v_krishna

Number 1 that’s black beans. Number 2 the punchline is “i dunno but I’ve never paid $20 to have a garbanzo bean on my face”. Number 3 I won’t allow my go to joke to be stolen by these fascist goons!

99 in Berkeley right now. My house was built in like 1928 and since we rent obviously there’s been no energy efficient updating of insulation or anything like that since maybe the 60s. It’s like 94 inside right now. Sitting in front of multiple fans just blowing hot air at me this is the life y’all.

I’m not sure if this is an Oscar reference or a Zizek reference and either way I’m here for it.

(((Truth)))

https://arewereorganizedyet.com/ lol already updated

How does lemmy federation work in this case? Conceivably after being restored from backup the lemmy.ml instance could see those few hours of lost history as federated to other lemmy instances and resync it back as the host instance. Obv I’m vastly oversimplifiying things but what happens today?

https://github.com/Mozilla-Ocho/Memory-Cache is the actual project if you want to use it.

Basically it’s a firefox extension to save a page as a pdf in a directory that is symlinked to your local PrivateGPT install which then ingests the docs. It doesn’t seem to me that it provides any in-browser querying of PrivateGPT but I haven’t tried setting it up to confirm that.

I think that is overly simplistic. Embeddings used for LLMs do definitely include a concept of what things mean and the relationship of things to other things.

E.g., compare the embeddings of Paris, Athens, and London to other cities and they will have small cosine distance between them. Compare France, Greece, and England and same. Then very interestingly, look at Paris - France, Athens - Greece, London - England and you’ll find the resulting vectors all align (fundamentally the vector operation seems to account for the relationship “is the capital of”). Then go a step further, compare those vector to Paris - US, Athens - US, London - Canada. You’ll see the previous set are not aligned with these nearly as much but these are aligned with each other (relationship being something like “is a smaller city in this countrry, named after a famous city in some other country”)

The way attention works there is a whole bunch of semantic meaning baked into embeddings, and by comparing embeddings you can get to pragmatic meaning as well.

For marketing emails sure but for transactional emails you usually don’t have to warm IPs, just have the various email security things setup mentioned above