Fable 5.1 Watermarks EVERYTHING, Here's How To Remove It
CChase AI
Computing/SoftwareInternet Technology
Transcript
00:00:00So yesterday, Anthropic launched Fable 5.1, and it is the first model they have put out
00:00:04that now watermarks everything it creates. And today, I'm going to show you how you can get rid
00:00:10of it. But first, let's talk about what this watermark even is, because it's a little bit
00:00:14of a misnomer to call it a watermark at all, why it's here in the first place, and how it works.
00:00:19Because if you understand those things, then the solution to get around this watermark will make
00:00:23a lot more sense. Now, why do we have to deal with this at all? Well, it's because this is
00:00:26in compliance with an EU AI Act that essentially all the major frontier labs have signed with the
00:00:31exception of XAI. And what this code states is that they need to, and they being the EU,
00:00:38needs a way to be able to tell if some sort of text or some sort of output was created by AI.
00:00:43And in order to do this, Anthropic has added a watermark to all of its outputs for models released
00:00:50after August 2nd, 2026, which just is Fable 5.1. Now, Anthropic claims this has no
00:00:56practical effects on the actual output it gives you, and that it's very limited in terms of what
00:00:59it's going to change if we're talking about code. But how does this thing actually work? And why did
00:01:03I call it a misnomer in the first place? Now, Anthropic's strategy for injecting these watermarks
00:01:07into its outputs is based on a paper that came out from Google in 2024 called Scalable Watermarking
00:01:13for Identifying Large Language Model Outputs. Now, this is a relatively technical paper. It goes into
00:01:19SynthID's tournament-based watermaking. But let me give you a simple mental model for you to sort of take
00:01:25on board. Now, as you know, large language models and their outputs are based on probability and there's a
00:01:29certain amount of randomness involved. If I give it a sentence that says, she is blank and it needs to
00:01:34fill it out, well, it's going to have a list of words it could possibly use to finish that sentence.
00:01:41And so let's say those words are beautiful, stunning, gorgeous, and pretty. Now, in reality,
00:01:48each of these words will have a different percentage or a different probability associated with them in terms of
00:01:54what the large language model will choose. A term you will often hear is called softmax, but you just need
00:01:58to understand all these words have a probability associated with them in regards to which one the
00:02:04large language model will choose. For this mental exercise, I want you to imagine all of these have
00:02:08the exact same percentage, right? So each of these words to finish the sentence has a 25% chance
00:02:14of being chosen. Now, normally before watermarking came into effect, it would just choose one of these.
00:02:20And so let's say it rolls the four-sided dice and it chooses beautiful. Cool, right? It had a 25%
00:02:26chance, all these had equal chance of being chosen. But now we work in a different system and that system
00:02:31is the watermarking system. With the watermarking system, we can still be in the same place where I say,
00:02:38hey, I need you to fill out the sentence, she is blank, and you have four options, right? And let's
00:02:42say, again, it's these four words and they have the same probability. When we add the watermarking
00:02:49construct, what it is going to do is it essentially is going to load this die. If this is some sort of
00:02:54four-sided die, well, it is then going to say, hmm, for watermarking purposes, beautiful is now going
00:03:01to be 50% and gorgeous is going to be 30%. So when we add a watermarking sort of system in place,
00:03:10it's going to choose certain words and more heavily weight them. And because certain words are more
00:03:15heavily weighted when the large language model chooses them, well, those words are going to show
00:03:19it more often, right? Using a watermarking system, more often than not, it's going to say she is
00:03:25beautiful. Now, you as the end user have no idea what these words are and which words are being
00:03:32weighted more heavily. But somebody who has the key, the watermarking secret key can tell. Now,
00:03:40they can't tell with absolute certainty because just like before, you know, there was always a chance
00:03:45it was going to say, you know, she is beautiful. You don't know that it was necessarily had a higher
00:03:49chance because of watermarking. But a person with the key is going to know which words were weighted
00:03:55more heavily. And it then is going to give them some sort of probability that tells that user who has the
00:04:01key, i.e. European regulators, okay, there's a 90% chance that this text, 100% chance, a 99% chance that this
00:04:09text was written with Claude, or this text was written with AI. That's how it works. Now,
00:04:15the idea here is that these words that it chooses to change and weight more heavily with watermarking
00:04:20aren't going to change the overall meaning of the sentence. It's not going to change your output.
00:04:24It's not going to change your performance. And when we talk about code specifically, it's not going to
00:04:28change code if it's going to affect what the output would look like. And it's not going to change facts.
00:04:34You know, if it says, hey, this historical event, you know, occurred on, you know, 810. Well,
00:04:41it's not going to change that wording, right? It's a fact. It occurred on 810. That's not going to be
00:04:45changed. But that is a simplified, again, simplified explanation of how this system works.
00:04:52Now, Anthropic hasn't totally come out with the exact algorithm for how that works, but we can
00:04:57extrapolate that from sort of the DeepMind papers. And what you also should have pulled from that is that
00:05:02having this key is the only way to know if it was written by AI based on the watermarking system.
00:05:08And this key is not public. To get access to the key, you have to request access. There's no public
00:05:12list. You probably have to be some sort of EU regulator. So anyone who comes out there and says,
00:05:16oh, hey, here's my website that can tell if it's watermarked or not, that's a lie that this does not
00:05:21exist. Now, if you want to go deeper into how the text watermarks work, Anthropic also has their own
00:05:25article. And they really try to hammer the point home that this isn't going to affect the outputs.
00:05:29So the watermarking system, in essence, is all about certain words being chosen more than others.
00:05:35And this is a statistical algorithm that you, the end user, will never be able to figure out unless
00:05:40you have the key. So how do we fix this? Do we simply do light editing to sort of the text outputs
00:05:47that Claude gives us and hope that's going to work? Or do we need to essentially rewrite the whole thing?
00:05:52And how do we rewrite it? Because you can't use Claude to rewrite whatever this sentence is,
00:05:56because that will be watermarked. And you also can't use ChatGPT. You also can't use Gemini.
00:06:01So your options become pretty clear. You need to rewrite significant portions of the text while
00:06:09retaining the overall feel. And you need to use either XAI. So you either need to use Grok or more
00:06:16likely what you're going to do is use some sort of open source model, right? Some sort of Chinese
00:06:21model that you can download and run on your computer that A is going to be free and B is not subject to
00:06:28these watermarking laws. Now, what does that system look like in a practical sense? Well, you do all your
00:06:33normal outputs with Claude. And if you've created something, think some sort of long blog post, and you
00:06:37don't want it to be flagged with the watermark, we're going to take that output. You're then going to send
00:06:42it to some sort of local model. And Claude can do that for you. There's tons of really good local models
00:06:47out there that you can download via OLAMA. That local model is going to go ahead and do its thing.
00:06:51It's going to rewrite the text. You're going to give it a prompt that says, "Hey, I want you to,
00:06:55you know, retain the actual feel of this. You can insert your own voice notes, whatever." And then once
00:07:01it's complete, it's just going to send its exact response verbatim back to Claude. And you can do
00:07:05whatever you want with it at that point. Now, the one other variable you need to think about in this whole
00:07:09thing is the length of your outputs. Like how many tokens are we talking about? Because, and this is not a
00:07:14number that we can actually know, is how many tokens, how long does this output need to be
00:07:19for the detection API, if it is run, to say with any degree of confidence it was written with AI.
00:07:25Because if I'm just writing LinkedIn comments that just say, "She is beautiful," can the API really tell
00:07:31if that was written with Claude or not? No. So if you're someone who is very sort of scared about having
00:07:37things watermarked and attributed to Claude, well, just ask yourself, "Am I writing things that are long
00:07:41enough for it to even matter?" If we're talking like LinkedIn posts, comments under, you know,
00:07:46100 words or so, probably not. But if we're talking like giant blog posts that are thousands of words
00:07:51long, yeah, you are going to be hit with that watermark. And it's going to be very obvious that
00:07:56it was written with Claude. Now, the easiest way to get this all set up is to download Ollama,
00:08:00download a local model that makes sense for your particular hardware, then create a skill inside of
00:08:05Claude that when you call it, sends your output to that local model, it does its full rewrite,
00:08:10and then it brings it back. To make this easy for you, I've created an entire prompt that walks you
00:08:15and Claude through the entire process. You simply copy paste this into Claude. It's going to do some
00:08:20research on your hardware. It's going to figure out what local model makes sense for you. It's going
00:08:24to download and install Ollama if you haven't done it. It's then going to create a skill for you,
00:08:28and it's going to ask you questions so you can get the actual verbiage of how that rewrite sounds like.
00:08:35Basically injecting your voice, giving examples, that sort of thing. So I'll put a link down below
00:08:40to actually do this. And rather than walk you through this entire thing step-by-step for the
00:08:44next 10 minutes, just run this prompt and it will do it all for you. So hopefully that whole explanation
00:08:48for watermarking made sense. This isn't an actual watermark. There's nothing being written behind
00:08:53the scenes. There's no code there. It's just that specific words are going to be used more often.
00:08:57You're going to have no idea what those specific words are. The only way you can tell is if you have
00:09:02the key for the watermark, which you won't have unless you're some sort of regulator. So anyone who's
00:09:07telling you that they can tell it's watermarked is pretty much lying to you. So know that right away.
00:09:11And based on how this works, again, you can dive into that DeepMind paper if you want. The only way
00:09:16you're going to get around this is with heavy editing. It's not going to be light edits. You have to
00:09:20rewrite it all. And the only way you're going to be able to do that is with an open source model.
00:09:24And it's going to be the cheapest way. So if you want to get your hands on that prompt,
00:09:29you can find it down below. Hopefully this helps some of you out. To be totally honest,
00:09:33I think the whole thing is rather overblown in terms of, you know, things are getting watermarked
00:09:38of that nature. Most of the people you see using AI to do sort of their writing, it is painfully obvious
00:09:43already that it's AI because they have really no idea how to humanize it or make it sound like them.
00:09:49And unless we're getting into a place where, you know, everywhere you post,
00:09:52every single website has some sort of like watermarker detector and that becomes some like huge faux pas.
00:09:58Again, all we have to do is run this through a local model and you're kind of scot-free.
00:10:02So let me know what you thought. Make sure to check out Chase AI+ to get your hands on
00:10:06the Cloud Code Masterclass if this is something you want to dive into more.
00:10:10Other than that, have fun avoiding these watermarks.
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