41–50 of 67 posts
This is far from what I expected. There is not much related to quantization, pruning, common architectures, precision or benchmarking. For those interested in this topic, I would recommend content from MIT HAN Lab.
The very first sentence: > Welcome to EdgeAI for Beginners – your comprehensive... Em dash and the word "comprehensive", nearly 100% proof the document was written by AI. I use AI daily for my job, so I am not against its use, but recently if I detect some prose is written by AI it's hard for me to finish it. The written word is supposed to be a window into someone's thoughts, and it feels almost like a broken social…
They are really embracing ai! I can feel them all around even. Above me. Below me.
imagine how much worse it will be soon, given everything they seem to be outputting now is entirely generated slop
Earlier quoted context omitted.
I said em dash _and_ the word comprehensive. If you work with LLM generated text enough it gets very easy to see the telltale signs. The emojis at the start of each row in the table are also a dead giveaway. I am guessing you are one of those people who used em dashes before LLMs came out and are now bitter they are an indicator of LLMs. If that's the case, I am sorry for the situation you find yourself in.
If it makes a difference: it's an en dash used in the readme. I've been wondering why LLMs seem to prefer the em dash over en dash as I feel like en (or hyphen) is used more frequently in modern text.
So:
* fragment a—fragment b (em dash, no space) = traditional
* fragment a — fragment B (em dash with spaces) = modern
* fragment a -- fragment b (two hyphens) = acceptable sub when you can’t get a proper em to render
But en-dashes are for numeric ranges…
This is far from what I expected. There is not much related to quantization, pruning, common architectures, precision or benchmarking. For those interested in this topic, I would recommend content from MIT HAN Lab.
Can you provide links or more information?
This is far from what I expected. There is not much related to quantization, pruning, common architectures, precision or benchmarking. For those interested in this topic, I would recommend content from MIT HAN Lab.
Can you provide links or more information?
It seems this is focused on on-device computation - as distinct from, say, Cloudflare's definition of the "edge" as a smart CDN with an ability to run arbitrary code and AI models in geographically distributed data centers ( https://workers.cloudflare.com/ ). Per Microsoft's definition in https://github.com/microsoft/edgeai-for-beginners/blob/main/... : > EdgeAI represents a paradigm shift in artificial intelligence…
Yeah, Cloudflare is in the minority with their definition of "edge."
Earlier quoted context omitted.
edge just means as close to the user as you can get. microsoft's edge is closer to the user than cloudflare's edge or an ISP's edge because microsoft runs your laptop.
Wow, they really do have an edge over the competition there...