Principles of Communications, 2018/2019 - Week "1" 24&26.10.18

This week, course started with brief Intro (what's in course)

Then skip to last lecture on:
Systems (will revisit at end of term)

Then:
Routing 1 - intro + fibbing (hybrid central/distributed inter-as routing)

Monday 29th, will start on BGP...

white space graphs

we often form graphs by addings edges to a collection of vertices, or vertices and edges - we can also form graphs by moving (rewiring) ends of edges from one node to another, or removing edges and nodes.

how about we form graphs by cutting holes in a piece of paper (or by dropping polygonal shapes on a surface)? they can overlap....

what sort of graphs do you get when you just make them out of interstial space?

Public Understanding of Machine Learning

"I understand we understand one another" is a great line from the Philadelphia Story - one fab film (also made as a great musical).

So machines start to understand us, at least statistically, programmes create models that may or may not have predictive value about our behaviour (film viewing, travel preferences, dating, etc etc).

But do we understand the machines (or do we, as Pat Cadigan said in the prescient novel Synners, need to "change for the machines"? (including 50 pence bits, as she implied :-)

David Spiegalhalter has spent a lot of time working out how to convey Uncertainty to the non-technical person. Now we have a more complex task

not just mean, variance, confidence limits etc, but also

principle components
linear regression
k-means
bayes
random forest
variational approaches
convolutional neural networks
GANs

etc etc

What hope have we for this? What fear do we have of that? All is blish, all is blush, all is plash.

The nine circles of hell for Computer Science and the Law

Nine Circles of Hell for Computer Science...
in the dock, with apologies to Dante

These are (in order):

1. Cloud (jurisdiction)
2. Things (liability)
3. ML (explicability)
4. Blockchain (privacy)
5. Compliance (cybersecurity)
6. Robots (safety)
7. Singularity (upload)
8. Legol(*) (sustainability)
9. QC (probable cause)


* as with John Cleese interviews with his therapist, where moving house is more traumatic than divorce
and only just after loss of a loved one and losing a limb, I think explaining computer science for law
is almost as hard as explaining law to computer scientists, and only marginally easier than
explaining Quantum Computing...

1. Cloud (jurisdiction)

I don't think we're in Kansas any more...

2. Things (liability)

The thing is, this is all your fault.

3. Machine Learning (explicability)

I told you so

4. Blockchain (privacy)

"You can't fool me, there ain't no Sanity Claus"

5. Compliance (cybersecurity)

You can't prove a system secure, only that it is (now) insecure,
so how do you claim compliance (see 1,2,3,4,9)

New angle - Privacy Enhancing Technologies are pretty hard to explain, too - if they are used as part of compliance, how can you tell?

6. Robots (safety)

"I thought you said 'a robot shall not inure a human being or allow one to come to arms through inaction".

7. Singularity (upload)

"where have all the people gone, today"

8. Legol(*) (sustainability)

see also
https://www.cl.cam.ac.uk/~jac22/emergence.pdf

9. Quantum Computing  (probable cause)

you are trying to persuade a jury
that someone is guilty
beyond a shadow of a doubt

here are four possible Quantum  Computational examples of algorithms:
https://en.wikipedia.org/wiki/Runaway_Jury
https://en.wikipedia.org/wiki/12_Angry_Men_(1957_film)

detectovation - 3 writers trying their hand

I recently read the latest "Robert Galbraith" Cormoran Strike (#4) novel (Lethal White)
and the latest Stephen King's Mr Mercedes linked novel (#4, The Outsider) and am looking forward to getting Kate Atkinson's latest novel, but have read the 4 Jackson Brodie Detective novels.

What's common? well aside from these being detective novels, by very well known writers, they are also all writing outside their main (or at least previously known-for) genre, which are respectively Fantasy (JK Rowling/Harry Potter), Horror (Stephen King's Shining, It, Carrie, you name it) and Kate Atkinson's non-genre (e.g. Behind the Scenes) but also Sci-Fi tinged tales (Life-after-life could be seen as in the same genre as Slaughterhouse Five or Tale for the Time Being).

It's interesting because all three are fantastic writers- imagination? in gallons. plot? incredible (but believable). readable? don't be silly!

What's interesting is how they fare in what is often a tightly stylized convention-bound genre.

They all do well on plot.
They are all very readable.

However, your mileage varies on characterisation, and for me, what I found most surprising was that this is where Stephen King, for me, was most successful. Both Hodges and Gibney are amazingly drawn, in all the books. Whereas Strike is great, but other characters are a little thin. Similarly, while Brodie is a wonderful creation, I wasn't grabbed by other people walking on and off the scene.

This is not to knock the books - they are all great reads, and by writers on top of their game, style and so on. They are all page turners. Buy or borrow them all. Unless you hate detective fiction! Then buy the writers' other books, which are also fantastic!