What fields are currently pre-eminent and what fields are going to be in the near future?

Please give some reasoning as to your assumption(s).

There must be something?

Math, now and for ever. Queen of both art and science.

Agreed, but what about genetics, or an engineering field?

I'd say Developmental Biology will be big with regenerative Medicine entering the scene

Certainly with the rise in so called 'biohacking', a renew interest in biology.

Anything genetic

With the research into longevity?

Machine learning and data science are super hot right now.

In your opinion, what is the best programming language for machine learning?

Haskell

Good pick, user.

Any others?

I'm a biofag for reference, but EE will always be relevant now and in the near future. I'd say it's the safest choice because it gives you a background in computer science as well as "real" engineering with electronics etc. Automation is going to be the biggest thing imo in the near future. Also .

Bioinformatics is already pretty big and is used for all types of biological research. Regenerative medicine and synthetic biology are also decent but these lab positions are often filled to the brim because there's a huge demand by life science graduates. "Biohacking" is mostly a normie meme and is retarded for many reasons that multiple top researchers have already explained. Unfortunately this is the result of CRISPR being popularized to a ridiculous degree.

Materials science is also good from my understanding if you want something more chemistry oriented, although don't take this at face value. That's it off the top of my head for now.

The first things that come to mind are Biophysics, biomath, computational life sciences, ecosystem engineering/agroecology call it a meme but I see biosemiotics or something similar becoming really big as a bridge between phenomenology and the life sciences

Stop trolling. Some innocent soul might believe you.

No one ever can predict that.

" Complex System Science " which contain the following
-Theory of pattrens
-Optimization
-Algorithmic information theory
-Decision and game theory
-Nonlinear Dynamics
-Automata Networks

>Haskell
>not forcing python into absolutely everything no matter what
what does it feel like to be beta, user?

Why is technology in there anyway? As far as I can tell the only aspects of technology that belong in that grouping fall under one of the other three.

It's a public relations acronym for educational recruitment purposes. Otherwise STEM is a virtually meaningless grouping. I'm always amused by how easily people follow the STEM meme like it's their dogma

I would say that math -> science -> engineering is a valid grouping that serves as a tool for getting things done as effectively as possible, even if the term itself is mainly for marketing.

Quantum computing soft/hardware development
Photonic computers
Wireless tech (charging, internet, globally)
Medical device miniaturization
Automation
Food growing
Water purification
Green energy
Non-kinetic weapons

At the end of that chain is technology, brainlet

Not really. Technology is an output of engineering but doesn't seem to represent a field of study in its own right.

Thank you, very informative.

The real answer is obviously LISP.

So, an explosion in the bio sector? Not too surprising, maybe we will go cyberpunk.

Really sick of Veeky Forums pedants, you can't predict:
>What fields are currently pre-eminent
What are you incapable of reading, or something?

Ok yes, but your chain represents the workflow of every device in our civilization.

That's a major field already.

That's true.

This. Stats and informatics is your friend in the near future at least.

Then who's the king? By corollary, the jack?

Agreed,

I didn't know this was /b/?

>python purism
My man.

C is King, followed by C++ the Crown Prince.

The only fields left in 2050 will be Machine Learning and maybe the arts (including Math).

C++ if you want to actually create new ML code.

Python if you just want to run Caffe2 on some data set you have.

Aerospacefag, people are going absolutely fucking bonkers over data-driven methods. It has applications in literally any sort of mechanics framework, as well as statistics, finance, you name anything that has trends or discoverable governing equations and data-driven methods have an application. It's obviously being driven by the explosive investments into computing power that governments are making, and this is only going to continue to grow. Machine learning is a small (but important) portion of this field, but ROMs and inverse problems are on the rise right now.