thesis statement 'not more defence rather, this aynrand thing'
have to define these things: topic,
If you knew someone who had a B.E. ('systems' engineering, with a 'mechatronics' major), a B.Sc. with an applied math major, an M.Phil. in statistical signal processing from the EE dept. of a defence affiliated school and a year and a half experience in 'analysis' kind of work with a defence industry supplier (radar). This person's two main complaints about the mphil were that their ee wagon was wading naively into ground already well covered by physicists and ai people, and that ai/cs was expanding out to annex the prbolbems that his work might have looked to address. now wanted to not become a cs or phys ..
Q1 defence and why i don't need it is cos..
Q2 What i thought was important to do as informs my actual interest in eng etc like career aims i guess leads to algo not phys cs i guess? i mean we were outcomes focused now dunno
Q3 What's not consumed by CS and why not and how to find other things like that
Technology is technique knowlege. Where science inquires into nature, engineering research inquires into methods. I once I dont much care about applying technology I want to make technology and that should have been a sign I was more interested in research than engineering proper.
The things that for a while we could be sure CS didn't know about: Noise, uncertain data, optimal dynamic (continuous, analog) controllers...
warning: detecting high levels of spinoff - remember, no emotion, no spinoff, no self-image - a practical problem. No buzzwordfeels either.
So is robotics over? It doesn't have to be - it's got so much interest that there's huge supply of robotics innovators, and if the demand for robotics innovation goes down just a little then you won't be able to make any living in doing that.
the ol medpod. signals and algos for medpods. Cochlear is a bit like that because it's got to be embedded, and it's all about embedded processing. Cochlear is kind of 'safe from cs'
Optimal control, Kalman filtering and ,, are all the same thing, calculus of variations applied to some posed problem giving out a policy. The posing of the problem is one thing from one time in each field, the applying of the policy by having to model the system another, etc.