M1 MACBOOK AIR REVIEW | A Good Choice For Computer Science Students? │ Apple-youtubeリンクまとめ

【視聴数　179352】

【チャンネル名　Created by Ella】

【タグ　m1 macbook air,m1 macbook,m1,macbook air,macbook air for comp sci,m1 macbook air for comp sci,m1 macbook air for computer science,m1 macbook air for comp sci students,m1 macbook air for computer science students,is the m1 macbook air good for cs students,m1 for cs】

コメント（244件）

Tanner Davies より:

12月 15, 2020 11:55 pm

If you are doing web dev, you need more than an IDE and a browser. One of the biggest pieces of web dev is designing a server. The server is an application just like any other, albeit without a GUI. Also, DOCKER. You will probably need docker to run and quickly set up several servers on one machine. If you are a CS student in this day and age, you will NEED docker. Maybe not for the first couple years of your program, but for the third or fourth year you certainly will. The missing virtualization capabilities are what keep Android emulators from running and are also what keep Docker and VirtualBox from running smoothly.

But yes, for first-year students just doing very basic Python or Java applications or basic HTML/JavaScript webpages that don’t require a server but are just parsed from a local file, the M1 works. For advanced students or for getting work done in the workplace (if you aren’t programming iOS/Mac exclusive apps), you will need an Intel or AMD processor for the time being.

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Devin Otero より:

12月 16, 2020 12:53 am

Wish macbook could do CAD decently

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fake より:

12月 16, 2020 3:17 am

is the weather widget from rainmeter?

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WildRifter より:

12月 16, 2020 1:29 pm

Nc Video! 💜

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Keith1020 より:

12月 16, 2020 6:19 pm

What’s your tech specs?! 🤓

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Aiman Harith Zaharudin より:

12月 18, 2020 4:26 am

oracle 11g can be download on m1 macbook?

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n2akilan458 より:

12月 18, 2020 5:33 pm

Do you know if it’s possible to write and compile C++?

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Abhishek Kumar より:

12月 18, 2020 8:59 pm

Well can you please tell me that is autocad working in this fine or not?

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Donnie より:

12月 19, 2020 1:38 am

6:27 – the thing is that commodity laptop hardware is as good, or better than server hardware, depending on the budget.

Let me explain:
Before, laptops just sucked. Servers were these machines with powerful CPUs. The latter is still true, but changed in the way that instead of having fast cores, they have MANY MANY cores. But they aren’t that fast. However laptop CPU performance has taken a course straight up about 5 years ago, probably as soon as the GeForce 9xxM appeared, since it was significantly better than previous generation and suddenly laptops were a viable option for gamers without being too thick. CPUs went straight up since then.

I’ve had many laptops that were far more powerful in computation than some of the large virtual servers that we rented out, for about the price of that laptop.

Servers are super expensive to rent. That’s because they’re well connected to an infrastructure where moving data is easy and cheap, and they are well cooled, and you can assure that they’ll always be online, etc.

When doing machine learning training, you don’t need a stable connection, nor any of the other prerequisites. You need FAST parallel workload capabilities. Laptops are cheaper than servers for this purpose. Desktop computers are even cheaper. It’s another question whether you want to stress your laptop when you’re on the go or in the office. Also if you have the budget – go ahead and get that GPU-powered supercomputer. And of course for production workloads it’s ALWAYS servers, and not laptops.

For experimenting and learning, even when you have to train on a large dataset, the computer you have (if it’s not a potato) is by far the better choice for this.

Especially the M1, that has dedicated components to deal with ML workloads apparently. Haven’t seen those in action yet and have no clue how are they different from GPGPU workload.

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Donnie より:

12月 19, 2020 1:45 am

One thing that’s important for developers, for day-to-day stuff, is the ability to run applications in Docker or similar container software (like Podman). Now Docker will eventually release a compatible version, but right now there’s no way to run containers.
And even with a container, it’s gonna be weird to see how the translation will work between the container (most often it’s gonna be x86) and the base system. Because it ain’t gonna be Rosetta.

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Esha より:

12月 19, 2020 8:10 am

Can you test gcc compiler please 🙏

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Gourav Goutham より:

12月 19, 2020 2:02 pm

Can you give me some tips for computer science, coding on python ….blah…
Plzz reply me….
I need some stuff to understand me
You could help me
I have some doubts so you could help me
…..

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Matt Styles より:

12月 19, 2020 6:17 pm

You can’t bootcamp into an M1 macbook, but you can use parallels to run Windows on it!

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Utkarsh Bajpai より:

12月 19, 2020 8:13 pm

You look like Jennie.

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Karthikeyan A K より:

12月 20, 2020 5:00 am

As long as it doesn’t get repaired it might be okay, if it breaks down you have to pay hefty for Apple service as none other than Apple can repair it.

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Dark Blood より:

12月 20, 2020 7:26 am

Great video I aint a cs student, I’m info tech networking and cybersecurity student but our uni treats it like cs course and this has helped me think about getting this as my next laptop

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Levyn KHS より:

12月 20, 2020 10:32 pm

I want to do cs, do you recommend me?

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Victor Nascimento より:

12月 21, 2020 12:55 am

Cool, but saying web development doesn’t really have CPU requirements is a mistake IMO. Modern web development relies on transpilation (Typescript, babel) and bundling (Webpack, parcel) which are both CPU intensive.

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Mark Jay Lunas より:

12月 21, 2020 3:29 am

Loved the vid. Thank you♥️

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Shaurya Tanwar より:

12月 21, 2020 5:49 am

You’re gonna be a ‘Creator on the rise’. Good luck.

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