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Wikipedia maintains a list of smells for LLM text.

https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing


Unlike Chrome, Firefox did not remove the older API.


What's this supposed to mean ? OP was saying that MV3 is feature-equivalent to MV2 and would like to see MV2 support removed from Firefox just as it was from Chrome. I replied pointing out that's utterly false.


MV2 and MV3 are feature equivalent on Firefox when it comes to request blocking.


quack3.exe again in a way. If it's been done for years on GPU shaders, then why not CPU code?


While highly specific optimisations might give you a tiny bit of advantage, the main boost here is vector code which would work on any processor supporting the instructions. They could have looked at the vendor bits and use those to flag for optimization in any cpu but they didn't and limited it to a small subset of programs and cpus. It tingles the "PR above all else must have highest score" sense.


Intel BOT seems to be patches for specific binaries (hence why they didn't see a difference for Geekbench 6.7), unlike BOLT/Propeller which are for arbitrary programs. The second image from their help page [1] showcases this.

[1] https://www.intel.com/content/www/us/en/support/articles/000...


Applying targeted binary patches shouldn't take 40 seconds... unless that's also a fake "so it looks like it's working really hard" delay.


I might be thinking of a different project then...

I swore Intel had their own PLO tool, but I can only find https://github.com/clearlinux/distribution/issues/2996.


Found it. It was https://www.phoronix.com/news/Intel-Thin-Layout-Optimizer.

It was open source, but has since been deprecated.


See also: Nominative determinism in hospital medicine, by orthopedics Limb, Limb, Limb and Limb

https://publishing.rcseng.ac.uk/doi/10.1308/147363515X141345...


Data tagging? 20k tok/s is at the point where I'd consider running an LLM on data from a column of a database, and these <=100 token problems provide the least chance of hallucination or stupidity.


Code blocks unreadable if the user's system reports dark mode and dark mode is toggled on for the web page.

Cool writeup. Have you had to do any other weird shenanigans with getting FFI between Rust and Clojure other than needing to use CStrings?


In Rust, wouldn't implementing BitOr for Fn/FnOnce/FnMut violate the orphan rule?


I'm envisioning that in Rust (and Python), the operator overload would be on a class/struct. It would be the macro/decorator (the same one that adds logging) which would turn the function definition into an object that implements Fn.


I have done exactly that as an exercise in what you can do with Python: overload |, and a decorator that you can use to on any function to return an instance of a callable class that calls that function and overloads |.

Whether it is a good idea to use it is another matter (it does not feel Pythonic), but it is easy to implement.


somehow this counts like model cot.


I don't think local as it stands with browsers will take off simply from the lead time (of downloading the model), but a new web API for LLMs could change that. Some standard API to communicate with the user's preferred model, abstracting over local inference (like what Chrome does with Gemini Nano (?)) and remote inference (LM Studio or calling out to a provider). This way, every site that wants a language model just has to ask the browser for it, and they'd share weights on-disk across sites.


It sounds good, but I'm not sure that in practice sites will want to "let go" of control this way, knowing that some random model can be used. Usually sites with chatbots want a lot of control over the model behaviour, and spend a lot of time working on how it answers, be it through context control, guardrails or fine tuning and base model selection. Unless everyone standardizes on a single awesome model that everyone agrees is the best for everything, which I don't see happening any time soon, I think this idea is DOA.

Now I could imagine such an API allowing to request a model from huggingface for example, and caching it long term that way, yes just like LM Studio does. But doing this based on some external resource requesting it, vs you doing it purposefully, has major security implications, not to mention not really getting around the lead time problem you mention whenever a new model is requested.


> "Open source" to me is sharing the input required [...]

I don't disagree with your sentiment, I am also more interested in human-written projects, but I'm curious about how this works. Would a new sorting network not be open source if found by a closed source searching program, like AlphaDev? Would code written with a closed source LSP (ie. Pylance) not be open source even if openly licenced? Would a program written in a closed source language like Mojo then be closed source, no matter what the author licences it under? The line between input and tool seems arbitrary at best, and I don't see what freedoms are being restricted by only releasing the generated code.


the line is blurry for shure. Code generated by a closed-source compiler (or LSP) is still 'your' code. Maybe the difference is whether humans can reproduce and learn from the process? With traditional code, you can read commit history and understand the author's thinking. With AI-generated code, that context is lost unless explicitly shared. Food for thought.


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