[Leimi]

yeah I get the benefits. And yeah the "repair" argument I agree, good luck finding a bad stick :)

The real frustrating thing as for now in the real world is, there is an extremely low number of laptops with soldered ram that offers 64 GB. And the few that do, charge an absurd amount of money for it.

With socketed ram, I can:

- buy the cheapest built-in config of a laptop

- then buy the RAM I currently need on my own, often saving a few hundreds bucks just doing that

- then, in a few years, buy some new RAM again, when I need it, if I need it, instead of having to buy a whole new laptop.

That's how I went with thinkpads during 15 years. Now I have to pay 500$ more to be a bit future proof. If the manufacturer offers it. Double that if you want a mac.

So, still today, I'm 100% taking socketed ram instead of soldered one.

[thomastjeffery]

I can't imagine actually using 64GB of RAM on a laptop.

How many concurrent VMs would I ever want to run anyway?

If I ever go over 16GB, and actually notice it swapping on an NVMe drive... why not just remote to a real workstation?

[Nullabillity]

I can't imagine living with a workflow that regularly requires me to remote into servers to get shit done. Life is miserable enough as it is.

[Leimi]

I guess we use our machines in different ways :)

And I have a few use cases where 32 Gb is limiting. So I don't want to buy a brand new machine stuck at something that is, sometimes, already not ideal. And well, the usual next step is 64 Gb.

[sireat]

I routinely use 64GB on one of my laptops.

Load a "largish" dataframe you will wish for even more RAM.

Even on smallish dataframes with say 20-30GB usage it can be convenient to have a copy near by.

[RulerOf]

16 gigs for the Docker VM

24 for chrome

8 for electron

10 for OS caching

4 for shared video memory

...and 2 that sit unused to let you know that you don't need any more to get the job done.