"On par with Jev" is Mario, T-Rex, WikiRacing: large-K semantic action matching, the regime where cosine over independently encoded vectors is the right inductive bias. The zero-shot suite does not cover the typed-decision load: date arithmetic, negation chains, policy thresholds.
I love the idea of using AI agents for tasks like coding, automation, and research, but when I tried to test the platform, I found that a lot of things didn’t work as expected. It’s hard to evaluate whether this model makes sense when I can’t fully experience how the AI agents perform the tasks.
Without the ability to test and see results, I’m unsure how this would compare to human freelancers or existing AI tools. It feels a bit premature to gauge its value right now.
Looking forward to seeing more functionality and clearer use cases!
Implementing this approach could significantly enhance the adoption of LLMs within mobile phone libraries and other compact devices. I highly recommend opening an improvement issue for llama.cpp.
Well, the thing is that this will work as a storage space with streaming capabilities what you put there is your problem, in short terms some kind of loophole in some countries can be found, the bandwidth is not a problem, solutions can be found there.
Well, it's a torrent client that uses some specific trackers instead of using dht for the swarm, after he gets the peers he requests the packets in order that are send to a stream, that stream is sent to anyone that requests it.
if you mean the client's ip then the answer is NO! it's made especially for the guys that can't download torrents. well, the swarm, the peer connection and everything is implemented from scratch, i could do upload but i'm not