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They have an interesting regex for detecting negative sentiment in users prompt which is then logged (explicit content): https://github.com/chatgptprojects/claude-code/blob/642c7f94... I guess these words are to be avoided...
They have an interesting regex for detecting negative sentiment in users prompt which is then logged (explicit content): https://github.com/chatgptprojects/claude-code/blob/642c7f94... I guess these words are to be avoided...
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Absolutely no AI company is trying to take up this banner. Examples of Claude being used in all kinds of nefarious ways are surfacing all the time, and all those human operators are still current customers. Anthropic has very little to say on the matter.
The idea that Anthropic is a "safety" brand suggests that AI companies operate in a much lower realm of morality.
Earlier quoted context omitted.
You're perfectly free to scrape the web yourself and train your own model. You're not free to let Anthropic do that work for you, because they don't want you to, because it cost them a lot of time and money and secret sauce presumably filtering it for quality and other stuff. Stole? Courts have ruled it's transformative, and it very obviously is. AI doomerism is exhausting, and I don't even use AI that much, it's jus…
Let's talk ethics, not law. Why is it okay for these companies to pirate books and scrape the entire web and offer synthesized summaries of all of it, lowering traffic and revenue for countless websites and professions of experts, but it is not okay for others to try to do the same to an AI model? Is the work of others less valid than the work of a model?
And everyone is free to consume all the free information.
They have an interesting regex for detecting negative sentiment in users prompt which is then logged (explicit content): https://github.com/chatgptprojects/claude-code/blob/642c7f94... I guess these words are to be avoided...
Earlier quoted context omitted.
It's fast, but it'll miss a ton of cases. This feels like it would be better served by a prompt instruction, or an additional tiny neural network. And some of the entries are too short and will create false positives. It'll match the word "offset" ("ffs"), for example. EDIT: no it won't, I missed the \b. Still sounds weird to me.
It’s fast and it matches 80% of the cases. There’s no point in overengineering it.
I swear this whole thread about regexes is just fake rage at something, and I bet it'd be reversed had they used something heavier (omg, look they're using an LLM call where a simple regex would have worked, lul)...
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Looking forward to someone patching it so that it works with non Anthropic models.
Cheap chinese models incoming.