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That's really interesting! Thanks for sharing. Will be trying it soon.

> Having less diversity in answers could mean you're more consistently getting a better/worse/same quality answer.

I wrote the article. I'm trying to show how diversity loss is itself a measure of quality loss in many applications. And as I pointed out in another comment, the paper's authors themselves acknowledge as much in their paper.

> Instead of just re-rolling the answer, why not continue in that thread and say what you don't like?

The re-roll is actually a feature of many chat apps with a dedicated button. So it's something users are familiar with.

But the results are also quite different. The prior answers in your example of asking for x alternatives influence the following answers too much in a way a re-roll doesn't.

I wrote the article. How you define quality is exactly the issue.

> In my opinion, 'sample diversity' and 'sample quality' are not the same thing, and conflating the two concepts leads to poor intuition.

But you're assuming everyone has the same notion of quality as you. As I point out in the piece, even the paper's writers use "quality" to show how watermarking can "lower the overall quality of a system"

> SynthID and the like probably matter most if one is trying to repeatedly sample an LLM in order to infer the probability distribution

Which is another impact I write about in the piece. If you evaluate the output quality of an LLM system in this way, you're impacted more by watermarking.

Worth noting that this is what OpenAI wrote about text watermarking two years ago:

> While it has been highly accurate and even effective against localized tampering, such as paraphrasing, it is less robust against globalized tampering; like using translation systems, rewording with another generative model, or asking the model to insert a special character in between every word and then deleting that character - making it trivial to circumvention by bad actors.

> Another important risk we are weighing is that our research suggests the text watermarking method has the potential to disproportionately impact some groups. For example, it could stigmatize use of AI as a useful writing tool for non-native English speakers.

https://openai.com/index/understanding-the-source-of-what-we...

It reduces diversity, which they don't talk about much. Wrote about it here. https://blog.keyvan.net/p/ai-text-watermarking-and-quality

Agree. I think many people forget that not long ago, HTML markup on many sites was a lot richer than it is today. Making it trivial to produce a good trimmed down markdown version.

The reason it may be more difficult today is because we've lost a lot of that. Some of it because of modern JS frameworks, but some also because publishers simply don't want to make it easy for the useful stuff to be scraped and extracted easily.

I'm not convinced that's changing because of AI agents (it's getting worse in many ways with anti-agent rules). Maybe improving for documentation pages intended for agents. But if it is changing, I think it'd be far easier to improve the HTML and let the agent take care of the rest.

In general I think I just don't like the idea of one URL being able to return different content. Forces me to think about what each system I give that URL to may be sending in content negotiation headers. Would rather the HTML is returned and alternatives listed in HTML head.

But for HTML and Markdown in particular, there's been so much useful work done in the semantic HTML space and microformats, that I don't know why anyone interested in this wouldn't just improve their HTML markup and leave it to the agent to do the rest. Convert to markdown or extract the useful HTML before handing it to model.

Thanks. I posted that comment before they had added support - https://news.ycombinator.com/item?id=48353325 - didn't know situation had changed.

But it's something I think developers should think about if they rely on caching. If it took Cloudflare this long to support this, there may be other systems which still don't.

Link to Roy Fielding comment:

https://lists.w3.org/Archives/Public/ietf-http-wg/2013JanMar...

I agree. I think a lot of people here are assuming that the full HTML retrieved has to go into the LLM eating up tokens. But why wouldn't the agent try to clean up first and remove bloat and convert to markdown itself, before feeding into LLM. Semantic HTML would make that easier.

I agree with Roy Fielding on this:

> It is a bad design trade-off to send a bunch of header fields on every request just to tell the server all of the possible variations of preference held by the user, particularly when there is a very small chance that any of those dimensions are applicable to the target resource. It has been a bad design trade-off ever since the very brief period in 1993-94 when folks didn't know which image format would be usable on all UAs and there was no CSS or javascript to allow for client-side adaptation.

> ...The caching impact of proactive negotiation is far worse than the one extra round trip per site for reactive negotiation, and even that round-trip isn't necessary in formats that support client-side adaptation.

On the caching impact, Simon Willison wrote:

> ...you can’t deploy an application that uses content negotiation via the Accept header behind the Cloudflare CDN — for example serving JSON or HTML for the same URL depending on the incoming Accept header. If you do, Cloudflare may serve cached JSON to an HTML client or vice-versa.

Note: I posted this in another comment with links to those two quotes which I couldn't copy easily now - will add later.

My biggest issue with AI text is just that it's annoying to read, so I get put off before I can figure out if the content is actually worth reading. I would love a detector that detects the style of writing I find annoying and warns me, or offers to rewrite it so I can give it a chance at least.

> this is only about machine-generated works that are trying to pass as human works.

But by "machine-generated" don't you mean "text that came out of an AI model"? My argument in the post is that such output tells us very little about how much human input went into the original work. It's all lumped together as AI slop.

That's an interesting idea to try as a browser extension. I think Facebook is particularly egregious here, so I doubt you'd need to run something like this on other sites. But if it worked fast enough on just Facebook, it would be useful.

This reminded me of an old documentary about corporations: "If we look at the corporation as a legal person, it exhibits all the characteristics of a psychopath" https://www.youtube.com/watch?v=s5hEiANG4Uk

I personally have no insight into what they have or haven't dismantled. Just found the article interesting (had never heard of the company). Was responding to the "They seized the wrong domain" claim in the tweet you quoted. I read that and thought they disabled an unrelated domain, which doesn't appear to be the case. As for the main domain, no idea about that. Someone brought that up to the author of the piece, and the bit I quoted was his response. I have no more info beyond that.

NearlyFreeSpeech.NET: https://www.nearlyfreespeech.net/about/