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It seems like it would be so low effort to bypass, especially when you can just train a system (maybe even another LLM) using the watermarker validation from Anthropic themselves. It seems it would get as simple as: outputText = promptLLM(prompt) scrubbedText = scrubWatermark(outputText) Might help with students and low-technical people passing off work as their own, but any industrial scale slop-generator should be able to bypass it trivially.
Allow me to disagree. GPL was a great idealistic dream that led to less-restrictive open-source licences such as MIT/BSD which have been the greatest catalyst towards the establishment of tech corpo giants and the software ecosystem we have today. GPL gave us Linux, but also gave us Amazon, Google and 2020s Microsoft. GPL is why 90+% of libraries on Github are MIT licensed. GPL gave us OpenAI and Anthropic and this here article.
Allow me to disagree. GPL was a great idealistic dream that led to less-restrictive open-source licences such as MIT/BSD which have been the greatest catalyst towards the establishment of tech corpo giants and the software ecosystem we have today. GPL gave us Linux, but also gave us Amazon, Google and 2020s Microsoft. GPL is why 90+% of libraries on Github are MIT licensed. GPL gave us OpenAI and Anthropic and this here article.
But what prevents someone from using Anthropic own detection system to train a watermark-scrubber? Seems like this would only catch the most unsophisticated cases.
And that will kill AI itself, since much of what it knows is from what learned from StackExchange before this latest one demise. And before the obvious comments on how GenAI is creative , then please do this OpenAI and Anthropic, for your next LLM. Just teach it Python, C and Rust and give it some good books. But dont give it access to Github...lets see what you can do then...
And that will kill AI itself, since much of what it knows is from what learned from StackExchange before this latest one demise. And before the obvious comments on how GenAI is creative , then please do this OpenAI and Anthropic, for your next LLM. Just teach it Python, C and Rust and give it some good books. But dont give it access to Github...lets see what you can do then...
Might give it a go, would be nice if there are some gains to be made. Though even then, need to think what’s my threshold where I would go this is good enough for me to use instead of defaulting to claude/openai/deepseek.
Just double checking my understanding: If this is true then only Anthropic will be able to detect if text was generated by one of its models, correct?
I've heard it can ramp the fans up so hard it'll suck the gold right off your motherboard traces and send it to OpenAI. This is the thing that the US administration is worried about, because Chinese open weights models will copy the function and then send all that gold to China, and the US will have to dip into the stores at Fort Knox, and potentially devalue the greenback.
Location: US/EU/IN Remote: Preferred Willing to Relocate: Yes Technologies: Agentic AI, SDKs, APIs, CLIs, AI-SDK, Langchain, Mastra, Typescript, Javascript, Tailwind, React, Nextjs, Vue, Python, HTML/CSS/SCSS, Git, Figma Resume: https://dub.sh/haxzie-resume Email: musthaq.gm@gmail.com About: Senior software engineer with extensive experience in building, and leading product and engineering teams. I have great design sense, and have been designing and shipping products for the last 8+ years. I have worked with several companies in their 0-1 journey, and 0-Mil journey as well, from idea to production. I have been working as a senior software engineer at Composio, where I have built the SDKs, APIs, and developer platfrom for the company which allows develop…
its banned by the terms of service. but contracts dont override copyright law, all they can do is terminate your account if they find out. when you give the outputs to a third party anthropic cant go after them. the copyright doesnt belong to them so all they can do is sue you for breach of contract where its impossible to prove damages.
I've noticed anthropic models going overboard on code comments recently (e.g. perhaps the last week or two?). I've noticed it poignantly in my own use of opus 5.0 and opus 4.8. It seems to add 3-6 lines of comments above most method definitions, even where it's totally unnecessary (e.g. where the comment is stating the bleeding obvious).
The Unabomber was anti-tech but not left wing in any coherent way.
> We're watching the end of Google's hegemony for sure. Who is standing by to replace them though? OpenAI and Anthropic certainly not, they are burning money in a fire pit to stay alive. There is no way in hell they can afford the compute necessary to replace Google.
> "Claude models launched on or after August 2, 2026 support marking at launch." No Anthropic model has been launched in August.
I agree. They have serious issues with coherence.
I was working in the mobile app via remote control when I saw it: "PostToolUse:Bash says: Tip: Run /ultrareview before you push to catch bugs with a cloud-based multi-agent review — 3 free reviews left." Haven't decided how I feel about this yet as it wasn't too disruptive, but I can see where it could cause issues in an automation pipeline. But maybe this is something they're only pushing to subscription users in interactive sessions, so I guess it could be considered "reasonably unobtrusive". Regardless though this is a darkening road.
I was recently working on an AI harness too, but I wasn't using AI to code it. It's really easy and requires little code. I wasn't even using langchain - that would require even less code. UI is harder for sure, but it's not that bad. You need to think though where to catch which exceptions. LLMs might opt for langchain which has had multiple breaking changes after the knowledge cutoff, making it hard for the LLM to work with it. This is probably going to lead to the LLM having to make many changes to it's code, making it messy and leading to further code being less maintainable.
WTF! I just looked at the filing date of March 2026 and assumed this was still an application! I realize now that even for a patent application it had published too early, since they usually get published 18 months after filing. Turns out it was fast-tracked, which is why it was issued in ~2 months. It does claim priority to an earlier filing so the invention date is indeed March 2006. Not a single claim was questioned or rejected, it went straight to grant! Yeah, unless I'm misreading claim 1, it seems iffy. From a quick glance at the spec, maybe the novel part is that all tool calls are executed in the sandboxed code block, thus keeping the intermediate results from polluting the context. But I'm not sure if that's different from existing systems like LangChain.
Location: Desoto, TX Remote: Yes Willing to relocate: Yes Technologies: Agentic AI, Python, Go, TypeScript/JavaScript, C#/.NET, React, Next.js, FastAPI, LangChain, LangGraph, CrewAI, OpenAI, Claude, Amazon Bedrock, Azure OpenAI, MCP, RAG, Multi-Agent Systems, AWS, Azure, GCP, Kubernetes, Docker, Terraform, PostgreSQL, MongoDB, Redis, Kafka Résumé/CV: https://www.toddfreeman.online/cv Email: toddfreeman06@gmail.com
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