I disagree regarding the “generic reply to Anti-ai”. Discourse nowadays simply ignores locally run models - they do not exist outside of a sphere of technically adept users. Making sure more people know that you don’t have to finance OpenAI, Anthropic, Meta or the Neoclouds should be way more accessible information.
This tech and what is happening currently should not be conflated. If Big Tech used up all global stockpiles of bubble gum because they wanted to create the worlds largest chewing gum bubble, it doesn’t mean that you with your single pack of gum is even comparable to what they are doing.
The only question in your comment i can see is the concern about energy cost while training a model. Those costs are a static amount - not ignoreable, but finite. The longer you use that model, or increasing the amount of people using it, reduces the cost per instance. Use a model long enough and the energy cost of creating in in the first place converges towards zero. It’s another point for local LLMs - nobody needs the aggressive update cycle Anthropic and OpenAI are running, and those can’t stop because the moment they do, investor money will stop flowing.
For what it can be used: well obviously it is a great tool in all areas where you can automate checking if what it did meets a specific criteria. That’s the reason why Mythos has Business entities like Microsoft scrambling like mad just right now - checking to see if Mythos managed to escalate privileges or run remote code is trivial, and Mythos is showing up security issues all over their software, up to the point that MS is scared that even if they patch the really ugly shit, Mythos might still chain multiple low level vulnerabilities to fuck them over, and all that is needed from Joe Shmoe are the words “go hack Onedrive”.
I personally like to use them to calculate stuff where i know it can be calculated because of my experience, but where i do not recall the specific formulas needed. I also use it for creating regular expressions on the fly, teaching myself how to create useful bash scripts (all my knowledge about sed and awk comes from a local LLM), among other things that are not the business of anyone - that’s why I am using a local model in the first place.
I honestly forgot that i also put a question about training cost; by the question i meant when i asked about uses for ai, i didnt realize i made it unclear whether it was a question or not
I dont think a model that you have said is bad for the environment is a good example
Regarding the first sentence, i have said that this seems like a generic reply because i have not said that llms are the worst thing ever (even saying that their uses could offset the downsides) or that they do not have uses (“AI is just a tool” is also an argument i see so often, never with any explanation behind)
For such impressive technology, i doubt the best use of it is a better search engine that you have to fact check or writing help
I have seen someone use a local model to control home assistant
I disagree regarding the “generic reply to Anti-ai”. Discourse nowadays simply ignores locally run models - they do not exist outside of a sphere of technically adept users. Making sure more people know that you don’t have to finance OpenAI, Anthropic, Meta or the Neoclouds should be way more accessible information.
This tech and what is happening currently should not be conflated. If Big Tech used up all global stockpiles of bubble gum because they wanted to create the worlds largest chewing gum bubble, it doesn’t mean that you with your single pack of gum is even comparable to what they are doing.
The only question in your comment i can see is the concern about energy cost while training a model. Those costs are a static amount - not ignoreable, but finite. The longer you use that model, or increasing the amount of people using it, reduces the cost per instance. Use a model long enough and the energy cost of creating in in the first place converges towards zero. It’s another point for local LLMs - nobody needs the aggressive update cycle Anthropic and OpenAI are running, and those can’t stop because the moment they do, investor money will stop flowing.
For what it can be used: well obviously it is a great tool in all areas where you can automate checking if what it did meets a specific criteria. That’s the reason why Mythos has Business entities like Microsoft scrambling like mad just right now - checking to see if Mythos managed to escalate privileges or run remote code is trivial, and Mythos is showing up security issues all over their software, up to the point that MS is scared that even if they patch the really ugly shit, Mythos might still chain multiple low level vulnerabilities to fuck them over, and all that is needed from Joe Shmoe are the words “go hack Onedrive”.
I personally like to use them to calculate stuff where i know it can be calculated because of my experience, but where i do not recall the specific formulas needed. I also use it for creating regular expressions on the fly, teaching myself how to create useful bash scripts (all my knowledge about sed and awk comes from a local LLM), among other things that are not the business of anyone - that’s why I am using a local model in the first place.
I honestly forgot that i also put a question about training cost; by the question i meant when i asked about uses for ai, i didnt realize i made it unclear whether it was a question or not
I dont think a model that you have said is bad for the environment is a good example
Regarding the first sentence, i have said that this seems like a generic reply because i have not said that llms are the worst thing ever (even saying that their uses could offset the downsides) or that they do not have uses (“AI is just a tool” is also an argument i see so often, never with any explanation behind)
For such impressive technology, i doubt the best use of it is a better search engine that you have to fact check or writing help
I have seen someone use a local model to control home assistant