1. openrouter is API usage. There is obviously consumer side
2. people often use openrouter for the sole purpose of using a unified chat completions API
3. OpenAI invented chat completions; if you use openrouter for chat completions often you can just switch your endpoint URL to point to the OAI endpoint to avoid the openrouter surcharge!
4. Hence anyone with large enough volume will very likely not use openrouter for OpenAI; there is an active incentive to take the easy route of changing the endpoint URL to OAI’s
Schemas can get pretty complex (and LLMs might not be the best at counting). Also schemas are sometimes the first way to guard against the stochasticity of LLMs.
Post-training doesn't transfer over when a new base model arrives so anyone who adopted a task-specific LLM gets burned when a new generational advance comes out.
Obviously we're just dueling anecdotes here, but FWIW, I'm a US tech worker who bought a Tesla in 2022 and certainly never will again. I have four friends with Teslas in tech and all of them say the same thing: never again. Replacement cycles for cars are so long that this will take a while to fully show up in the data, but I don't see growth anywhere in their future, especially when BYD is eating their lunch in seemingly every non-US market.
Sure never again is totally fair and I am sure a lot of people hate it. I was mostly objecting to the radioactivity of it. Your friends will be more like “I am looking to sell my Tesla in 3 months” if it is truly radioactive.
Unfortunately, Tesla resale values have also plummeted, so even if people wanted to sell them desperately it may not be a financially sensible decision.
Personally, as a Tesla owner I'm concerned that if my car gets totalled I'll get pretty lowballed on the insurance settlement.
> Personally, as a Tesla owner I'm concerned that if my car gets totalled I'll get pretty lowballed on the insurance settlement.
The kinda obvious answer there is to use your insurance settlement to buy another highly-depreciated Tesla. Insurance settlements are intended to let you get a comparable replacement as determined by market value. (The alternative is that if your Tesla gets totalled, it's a get-out-of-jail-free card to get a non-Tesla.)
> And if for some ungodly reason you had to do it in Python
I literally invoke sglang and vllm in Python. You are supposed to (if not using them over-the-network) use the two fastest inference engines there is via Python.
I work in this space. In traditional diffusion-based regimes (paired image and text), one can absolutely check the text to remove all occurrences of Indiana Jones. Likewise, Adobe Stock has content moderation that ensures (up to human moderation limit) no dirty content. It is a world without Indiana Jones to the model
I don't know the data distribution, but are you sure that's generated by an Adobe model? I can only see that it is in Stock + it is tagged as AI generated (that is, was that image generated by some other model?)
Disclaimer: I used to work at Adobe GenAI. Opinions are of my own ofc.
Yeah, there's no way Indiana Jones was not in the training data that created that image. To even say it's not in there is James Clapper in front of Congress level lying.
> one can absolutely check the text to remove all occurrences of Indiana Jones
How do you handle this kind of prompt:
“Generate an image of a daring, whip-wielding archaeologist and adventurer, wearing a fedora hat and leather jacket. Here's some back-story about him: With a sharp wit and a knack for languages, he travels the globe in search of ancient artifacts, often racing against rival treasure hunters and battling supernatural forces. His adventures are filled with narrow escapes, booby traps, and encounters with historical and mythical relics. He’s equally at home in a university lecture hall as he is in a jungle temple or a desert ruin, blending academic expertise with fearless action. His journey is as much about uncovering history’s secrets as it is about confronting his own fears and personal demons.”
Try copy-pasting it in any image generation model. It looks awfully like Indiana Jones for all my attempts, yet I've not referenced Indiana Jones even once!
My personal mantra (that I myself cannot uphold 100%) is that every dev should at least do the exercise of implementing binary search from scratch in a language with arbitrary-precision integers (e.g., Python) once in a while. It is the best exercise in invariant-based thinking, useful for software correctness at large
Yes, it's a simple enough algorithm to be a good basic exercise---most people come up with binary search on their own spontaneously when looking a word up in dictionary.
each text token is often subword unit, but in VLMs the visual tokens are in semantic space. Semantic space obviously compresses much more than subword slices.
2. people often use openrouter for the sole purpose of using a unified chat completions API
3. OpenAI invented chat completions; if you use openrouter for chat completions often you can just switch your endpoint URL to point to the OAI endpoint to avoid the openrouter surcharge!
4. Hence anyone with large enough volume will very likely not use openrouter for OpenAI; there is an active incentive to take the easy route of changing the endpoint URL to OAI’s
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