# 22 Fun Stuff

library(rtemis)
  .:rtemis 0.8.0: Welcome, egenn
[x86_64-apple-darwin17.0 (64-bit): Defaulting to 4/4 available cores]
Documentation & vignettes: https://rtemis.netlify.com

## 22.1 Harmonograph

Want to simulate a harmonograph?

mplot3.harmonograph()

## 22.2 Guitar frets

Looking for a guitar fretboard cheatsheet?

mplot3.fret()

## 22.3 Attack Decay Sustain Release

Want to learn about music synthesis and envelope generators?

mplot3.adsr()

## 22.4 Delay Calculator

I’m setting up my delay effects - how long, in milliseconds, is a quarter dotted note at 120 beats per minute?

delayTime(bpm = 120, note = "1/4D")
[1] 750

## 22.5 Magic Eightball

You’re a little tired, a little bored, a little busy, a little hungry. Should you go out tonight?

eightball("Should I go out tonight?")
   Should I go out tonight?
>> Signs point to yes. 

On a more serious note, Machine Learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption is limited by the level of trust afforded by given models. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert. In reality, the optimal learning strategy may involve combining the complementary strengths of man and machine (Gennatas et al. 2019). Unfortunately, there are often times when no man or machine can predict a question at hand. For those questions, there is magic eightball:

eightball("Will we even be half ready for the AI apocalypse?")
   Will we even be half ready for the AI apocalypse?
>> Reply hazy, try again. 

…and there we have it.

### References

Gennatas, ED, JH Friedman, LH Ungar, R Pirracchio, E Eaton, L Reichman, Y Interian, et al. 2019. “Expert-Augmented Machine Learning.” arXiv Preprint arXiv:1903.09731.