401 points by nigelgutzmann35 days ago | 66 comments
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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.
Chipotle uses IPSoft Amelia. Amelia is quite horrible software, a place I worked did a bake off about 10 years ago and Amelia failed so miserably it was actually funny.
We shipped a "viral" feature once that two journalists had written up before we'd even finished building it. Never shipped. Screenshots are evidence of nothing.
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.
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.
To be pedantic: linking your own profile isn't really a crime itself, just evidence. Though yeah, probably not ideal when the rest of the repo is legally questionable.
I’m not a lawyer, but Chipotle is a US company and this github repo belongs to a US citizen currently residing and employed in New York, so US law might apply here.
There was a really great, really underrated show on Peacock a few years ago called Mrs. Davis. The titular Mrs. Davis was an all-encompassing AI assistant that had taken over all of the governments of the world. Everyone wore a Whispering Earring-style earbud with a voice that guided them through their lives and made every decision for them. (Betty Gilpin plays a nun who's simultaneously rebelling against the AI and searching for the Holy Grail on its behalf.)
In the show the AI had originally started as (spoiler, but not really) the customer support bot for Buffalo Wild Wings. I don't know what to do with this.
I thought it was fantastic show too. It was made in part by Damon Lindelof, who is kinda an auteur of sorts in the prestige TV world (for better and worse), probably most notably for Lost. But for those who know: he is the guy that did The Leftovers.
Mrs. Davis is its own really colorful and rich and funny thing though, more akin imo to other 1-season gems like I'm a Virgo or Maniac where I am more glad it stopped where it did rather than continue and become bad.
They knew what they were making and went exactly hard enough to sustain 8 episodes without feeling rushed or dragging.
It’s one of the few shows that reaches a satisfying conclusion, ties up the loose ends, the hero rides off into the sunset, and it just ends. There’s no setting up a season 2 that never got made.
Mrs. Davis is absolutely worth it. The writers clearly thought deeply about alignment and human-AI dependency in ways Silicon Valley never touched. Funnier too, but it earns it.
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 :)
The burrito analogy is strained. A monad is a design pattern for sequencing computations, not a memory model. Calling it "leaky" confuses abstraction layers — the nondeterminism and the forgetting are separate concerns.
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 have a personal, fully offline and local version of Windows Recall basically, but good, made using macOS built-in OCR and LLM. The reasoning requirements are tiny (just interpret the screen based on the OCR, do rolling de-duplication and summarization), but they are non-zero. The tool is valuable to me and it being dep-free and fully offline and local just gives me a good feeling.
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.
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.
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.
Resource-seeking as a convergent instrumental goal shows up a lot in alignment literature. What's described here would be a fairly literal instantiation of those concerns, not just a thought experiment.
There's also Horde or Koboldai.net or Koboldai.com or whatever their project is named, if you want a community-driven version of this. You can play with it via a WebGUI at https://lite.kobaldai.net, or with an API token of all zeroes. (Or, an actual API key associated with your user.)
> The AI Horde is a service that generates text using crowdsourced GPUs run by independent volunteer workers.
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.
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.
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.
As someone who was forced to use Ask Pepper last time I had a problem with Chipotle, good riddance. Apparently too many people were tricking it into giving refunds, so the best it is allowed to do is hand out coupons for "free guac" that expire in a month, even if your order was missing items.
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.
Has anyone tested whether the model consistency actually degrades mid-session when it silently switches providers? Curious if the persona holds or if you get jarring tone shifts.
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.