tart VS Chart

the inability to log in with an Apple ID in a MacOS VM is a decision made by Apple. you can certainly sign without logging in, but I don't think you can submit to the store in a VM.

you can see how they build tart here, including signing and entitlements and so on: https://github.com/cirruslabs/tart/blob/main/.cirrus.yml

Boots in 5 minutes, minimum allocation of 24 hours, is "low stock" if you actually try to allocate one, and was recently "no stock". I'd be unsure if its actually available when you need it.

Would be nice to see a Virtualization.Framework as a service, such as with Tart [1], but perhaps there are performance and security issues when making those M1s multi-tenant. The license limits it to a maximum of two guest systems, and only for the purposes of software development and testing [2].

[1] https://github.com/cirruslabs/tart/

[2] https://www.apple.com/legal/sla/docs/macOSVentura.pdf#page=2 (2B iii)

I haven’t used UTM personally so I can’t vouch for that. There is also Tart.

For a full reproducible solution, I thought of this: https://github.com/cirruslabs/tart

tart, uses also new Virtualization framework and supports ARM Linux on upcoming macOS Ventura

An alternative: https://github.com/cirruslabs/tart

So, for example, how would I get either versions of this to run with the script method? Would be nice to see ghc or ghci versions.

Hi u/Target_Organic, I wich you a warm welcome! Haskell is often very satisfying to work with, it has a sense of beauty in it. Regarding your questions: 1. I never had big problems about performance. However, I personally place more emphasis about correctness, simplicity and readability of my programs. Performance tuning comes after. 2. For graphic libraries, I know diagrams, Reanimate and Haskell-chart. Since you seems interested by mathematical approach to graphics, I think you will find happiness there. 3. I'm not sure about the AI field. Other, more practical languages such as Python seems to have taken the lead. What is sure for me, that Machine Learning/NN would be nicely describe in Haskell with solid foundations.