Minimum Laptop Specs to Consider for Running AI/ML Tools and Virtualization

Minimum Laptop Specs to Consider for Running AI/ML Tools and Virtualization

by March 10, 2021 0 comments

It’s not just graphics designers and animators that need a powerful laptop today. Professions like data scientists, software developers and testers also require powerful machines for their work.

Take AI and ML for instance. Just about every sector today is embracing these technologies in various forms, and are hiring data scientists because the work involves working with huge data sets and files that run into hundreds of MBs or even GBs. They process this data work on tools like SQL, R, Python, Hadoop, LaTeX, etc.

Similarly, a programmer or tester working on multiple projects needs to run them in their own isolated environments to ensure that they don’t throw exception errors or cause conflicts. They need a clean environment for each project, for which they must run multiple virtual machines on the same system in order to test their code safely.

Even marketing professionals need to work on presentations that run into hundreds of MBs.

A normal machine would either crash or take ages to load these various kinds of files. That’s why these professions also need a powerful machine to handle their tasks efficiently. Here are the minimum requirements in systems for these power users:

Minimum Specs for Power Users

CPU: Intel has introduced its next generation of CPU which has more cores, threads, and higher frequency and cache to make processors as fast as they can. The new CPU is based on Tiger Lake architecture and offers AI acceleration. The Intel Iris Xe graphics enables to work on projects, powered by unique hardware-accelerated AI.

If budget is a constraint, then you can look at previous generation i7 or i9 CPUs with higher clock speed.

RAM: 8 GB is the bare minimum, 16 GB is recommended, but if you can go for more, like 32 GB, then that’s ideal. For instance, if you load a very heavy Excel sheet or CSV file with more than a million rows, then each row is loaded in the memory. So as you can imagine, the lesser the memory, the longer it will take to load. The Virtual Machine being run by a developer to test a project would also require its own memory.

GPU: When you are processing AI and Deep Learning algorithms, then GPU becomes very important, especially when you’re working on images or videos, which would require heavy amounts of Matrix Calculations. The graphics card would enable the machine to do parallel processing of these matrices.

We would recommend going for at least Nvidia GeForce 10 series or higher. You can also consider an AMD Radeon GPU. Whichever GPU you choose, it should have at least 4 GB of video memory or more.

Storage: This depends on you, but don’t go for anything less than 1 TB. Data scientists and programmers should choose only SSD, while other professions could choose a hybrid of SSD+HDD if budget is a constraint.

Laptop Recommendations

For these professions, what you need is a laptop that’s not only powerful, but one whose hardware is certified by all the top ISVs. The ZBook series by HP would be ideal for all these professions. The ZBook Firefly 14 G7 Mobile Workstation for instance, is powered by 10th Gen Intel Core i7 CPU, has 32 GB RAM, 1 TB SSD and NVIDIA Quadro P520 (4 GB GDDR5 dedicated) graphics card. It would easily be able to handle such resource intensive workloads.

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