I’m a native Spanish speaker and I find English poetry much easier to understand, English is more rigid and while technically it might have a larger vocabulary you can do less with it, while the flexibility of Spanish in terms of word order and suffixes makes it possible to craft some really labyrinthine verses

Inference is still done in plaintext after this multi-agent message gets decrypted in the server side

In that situation it makes sense for you to bring a personal laptop which you can use to access non confidential stuff, you might not write any code in it and might just be given docs to read through

But if the bot is advanced / expensive enough, it gets a lot harder. Where this product's market sits is in giving a paid way to access content compared to having to spin up bots that run js, from real IP addresses, etc. all of which are more expensive

Even in LLM jailbreak CTFs I've seen, it ends up feeling like underpaid work when it's sponsored by Microsoft and the prize pool is, say $10k (including stuff like azure credits) considering the salaries AI safety engineers command at big tech!

For comparison, I won a similar prompt injection challenge ran by a crypto company a while back where the total prize pool was over $100k... I didn't win every challenge though, but my team took home around half of that

The problem with good prompt injections is they have a very short half life once they are out in the wild (especially if they work against frontier models)

  name: my-cool-pages-project   
  pages_build_output_dir: ./html-files/

I don't understand how they rank words though, some extremely common words like xenophobia were ranked as high as much more obscure ones.

Anything up to expert was obvious

In reality, what most people need is much simpler, a mini app with some curated datasets and simple filters, maybe some AI querying if we want to get fancy. There's some companies out there that work with big data, but for the rest of us small data is ok.

Apart from the shitty software and basic features either missing or locked behind a monthly cost, the network itself is not bad at all, I get 600-700mbps on wifi throughout the house and have my servers wired on 2.5gbe

But the one thing I really thought I was buying into by choosing an amazon brand was ease when it came to buying upgrades, and yet I ended up having to buy extra hardware (like the wired gateway) from ebay and sellers in the US as amazon does not sell their own hardware everywhere

- What are the margins of Anthropic over their API pricing? Without this, all we're saying is the API is more expensive for heavy usage

- How have their price margins changed over time? I imagine built into their commercial model is the expectation for inference to get cheaper over time

- They have tighter usage windows than they used to, now having both 5-hour and weekly limits, they also seem to experiment with their usage quite often, this probably affects user's average utilisation, do they have any other levers they can pull here? eg how does changing to an 8-hour window affect it, or limiting certain models to API-only usage based on capacity like Fable

I know there is a certain level of subsidised usage built into their subscriptions, the VC-funded company playbook, but I don't think anyone from the outside knows for sure how much it is and I imagine it's lower than most people think, and reducing over time.

Say I want to distribute an hmml file as a single file, I'd have to create an html with the embedded js runtime, and then embed the hmml file... as b64, therefore negating any benefits.