I've been using Linux since the late 90s as well. And I have other OS's as well - mostly for work - XP/Win7/Win 10 and various flavors of OSX. My kids machines runs windows simply because of steam and minecraft bedrock. Every now and then I have to turnn off copilot stuff that turns on because of updates, but other that, windows 11 has been ok. I guess none of the kids use those machines for anything other than gaming - they have school chromebooks for actual work.

I however was handed down an older 2017 macbook pro with the cursed touchbar. Apple doesnt support it anymore but the hardware is (on paper) good enough for me. I can't get the wifi to work properly or the touch bar to work. Suspend and resume doesn't work. I've tried many linux flavors. This is not a gripe against Linux but against Apple, their T1 chip and their refusal to help open source community. How many of these good machines are going to get discarded? I've heard of a lot of people ditching older computers and buying new ones because of Microsoft's win 11 resource requirements. What a waste.

Besides an academic exercise, whats the use of chatbots? My life isn't incomplete because I lack one. I doesn't help me. Yeah we can talk about chatbot based interfaces. But we can also design user interfaces better. And if the purpose of such interface is to get stuff done, then the task is more about understanding and doing things rather than having a conversation. Really, who has the time to have a conversation with AI?
Is this yet another way to make people obsolete in a race to the bottom?

I love R and Python. However, both of them choke on big data sets. What they need is an in-built mechanism to store data on disk rather than in-memory. There are some really convoluted ways of doing this..but then dont always work with modeling packages that weren't written with the convoluted approach you are taking, in mind. So, if the base language has the ability to store object on disk, say with a simple flag, and its transparent to the rest of the system, most downstream libraries/packages would still work.

ff package in R is a good approach..maybe that should be adopted as the memory model for R.

I hate to say this but maybe R/Python can learn something from SAS here.

Apache Mahout is based on a Machine Learning using MapReduce paper by Andrew Ng (Stanford)

Or what are your interests? CS is a huge field and you probably like something specific to bother going for a Masters.

Also, almost every large company out there working on X (X being their area of specialization) needs CS people these days in R&D (and not just IT). So don't limit your search to Tech companies. Look at Financial Services, Healthcare, Media, Marketing etc. Since it's your first job, pick up the Fortune 500 list of companies and see if something excites you. A good majority of them have R&D depts.

And I really hope you are prepared to move and aren't stuck to one place geographically. If you want to solve interesting problems and not do mind-numbing work, use your CS degree to it's fullest. Don't go for IT career.

Or it might be a semi-april fools joke...you know we are six month out and six month in from fools day :)

well..M&A deals are usually not all that they are touted about anyways. The only parties that actually benefits from M&As are the investment banks and the lawyers. Everyone else loses. Including the 2 merging/acq firms. So, if high testosterone in CEOs causes the M&A deals to fall through, so be it.

Production side: I would agree. However statistical differential equations? SAS is good for predefined "statistical analysis", not for solving partial differential equations. Almost all mechanical problems in aerospace (read fluids, solids, thermal, electro) are expressed as partial differential equations. solutions of these (baring a few special cases) require numerical methods. The most common of these methods are finite element, finite difference and finite volume.
And each one of these has it numerous "schemes" for solving a particular class of PDE. The choice of scheme/method depends on the problem at hand. You can use a prepackaged tool like Fluent/Gambit. But that limits you to the limitations of those packages. Need anything cutting edge, or applicable to a special case, you need to program it yourself (c/c++/fortran). Most design houses have tons of legacy code that they build upon and add modules to deal with their specific problem. A lot of these run on linux clusters or unix big irons. I don't think they use gcc though. For performance sake most use proprietary compilers (eg pgc, icc etc). But no SAS.

Now, on the control systems side, most researchers use matlab, but most of the implementation is done using imbeded C or ADA.

As for SAS, they do now support freeware aka Linux.
I have personally notice a sense of unease when SAS employees are asked about R. They are quick to dismiss it claiming the usual FUD and then change the topic. It is quite amusing actually. Happens everytime.

FTA
"I think it addresses a niche market for high-end data analysts that want free, readily available code," said Anne H. Milley, director of technology product marketing at SAS. She adds, "We have customers who build engines for aircraft. I am happy they are not using freeware when I get on a jet.""

Seriously, does this person know what she is talking about?

1. Yes, CFD and Structural Analysis software is increasingly written using open source tools and run on open source OS (Linux running on clusters)

2. SAS is not used to design any part of the aircraft.

I have noticed SAS uses the same kind of FUD to counter R as M$ uses to counter Linux.