The same way LLM's without watermarking cannot be reliably classified as "not-human" neural-network driven scraping tools are getting harder to detect.

Cloudflare, and DataDome position themselves as companies that can detect automated traffic using things like IP reputation, behavioral signals, timing... But these things can be faked through proxy-networks, human behavior signals can be imitated with generative AI the same way text can be, web bots can utilize neural networks to generate trajectories and timings similar to those of humans.

If you can have an AI use a browser the same way a human can how can you distinguish the two?

For example, take a large online retailer... They have to show their products to customers (for free) for people to be able to shop, but increasingly they see spikes in traffic that match what would be expected from targeted bot attacks or scraping... But this traffic is getting more and more difficult to distinguish from legitimate traffic to the website. They could easily add this x402 middleware to their services, or they could offer API access to their product catalog for a price and enforce usage limits... But if they cannot reliably detect human users from bot/agent users, they have no way of pushing the bot/agent users to paid access... And why would the people running these bots pay when they're already getting what they need for free? Now Cloudflare cannot even reliably block bot traffic, and there are AI based browsing/scraping tools available now for bypassing Cloudflare.

Why does this company deserve tax-breaks on their AI data-centers again?

> I'm much more worried about people who give full write access to their agents! But at least this solves that problem.

Yeah it goes without saying that write access would be crazy... But, it seems like people don't really care about the fact that they are just giving their private data to companies like Anthropic, OpenAI and Google.

> Branch anonymization Branches default to a full copy of your production data.

<-- This doesn't seem a safe default to me...

Perhaps a data policy should be required to be in place before a branch can be cloned... The default configuration giving the LLM full prod data access by default, is a bad standard to set, I think.

> Most data centers colo multiple types of compute, not just those dedicated to inference or model training. Additonally, strangling the economics of the infrastructure layer makes entire ecosystems move abroad.

Sure but we are talking about whether the enormous investment into AI infrastructure is prudent or not. Also I reckon most people on here made a living just fine before everything moved to remote data centers, and many if not most HNers workloads could run on individual machines... But that's another conversation.

They Might Be Giants - Istanbul (Not Constantinople) (Official Music Video)

Than pass the program, your server or application can parse the instructions and work from the generated AST to do all sorts of interesting things, within the confines of your language features.

It's verifiable, since you are providing within the defined grammar, and with the parser provided.

It is implicitly sandboxed by the powers you give (or rather exclude) to your runtime via an interpreter/compiler

I've tried this before for a grammar I defined for searching documents, and found it to be quite good at creating valid often complex search instructions.