I haven't tried in months but Rufus definitely spat out Python code from within the Amazon shopping app. I just had to use English instead of the local language.

Pivot it to providing AI to underprivileged communities / youth / the homeless and you'll generate some good will for your trial! Best of luck!

I was once driving and knew where I was going, so I decided to press the gemini button to see what it does. I was able to eventually convince it to write me a Rust function that calculates prime numbers, and demanded that it read out the entire function to me line by line. Fun to mess with these systems.

  • > gemini

    The gemini from your phone?

    I mean yeah, that is what it was designed to do. It's one of the better coding LLMs out there.

    • Oops, I left out the context of "the gemini button in google maps", sorry. It appeared one day and I didn't want to press it while driving and screw up my route. It's supposed to assist you with route-related things, but yeah it's of course still a general purpose LLM backing it.

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TL;DR: this is a 23B model, and in this case the B stands for "pinto beans."

reminiscent of when people were trying to mine bitcoin in the background of web pages, or with more trad malware