What's your counter to "if they cant use op_return then they will include it in the witness and thats worse because witness it cant be pruned and creates an unspenable output, further bloating the utxo set" ?
Missing nostr:npub1guh5grefa7vkay4ps6udxg8lrqxg2kgr3qh9n4gduxut64nfxq0q9y6hjy's nostr:npub1cashappn03s3cl2ljsdntv0v28e2um5lgx4vjctqjt23pcwzjhsqmtdg5l falsetto. Can y'all sponsor the show again 😅
Ever pull clothes out of the dryer and realize you washed something with a tissue in the pocket? 😑
I hope bitcoin is saved by a fork with a sweet logo
nostr:npub1xapjgsushef5wwn78vac6pxuaqlke9g5hqdfjlanky3uquh0nauqx0cnde and nostr:npub1s6z7hmmx2vud66f3utxd70qem8cwtggx0jgc7gh8pqwz2k8cltuqrdwk4c
> A talk with Bitcoin Core developer Sjors Provoost about how the project is organized, and what it's like to contribute to it.
Idea:
Nostr client adds # button above keyboard, in line with gif, media and other buttons. It suggests recently used hashtags, or recent hashtags from wot, or context of draft message. Use local or private llm for the last one. Feels like it could create communities more organically
Maybe nostr:npub1n0stur7q092gyverzc2wfc00e8egkrdnnqq3alhv7p072u89m5es5mk6h0 could add this? 🙏 nostr:npub1n0sturny6w9zn2wwexju3m6asu7zh7jnv2jt2kx6tlmfhs7thq0qnflahe
Brother cuts my hair. Its free, but i like to pay with bud. #v4v
Links dont even appear the same way in all clients. I bet notes with native media get zapped way more than notes with links to stuff
Original estimate: 2 weeks. But you're saying maybe... 3?
Of course she needs gpus. Shes trying to keep the company's data secure by running local llms and those require some power 😬
Shes going to need...
2x nvidia rtx 4090
Ryzen 9 7900x
128 gb ddr5 ram
Asus tuf b850 mobo
2x Samsung 990 pro 4 tb
Have fun
Which is in... two weeks?
Yup
Shocker, big ai is throwing their dick around
> We find that undisclosed
private testing practices benefit a handful of providers who are able to test multiple variants before
public release and retract scores if desired. We establish that the ability of these providers to choose
the best score leads to biased Arena scores due to selective disclosure of performance results. At an
extreme, we identify 27 private LLM variants tested by Meta in the lead-up to the Llama-4 release.
We also establish that proprietary closed models are sampled at higher rates (number of battles) and
have fewer models removed from the arena than open-weight and open-source alternatives. Both
these policies lead to large data access asymmetries over time.
No GUI. User configs are handled with environment variables.
