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The Lord of the Rings Mythology Explained

December 19, 2014

Wallpapers:

If you like the artwork, there are 4k resolution wallpapers of the characters available at Patreon and Subbable

Script:

The Lord of the Rings has lots of different kinds of people: elven people, dwarven people, tree people, half-sized people, even people people.

There's like a million pages of background explaining this world that goes much deeper than the books or the movies, but if you don't want to read it all here's a four minute summary, starting with Wizards:

It's easy to mistake the wizards as humans trained in magic, like elsewhere.

But in the Lord of the Rings, wizards are low(ish) level angels. They're called Istari (get ready for lots of names in this video) and there are five of them -- Sauroman the White, Gandalf the Grey, Radagast the Brown, and the two blue wizards.

Their power comes mostly from being supernatural and not so much from book learnin'.

They're sent (by who? We’ll get to that in a second.) to help the people of world stand against evil -- not wildly successfully either. Sauroman, the leader of the five with a mind of metal and wheels gets corrupted, Radagast, gets distracted by all the pretty nature, the blue wizards just kind of fade into the East -- possibly starting cults of magic and it's only Gandalf that stays true to the quest.

Now, where there's angels there’s a god and in this Universe that's Eru Ilúvatar.

In the beginning there was naught but Eru and the infinite timeless nothing, which is rather boring so he created lots of angels to keep him company.

Ilúvatar 's angels are called the Ainur and are divided into two groups The Valar (Guardians of the world of which there are fourteen or fifteen depending on who you want to count) and their servants The Maiar.

The Wizards are the Istari a subset of the Maiar, which serve the Valar, all created by Ilúvatar.

Ilúvatar and all his angels sang together to make the world. The harmony started out great But there was one Valar named Melkor, and just from the name Melkor, you know what's going to happen, even before learning he's also the smartest, and the most powerful of the angels. And also a bit of a loner.

Melkor didn't want to just be part of the chorus like his dimmer Valar co-workers, he wanted his own song and creations and so his voice became discordant from the others and... created all the suffering and evil in the world.

But Melkor's song also attracted some Maiar to his side including the balrogs. Which means the balrog is a low-level angel making him on the same level of the power org chart as Gandalf: which explains why an old man can hold his ground against a giant lava monster.

Through his discordant singing Melkor also created some of the evil creatures in the world such as the dragons and trolls. Which finally gets us to things that aren't angels.

Other Valar, also made their own non-angelic creations, though in a cooperative spirit with Ilúvatar.

Manwë makes the Great Eagles.

Aulë made the dwarves and his wife Yavanna made all of the animals and plants in the world before capping off that minor task with the Ents, her own race of sentient creatures.

While Ilúvatar seemed happy to leave it to his Valar to make most of the stuff -- he did personally create men and elves which makes them special and kind of above all the other living creatures. (Sorry Dwarves)

And of these two, the men are Ilúvatar 's favorite children: and he show's this by giving men shorter lives than everybody else and also the gift of death? Thanks a lot, Dad. But their short lives set them apart from the other creatures and they aren't tied to the music of creation and the world like everyone else and so are the able to forge their own futures. These qualities make them the get-stuff-done species of middle earth.

Elves, on the other hand, are so connected to the world they're practically made of nature. Same with the Dwarves in their own way, and the Ents of course. These species all but follow the flow of nature and it's partly why the humans have such a hard time getting them to do anything.

Even when faced with armies of Orcs, which brings us to Orcs. Melkor was powerful but couldn't make his own creatures as great as the elves and men and so cheated by corrupting some of them in the beginning and selectively breeding them over the generations into these creatures.

This business Melkor was up to of torturing elves, making monsters, recruiting angels from the other side eventually, but unsurprisingly, led to a war that Melkor loses and got him banished into the void.

All of the conflict in the Lord of the Rings comes long after the epic good vs. evil fight of that universe. Sauron, the Big Bad who caused all of the trouble in these books was just one of the Maiar, though an unusually powerful one, who started his career as Melkor's lieutenant -- after the war he did make a ring to focus his strength, but that's a story for another time.

Last, but not least, we have the hobbits. Even though they seem related to dwarves, what with the living underground and the vertical challenge, hobbits are a subspecies of men. For such an important and pivotal race there is little written of their origin other than the phrase 'related to men.' Turns out with a million pages you still can't talk about everything, just like in a four minute video.

Politics in the Animal Kingdom: Single Transferable Vote

October 27, 2014

Extra: STV Election Walkthrough

Footnotes:

Script:

Queen Lion is looking to make the elections in her animal kingdom more fair. Currently she divides her citizens into ranges each of which selects one representative to go to the jungle council which makes laws for the kingdom.

But her citizens are unhappy, and it's easy to see why: the council is full of monkeys. Of course some of her citizens are monkeys, but not all of them. This council doesn't fairly represent her kingdom.

Queen lion visits one of the ranges to find out what's wrong and how to fix it.

In this range there five monkeys, four tigers, three owls, two lynx and one buffalo. One of each runs for representative and all citizens vote for their own species.

The election rule is that the candidate with the most votes wins, which is the monkey. But it's a pretty unsatisfying result considering that 2/3rds of citizens in this range aren't monkeys and wouldn't vote for monkeys.

This is the same across all the ranges of the kingdom, the monkeys have more votes than anybody else, so they win all the elections, even though they are a minority of the total population. Closer inspection reveals that the independent advisors hired to draw the range boundaries in the first place weren't as independent as they first appeared.

The result is unhappy citizens who don't trust the jungle council to make the fairest laws for all, quite rightly.

Now Queen lion wants to maximize the number of citizens happy with the election results. One way to do that is to abolish the ranges and use a proportional system... ...But her citizens want local representatives.

So Queen lion needs a system that both make her citizens happier by having a more representative council while keeping local elections in place.

After doing a little research she finds out how: Single Transferable Vote.

The big change with STV is that ranges send more than one representative, which may seem weird, but queen lion decides to test it out: she takes three ranges which used to each send one representative and combines them into one bigger range that will send three.

On election day citizens go to the polls and the results in this new range are just the same as they were in the old ranges: 34% for Monkey, 33% for Owl and 33% for Lynx.

But this isn't most votes wins: with STV to figure out the winners take the total votes and divide by the number of representatives needed, in this case 3 which gives 33% as the amount a candidates needs to win.

So all three candidates go to the council -- which accurately represents the citizens in the range.

Whereas under the old system each range would have sent a monkey. Leaving 2/3rd of the citizens without representation. A bigger range with more representatives allows the range to be more proportional.

This test turned out well, but it was also as simple as could be -- now Queen Lion wants to see what happens in a race where not everyone is a winner.

The next big range she tests has five candidates running for office: Gorilla, Tasier, Monkey, Tiger, and Lynx, three of which can be representatives.

Election day comes and goes, and here are the results of citizens first choices:

Tasier gets 5% Gorilla gets 28% Monkey gets 33% Tiger gets 21% Lynx gets 13%

As before, a candidate needs 33% to win. Monkey has that as so is immediately selected as one of the three representatives.

But no one else reached the winning 33% so how are the other two representatives selected?

Step one: get rid of the biggest loser. Sorry tasier -- you really had no chance at all.

Now, when the citizens voted, they could have just put an X next to the candidate they liked most but with STV they can also rank their favorite candidates. This is important because it shows how the election would have turned out if one of the candidates hadn't run.

Tiny and Worried Tasiers would have voted for the big calm gorilla without tasier in the race. So if their candidate can't win, they want their votes to go to Gorilla instead. This pushes gorilla up to 33% and he become the next representative.

Ranking allows citizens to support their favorite candidate without worry -- there's no point in strategizing about how everyone else is going to vote. The system works to maximize voter happiness with the result.

Back to the range: there's still one representative to select, so the next biggest loser is Lynx. His voters don't like simians, but they do think tiger's interests are similar to theirs and so if Lynx can't win they want him to have their votes. Tiger gets reaches 33% and becomes the third and final representative.

The election result looks pretty good especially considering citizens first and second choices.

Now more citizens have a local representative they can feel comfortable approaching, whereas using the old system, everybody gets a monkey.

Lastly queen lion wants know what happens in a range with just two political parties. Under the most-votes-wins systems, multiple candidates from the same party would be a disaster: they'd split their voters and hand the win to their opposition.

Queen lion makes one last test range with 2/3rd tigers and 1/3 gorillas that as before, needs three representatives.

Because with STV citizens rank their candidates there can be more than one candidate running at the same time without any problems.

The tigers run two candidates as do the gorillas.

White tiger becomes the first representative, but what happens next? While tiger seems to be the biggest loser, it's also obvious that he would have gotten way more votes if white tiger wasn't in the race. If a candidate has more votes than they need, like white tiger does, the first step is to give the extra votes to their second choice. This gets tiger to 33% and he becomes the next representative.

If that seems strange, there are two things to consider:

1) If instead the extra votes were ignored, and tiger eliminated then the gorillas would get the remaining two wins, which would obviously not be represent the range.

2) Ignoring these 'extra' votes is punishing citizens who backed the popular candidate, which makes voters start thinking about how everyone else will vote, rather than what they really want. If a candidate gets extra votes in the first place it also means that those who voted for him are a big section of the population and thus fairly should get more representation.

Right: after the extra votes go to tiger, the election finishes as before: Silverback came in last, is eliminated and his voters' second choice is the younger candidate so gorilla gets in. And the results are fair.

Queen Lion has now seen STV work. Whether a range has one party or lots the process is still the same:

Citizens rank their favorite candidates.
Any candidate above the threshold wins immediately,
'Extra' votes go to their next choice.
If no winner, last place is eliminated, and the votes to go their next choice.
Repeat until all the winners are found.

This whole this process is designed to maximize the number of citizens who are happy with the result.

This process gives STV has many advantages over the old, most-votes-wins system:

Citizens can honestly vote for their favorite candidate without worrying about what everyone else is going to do.
It's more proportional. So monkeying with the borders matters less.
Almost all citizens will have a local representative they actually voted for.

In the end Queen lion decides to switch the council's elections to Single Transferable Vote to make a better jungle council for all.

Humans Need Not Apply

August 15, 2014

Script

Every human used to have to hunt or gather to survive. But humans are smart-ly lazy so we made tools to make our work easier. From sticks, to plows to tractors we’ve gone from everyone needing to make food to, modern agriculture with almost no one needing to make food — and yet we still have abundance.

Of course, it’s not just farming, it’s everything. We’ve spent the last several thousand years building tools to reduce physical labor of all kinds. These are mechanical muscles — stronger, more reliable, and more tireless than human muscles could ever be.

And that's a good thing. Replacing human labor with mechanical muscles frees people to specialize and that leaves everyone better off even though still doing physical labor. This is how economies grow and standards of living rise.

Some people have specialized to be programmers and engineers whose job is to build mechanical minds. Just as mechanical muscles made human labor less in demand so are mechanical minds making human brain labor less in demand.

This is an economic revolution. You may think we've been here before, but we haven't.

This time is different.

Physical Labor

When you think of automation, you probably think of this: giant, custom-built, expensive, efficient but really dumb robots blind to the world and their own work. There were a scary kind of automation but they haven't taken over the world because they're only cost effective in narrow situations.

But they are the old kind of automation, this is the new kind.

Meet Baxter.

Unlike these things which require skilled operators and technicians and millions of dollars, Baxter has vision and can learn what you want him to do by watching you do it. And he costs less than the average annual salary of a human worker. Unlike his older brothers he isn't pre-programmed for one specific job, he can do whatever work is within the reach of his arms. Baxter is what might be thought of as a general purpose robot and general purpose is a big deal.

Think computers, they too started out as highly custom and highly expensive, but when cheap-ish general-purpose computers appeared they quickly became vital to everything.

A general-purpose computer can just as easily calculate change or assign seats on an airplane or play a game or do anything by just swapping its software. And this huge demand for computers of all kinds is what makes them both more powerful and cheaper every year.

Baxter today is the computer in the 1980s. He’s not the apex but the beginning. Even if Baxter is slow his hourly cost is pennies worth of electricity while his meat-based competition costs minimum wage. A tenth the speed is still cost effective when it's a hundred times cheaper. And while Baxtor isn't as smart as some of the other things we will talk about, he's smart enough to take over many low-skill jobs.

And we've already seen how dumber robots than Baxter can replace jobs. In new supermarkets what used to be 30 humans is now one human overseeing 30 cashier robots.

Or the hundreds of thousand baristas employed world-wide? There’s a barista robot coming for them. Sure maybe your guy makes your double-mocha-whatever just perfect and you’d never trust anyone else -- but millions of people don’t care and just want a decent cup of coffee. Oh and by the way this robot is actually a giant network of robots that remembers who you are and how you like your coffee no matter where you are. Pretty convenient.

We think of technological change as the fancy new expensive stuff, but the real change comes from last decade's stuff getting cheaper and faster. That's what's happening to robots now. And because their mechanical minds are capable of decision making they are out-competing humans for jobs in a way no pure mechanical muscle ever could.

Luddite Horses

Imagine a pair of horses in the early 1900s talking about technology. One worries all these new mechanical muscles will make horses unnecessary.

The other reminds him that everything so far has made their lives easier -- remember all that farm work? Remember running coast-to-coast delivering mail? Remember riding into battle? All terrible. These city jobs are pretty cushy -- and with so many humans in the cities there are more jobs for horses than ever.

Even if this car thingy takes off you might say, there will be new jobs for horses we can't imagine.

But you, dear viewer, from beyond 2000 know what happened -- there are still working horses, but nothing like before. The horse population peaked in 1915 -- from that point on it was nothing but down.

There isn’t a rule of economics that says better technology makes more, better jobs for horses. It sounds shockingly dumb to even say that out loud, but swap horses for humans and suddenly people think it sounds about right.

As mechanical muscles pushed horses out of the economy, mechanical minds will do the same to humans. Not immediately, not everywhere, but in large enough numbers and soon enough that it's going to be a huge problem if we are not prepared. And we are not prepared.

You, like the second horse, may look at the state of technology now and think it can’t possibly replace your job. But technology gets better, cheaper, and faster at a rate biology can’t match.

Just as the car was the beginning of the end for the horse so now does the car show us the shape of things to come.

Automobiles

Self-driving cars aren't the future: they're here and they work. Self-driving cars have traveled hundreds of thousands of miles up and down the California coast and through cities -- all without human intervention.

The question is not if they'll replaces cars, but how quickly. They don’t need to be perfect, they just need to be better than us. Humans drivers, by the way, kill 40,000 people a year with cars just in the United States. Given that self-driving cars don’t blink, don’t text while driving, don’t get sleepy or stupid, it easy to see them being better than humans because they already are.

Now to describe self-driving cars as cars at all is like calling the first cars mechanical horses. Cars in all their forms are so much more than horses that using the name limits your thinking about what they can even do. Lets call self-driving cars what they really are:

Autos: the solution to the transport-objects-from-point-A-to-point-B problem. Traditional cars happen to be human sized to transport humans but tiny autos can work in wear houses and gigantic autos can work in pit mines. Moving stuff around is who knows how many jobs but the transportation industry in the United States employs about three million people. Extrapolating world-wide that’s something like 70 million jobs at a minimum.

These jobs are over.

The usual argument is that unions will prevent it. But history is filled with workers who fought technology that would replace them and the workers always loose. Economics always wins and there are huge incentives across wildly diverse industries to adopt autos.

For many transportation companies, the humans are about a third of their total costs. That's just the straight salary costs. Humans sleeping in their long haul trucks costs time and money. Accidents cost money. Carelessness costs money. If you think insurance companies will be against it, guess what? Their perfect driver is one who pays their small premium but never gets into an accident.

The autos are coming and they're the first place where most people will really see the robots changing society. But there are many other places in the economy where the same thing is happening, just less visibly.

So it goes with autos, so it goes for everything.

The Shape of Things to Come

It's easy to look at Autos and Baxters and think: technology has always gotten rid of low-skill jobs we don't want people doing anyway. They'll get more skilled and do better educated jobs -- like they've always done.

Even ignoring the problem of pushing a hundred-million additional people through higher education, white-collar work is no safe haven either. If your job is sitting in front of a screen and typing and clicking -- like maybe you're supposed to be doing right now -- the bots are coming for you too, buddy.

Software bots are both intangible and way faster and cheaper than physical robots. Given that white collar workers are, from a companies perspective, both more expensive and more numerous -- the incentive to automate their work is greater than low skilled work.

And that's just what automation engineers are for. These are skilled programmers whose entire job is to replace your job with a software bot.

You may think even the world's smartest automation engineer could never make a bot to do your job -- and you may be right -- but the cutting edge of programming isn't super-smart programmers writing bots it's super-smart programmers writing bots that teach themselves how to do things the programmer could never teach them to do.

How that works is well beyond the scope of this video, but the bottom line is there are limited ways to show a bot a bunch of stuff to do, show the bot a bunch of correctly done stuff, and it can figure out how to do the job to be done.

Even with just a goal and no example of how to do it the bots can still learn. Take the stock market which, in many ways, is no longer a human endeavor. It's mostly bots that taught themselves to trade stocks, trading stocks with other bots that taught themselves.

Again: it's not bots that are executing orders based on what their human controllers want, it's bots making the decisions of what to buy and sell on their own.

As a result the floor of the New York Stock exchange isn't filled with traders doing their day jobs anymore, it's largely a TV set.

So bots have learned the market and bots have learned to write. If you've picked up a newspaper lately you've probably already read a story written by a bot. There are companies that are teaching bots to write anything: Sports stories, TPS reports, even say, those quarterly reports that you write at work.

Paper work, decision making, writing -- a lot of human work falls into that category and the demand for human metal labor is these areas is on the way down. But surely the professions are safe from bots? Yes?

Professions

When you think 'lawyer' it's easy to think of trials. But the bulk of lawyering is actually drafting legal documents predicting the likely outcome and impact of lawsuits, and something called 'discovery' which is where boxes of paperwork gets dumped on the lawyers and they need to find the pattern or the one out-of-place transaction among it all.

This can all be bot work. Discovery, in particular, is already not a human job in many firms. Not because there isn't paperwork to go through, there's more of it than ever, but because clever research bots sift through millions of emails and memos and accounts in hours not weeks -- crushing human researchers in terms of not just cost and time but, most importantly, accuracy. Bots don't get sleeping reading through a million emails.

But that's the simple stuff: IBM has a bot named Watson: you may have seen him on TV destroy humans at Jeopardy — but that was just a fun side project for him.

Watson's day-job is to be the best doctor in the world: to understand what people say in their own words and give back accurate diagnoses. And he's already doing that at Slone-Kettering, giving guidance on lung cancer treatments.

Just as Auto don’t need to be perfect -- they just need to make fewer mistakes than humans, -- the same goes for doctor bots.

Human doctors are by no means perfect -- the frequency and severity of misdiagnosis are terrifying -- and human doctors are severely limited in dealing with a human's complicated medical history. Understanding every drug and every drug's interaction with every other drug is beyond the scope of human knowability.

Especially when there are research robots whose whole job it is to test 1,000s of new drugs at a time.

Human doctors can only improve through their own experiences. Doctor bots can learn from the experiences of every doctor bot. Can read the latest in medical research and keep track of everything that happens to all his patients world-wide and make correlations that would be impossible to find otherwise.

Not all doctors will go away, but when doctor bots are comparable to humans and they're only as far away as your phone -- the need for general doctors will be less.

So professionals, white-collar workers and low-skill workers all have something to worry about.

But perhaps you're still not worried because you're a special creative snowflakes. Well guess what? You're not that special.

Creative Labor

Creativity may feel like magic, but it isn't. The brain is a complicated machine -- perhaps the most complicated machine in the whole universe -- but that hasn't stopped us from trying to simulate it.

There is this notion that just as mechanical muscles allowed us to move into thinking jobs that mechanical minds will allow us all to move into creative work. But even if we assume the human mind is magically creative -- it's not, but just for the sake of argument -- artistic creativity isn't what the majority of jobs depend on. The number of writers and poets and directors and actors and artist who actually make a living doing their work is a tiny, tiny portion of the labor force. And given that these are professions that are dependent on popularity they will always be a small part of the population.

There is no such thing as a poem and painting based economy.

Oh, by the way, this music in the background that your listening to? It was written by a bot. Her name is Emily Howel and she can write an infinite amount of new music all day for free. And people can't tell the difference between her and human composers when put to a blind test.

Talking about artificial creativity gets weird fast -- what does that even mean? But it's nonetheless a developing field.

People used to think that playing chess was a uniquely creative human skill that machines could never do right up until they beat the best of us. And so it goes for all human talent.

Conclusion

Right: this might have been a lot to take in, and you might want to reject it -- it's easy to be cynical of the endless, and idiotic, predictions of futures that never are. So that's why it's important to emphasize again this stuff isn't science fiction. The robots are here right now. There is a terrifying amount of working automation in labs and wear houses that is proof of concept.

We have been through economic revolutions before, but the robot revolution is different.

Horses aren't unemployed now because they got lazy as a species, they’re unemployable. There's little work a horse can do that do that pays for its housing and hay.

And many bright, perfectly capable humans will find themselves the new horse: unemployable through no fault of their own.

But if you still think new jobs will save us: here is one final point to consider. The US census in 1776 tracked only a few kinds of jobs. Now there are hundreds of kinds of jobs, but the new ones are not a significant part of the labor force.

Here's the list of jobs ranked by the number of people that perform them - it's a sobering list with the transportation industry at the top. Going down the list all this work existed in some form a hundred years ago and almost all of them are targets for automation. Only when we get to number 33 on the list is there finally something new.

Don't that every barista and officer worker lose their job before things are a problem. The unemployment rate during the great depression was 25%.

This list above is 45% of the workforce. Just what we've talked about today, the stuff that already works, can push us over that number pretty soon. And given that even our modern technological wonderland new kinds of work are not a significant portion of the economy, this is a big problem.

This video isn't about how automation is bad -- rather that automation is inevitable. It's a tool to produce abundance for little effort. We need to start thinking now about what to do when large sections of the population are unemployable -- through no fault of their own. What to do in a future where, for most jobs, humans need not apply.