I don't think it represents a lot of people, Apple high end offering is absolutely unaffordable for most of us.
If you can afford a max specced M3 you can also afford 2 RTX 4090 which should theoretically be faster.
If you can afford a max specced M3 you can also afford 2 RTX 4090 which should theoretically be faster.
If all you want to do is AI/ML then yes, a M3 is not your best option but if you want an extremely powerful laptop that can run AI models locally fairly easily (and it's well supported) then the M3 is a great choice. I love being able to download and test out AI models on my M3.
Still, trying to do significantly fun or interesting things in any major AI ecosystem, such as the Stable Diffusion one through Automatic1111 or with the LLMs in Oobabooga (which supports nearly all LLM backends i.e. llama.cpp), will be mostly crippled and stuff will break in ways that simply don't happen to Nvidia hardware. I'll take the 2 4090s all day, because I know that quantization techniques which shouldn't even be possible (who knows maybethe fabled 1 bit quantization seems inevitable at this point) will make it possible for me to stuff even the most bloated LLM into my measly 48 GBs will be available on Nvidia first and Apple (maybe) second.
That or devs will start building Linux hosts for their gpus at home.
Might be a good hold-over for X years until the consumer hardware catches up and/or the model optimizations make the same hardware perform up to today's DC hardware.