Basically the same remarks as for university, just 10 times more useless, see also: Section "Motivation".
Singapore's Remote-Controlled Cyborg Insects by Vice Media (2018)
Source. By Dr. Hirotaka Sato from Nanyang Technological University Singapore.
Basically a mini-Constellation.
Specific type of Josephson junction. Probably can be made tiny and in huge numbers through photolithography.
Standard from 2011: abcnotation.com/wiki/abc:standard:v2.1
No bend/vibratto/slides :-(
Multitrack volatile: abcnotation.com/wiki/abc:standard:v2.1#multiple_voices
Some of the earlier computers of the 20th centure were analog computers, not digital.
At some point analog died however, and "computer" basically by default started meaning just "digital computer".
As of the 2010's and forward, with the limit of Moore's law and the rise of machine learning, people have started looking again into analog computing as a possile way forward. A key insight is that huge floating point precision is not that crucial in many deep learning applications, e.g. many new digital designs have tried 16-bit floating point as opposed to the more traditional 32-bit minium. Some papers are even looking into 8-bit: dl.acm.org/doi/10.5555/3327757.3327866
As an example, the Lightmatter company was trying to implement silicon photonics-based matrix multiplication.
A general intuition behind this type of development is that the human brain, the holy grail of machine learning, is itself an analog computer.
Unfortunately, all software engineers already know the answer to the useful theorems though (except perhaps notably for cryptography), e.g. all programmers obviously know that iehter P != NP or that this is unprovable or some other "for all practical purposes practice P != NP", even though they don't have proof.
And 99% of their time, software engineers are not dealing with mathematically formulatable problems anyways, which is sad.
The only useful "computer science" subset every programmer ever needs to know is:
- for arrays: dynamic array vs linked list
- for associative array: binary search tree vs hash table. See also Heap vs Binary Search Tree (BST). No need to understand the algorithmic details of the hash function, the NSA has already done that for you.
- don't use Bubble sort for sorting
- you can't parse HTML with regular expressions: stackoverflow.com/questions/1732348/regex-match-open-tags-except-xhtml-self-contained-tags/1732454#1732454 because of formal language theory
Funnily, due to the formalization of mathematics, mathematics can be seen as a branch of computer science, just like computer science can be seen as a branch of Mathematics!
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