Nothing dishonest with pirating. You wouldn’t download a car? Well I would.

When billion dollar companies, which are praised and supported by governments, download pirated material and do not pay, why should ordinary people restrain themselves and pay? I cannot see how one can make moral arguments against piracy now. It makes no sense to pay if others are not paying and not punished for it. People also have a right to train their real neural network for free without paying.

Many companies encourage employees to go home and relax or engage in other rewarding activities; it can be very beneficial for the employer. For one thing, it encourages people to separate their work lives and home lives, which can decrease stress (often encouraging productivity and increasing tenure), as well as encouraging people to treat their office as somewhere to focus on work (to the exclusion of distractions). Additionally, in many fields it can be helpful to get a fresh perspective on your work every day, rather than getting tunnel-vision, which can happen from having your 'head down' all the time.

no that's incorrect - llama.cpp has support for providing a context free grammar while sampling and only samples tokens that would conform to the grammar, rather than sampling tokens that would violate the grammar

and in fact leverages that control to constrain outputs to those matching user-specified BNFs

https://github.com/ggml-org/llama.cpp/tree/master/grammars

The inference engine (llama.CPP) has full control over the possible tokens during inference. It can "force" the llm to output only valid tokens so that it produces valid json

I recently discovered that ollama no longer uses llama.cpp as a library, and instead they link to the low level library (ggml) which requires them to reinvent a lot of wheel for absolutely no benefit (if there's some benefit I'm missing, please let me know).

Even using llama.cpp as a library seems like an overkill for most use cases. Ollama could make its life much easier by spawning llama-server as a subprocess listening on a unix socket, and forward requests to it.

One thing I'm curious about: Does ollama support strict structured output or strict tool calls adhering to a json schema? Because it would be insane to rely on a server for agentic use unless your server can guarantee the model will only produce valid json. AFAIK this feature is implemented by llama.cpp, which they no longer use.

People should be way more upset at the fact that Safari adblocking today is still inferior to even MV3 Google Chrome. Apple's implementation of declarativeNetRequest was semi-broken until the very latest iOS 18.6.

Apple can do the bare minimum, years after everyone else, and barely get called out. The Reality Distortion Field is the enemy.

Also funny that other devs had the gall to make people pay (sometimes subscriptions!) for Safari adblockers inferior to the free adblockers on any other browser.

I’m still trying to understand what is the biggest group of people that uses local AI (or will)? Students who don’t want to pay but somehow have the hardware? Devs who are price conscious and want free agentic coding?

Local, in my experience, can’t even pull data from an image without hallucinating (Qwen 2.5 VI in that example). Hopefully local/small models keep getting better and devices get better at running bigger ones

It feels like we do it because we can more than because it makes sense- which I am all for! I just wonder if i’m missing some kind of major use case all around me that justifies chaining together a bunch of mac studios or buying a really great graphics card. Tools like exo are cool and the idea of distributed compute is neat but what edge cases truly need it so badly that it’s worth all the effort?

  - Costs.
  - Rate limits.
  - Privacy.
  - Security.
  - Vendor lock-in.
  - Stability/backwards-compatibility.
  - Control.
  - Etc.