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As an engineer on an M1, I have to say you made the right choice. Half the stuff that I try to work on is just straight up broken, especially Python/AI related

by brink 6y ago

As an engineer on an M1, I have to say you made the right choice. Half the stuff that I try to work on is just straight up broken, especially Python/AI related tools. I have to switch to my Linux laptop regularly to get anything done. I've wasted days just trying to get certain dev tools working.

mark_l_watson 6y ago
I have hit the same problems with Python deep learning tools. Apple’s version of TensorFlow was an OK start. If you like conda, they now have pretty good support for M1. I have the usual Docker problems, and I don’t think that they will get sorted until many more pre-built containers are also built for ARM. That said, I love my M1 MacBook Pro and for now I don’t mind too much keeping my old MacBook nearby.
martinald 6y ago
I've found the experience better, most stuff I've used works out of the box, but there are often weird lib problems that require various hacks. You then can't check them into source control as it'll break intel users, and it becomes a bit of a headache remembering all this. I think the situation should continue to improve, but there is an extremely long tail of stuff to get working. The other thing I would mention is that Rosetta is very very slow. A lot of the initial impressions made out it was basically a bit slower, but for a lot of stuff it's slow as hell. You do not want to for example run an IDE in Rosetta.
eigenvalue 6y ago
Apple should really hire a couple smart devs to just focus 100% on getting working M1 wheels on PIP for all the most popular Python libraries (same for conda forge). Seems like a no-brainer given their dominance in laptops for software developers. I'm sure the community would just do it on its own, but if they can speed up the process by 6 months they will be able to sell enough extra units to pay for the devs.
- NoSorryCannot 6y ago
  Maybe they have, but whoever does the work, there is a lot of ground to cover in the space of developer tool chains. It's going to be a minute to get to a point where devs don't feel like they have to make compromises.
syntaxing 6y ago
Totally agreed and tensorflow is pretty broken (I guess the alpha release tag is fair). But the newest brew released has fixed maybe 90% of the issues. With miniforge + pytorch, you can run most things.
runeks 6y ago
I just default to an x86-emulated terminal and everything I use on my M1 works exactly as it did on my Mid 2015 MBP, except faster. The only exception is virtualization, which only works if there’s an ARM image available (which there isn’t, mostly).

by brink 6y ago

mark_l_watson 6y ago

I have hit the same problems with Python deep learning tools. Apple’s version of TensorFlow was an OK start. If you like conda, they now have pretty good support for M1. I have the usual Docker problems, and I don’t think that they will get sorted until many more pre-built containers are also built for ARM. That said, I love my M1 MacBook Pro and for now I don’t mind too much keeping my old MacBook nearby.

martinald 6y ago

I've found the experience better, most stuff I've used works out of the box, but there are often weird lib problems that require various hacks. You then can't check them into source control as it'll break intel users, and it becomes a bit of a headache remembering all this. I think the situation should continue to improve, but there is an extremely long tail of stuff to get working. The other thing I would mention is that Rosetta is very very slow. A lot of the initial impressions made out it was basically a bit slower, but for a lot of stuff it's slow as hell. You do not want to for example run an IDE in Rosetta.

eigenvalue 6y ago

Apple should really hire a couple smart devs to just focus 100% on getting working M1 wheels on PIP for all the most popular Python libraries (same for conda forge). Seems like a no-brainer given their dominance in laptops for software developers. I'm sure the community would just do it on its own, but if they can speed up the process by 6 months they will be able to sell enough extra units to pay for the devs.

NoSorryCannot 6y ago
Maybe they have, but whoever does the work, there is a lot of ground to cover in the space of developer tool chains. It's going to be a minute to get to a point where devs don't feel like they have to make compromises.

syntaxing 6y ago

Totally agreed and tensorflow is pretty broken (I guess the alpha release tag is fair). But the newest brew released has fixed maybe 90% of the issues. With miniforge + pytorch, you can run most things.

runeks 6y ago

I just default to an x86-emulated terminal and everything I use on my M1 works exactly as it did on my Mid 2015 MBP, except faster. The only exception is virtualization, which only works if there’s an ARM image available (which there isn’t, mostly).