Let's make more self-driving mini-vehicles

I think there should be not only self-driving cars, but also self-driving segways, unicycles, bicycles, and more, to solve the last-mile problem.

The last-mile problem is this: when people take public transport, they can't get to exactly where they want to go, and must walk the last mile. This sometimes deters people from using public transport. There has been many solutions:

• Just walk.
• Ride-sharing bicycle/scooter/unicycles.
• Carry the bicycle along on the public transport.
• Give up and drive a car.

Why?

The main problem with ride-sharing are two:

1. Once they go out, it's hard to get them back to their stations. People like to just toss them anywhere.
2. Even if people park them nicely, it's still hard to maintain a balance of vehicles at the stations. Some stations lose bikes on average, while others gain.

The first problem is essentially the last-half-mile problem, and can be solved by adding many small stations, but that exacerbates the second problem, since each station has so few vehicles that a small fluctuation in supply and demand would completely fill or drain a station.

New High Tech for art

This post reviews many AI tech that would be useful for artists. As a preview of what's inside:

Wait no!

Right...

A collection of beautiful stories about mechanical life

The purpose of a system is what it does.

-- Stafford Beer

What do you mean? What are you doing? You mean what you do...

I mean what I do and I do what I mean.

This post is a collection of stories that made me lose self-consciousness for a bit.

Mechanical life

Theseus (maze rat) of Claude Shannon

More pictures here.

Thoughts

If an embryo of two cells can be separated into two embryos, from which twins can develop, can this be continued more? So we get triplets, fourplets, fiveplets, etc.
And if that is so, would they have shorter lifespans due to cell division shortening the telomeres?

• Race against the machine
• Race with the machine
• Race into the machine
• Race of the machine

What would happen if sex organs are plug-and-play devices?

 - Well for starters it'd be pretty horrific if someone loses their vagina during pregnancy.
 - Maybe not so much. Hospitals would have emergency vaginas for that. Or just do cesarian.

1. All models are wrong, but some are useful. ---- George E. P. Box
2. Ethics are models of the world. ---- One possible stance of ethics 
3. All ethics are wrong, but maybe some are useful. ---- Conclusion

Susan Blackmore's Theory of the Self

Susan Blackmore is a scientist who is most famous for studying memes, with the book The Meme Machine (2000). It's a bit outdated at this point though. She's also a skeptic in debunking some pseudoscience.

I'll start with two videos:

Memes and Tremes

Susan Blackmore studies memes: ideas that replicate themselves from brain to brain like a virus. She makes a bold new argument: Humanity has spawned a new kind of meme, the teme, which spreads itself via technology -- and invents ways to keep itself alive

Living Without Free Will

When I say that consciousness is an illusion, I do not mean that consciousness does not exist. I mean that consciousness is not what it appears to be. If it seems to be a continuous stream of rich and detailed experiences, happening one after the other to a conscious person, this is the illusion.

Clenes and Genes: Evolution of clay and the genetic takeover

This post is heavily based on Tim Tyler's page. It has lots of dead pictures, so view them on the Internet Archive if you see them.

Genes are not the only thing that can copy themselves. Computer virus, RNA, protein virus (prion), and chain mails, they all can.

The idea of non-gene replicators is not new. Richard Dawkins proposed memes in The Selfish Gene (1976), and Graham Cairns‑Smith proposed clay-genes (clenes?) in The origin of life and the nature of the primitive gene (1966). Genes and memes are getting all the popularities, but clenes aren't, so I'll summarize clene theory. A detailed explanation is here.

Overview of clenes and genes

First we check the 1966 paper's abstract:

Life on earth evolved through natural selection from inorganic crystals.

During the formation of a crystal, certain kinds of lattice imperfections usually replicate as a necessary part of the crystallization process.

... the primitive genographs were patterns of substitutions in colloidal clay crystallites. (The theoretical information density in such a crystallite is comparable to that in DNA.)... A gradual “take-over” of the control machinery by organic macromolecules—a genetic metamorphosis—is then considered to have occurred.

Let's Read: Mind Children (1988) by Hans Moravec

This book is half outdated and half amazing. The outdated parts are where he talked about the "latest" advances in AI and robotics, such as the amazing robots that could move across a cluttered room in just 5 hours! (and fails 1/4 of the times). This is why I skipped most of the first 3 chapters.

One great thing I found in the book is a very poetic description of a "Bush Robot" which can be best explained by ponies:

Bush Robot Scootaloo

Fun Stuffs: Dog metacognition, Tarski used drugs, Soul Machine babies, FarmBots

Dogs know when they don't know

DogStudies lab... have shown that dogs possess some "metacognitive" abilities -- specifically, they are aware of when they do not have enough information to solve a problem and will actively seek more information... a test in which a reward (food/toy) is placed by one researcher behind one of the two fences while another researcher held the dog. They found that the dogs looked through gaps in the fences significantly more often when they had not seen where the reward was hidden.

 Amusingly, looking through the gaps didn't help sometimes.

The researchers theorize that... the dogs get so excited about finding the reward, that they cannot stop themselves from approaching the closest fence even when they have seen that the reward is probably not there.

Michal Kosinski's researches, and manipulation of human behavior

Michal Kosinski's research papers.

First gonna list the two papers of Kosinski in 2013 that generated lots of talking.

Private traits and attributes are predictable from digital records of human behavior (2013), by Michal Kosinski, David Stillwell, and Thore Graepel.

... Facebook Likes... predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender... dataset of over 58,000 volunteers... 

Manifestations of user personality in website choice and behaviour on online social networks (2013), Michal Kosinski et al.

... a sample of over 1/3 million users... their website choices and Facebook profile features, relates to their ... standard Five Factor Model personality questionnaire. 

Wait... DEVIANTART???

6 tech problems that every lawyer should think about

I wrote an email to an acquaintance who is a lawyer, advising them on the most pressing issues that a lawyer should deal with in a world that's changing quickly by AI, cryptocurrency, and some other technologies. Here's the edited version of it.

Have you studied more about AI? Kai-fu Lee wrote a new book AI Superpowers, and it is worth a read. You could read and watch a presentation here, and an interview with Wharton here.

There will be a very strong market for lawyers proficient in legal issues around AI and other emerging technologies, and I think you can benefit from learning more. Here are some problems for you to think about:

1. Income inequality is increasing more and more in the world due to AI. Read a piece by Kai-fu Lee to see why. How should the laws be changed so that those who lose their jobs won't sink into poverty? Universal Basic Income? Free education? Unemployment benefits?
2. If a self-driving car kills someone, who are legally responsible?
3. If a self-driving car senses that the brakes failed and there is a group of people walking in front, should it crash into the crowd, killing 3, or crash into the side of the road, killing 1 in the car?
4. How would the laws treat bitcoins and other cryptocurrencies?
5. What are the legal tasks that AI can perform? What would the lawyers do instead? Watch this TED talk. There are already companies like Kira that do lawyer work with AI, and their capabilities would only grow and grow.
6. Algorithmic discrimination: what to do where the algorithms create discrimination? See this and this.

Summary of Elon Musk's projects

This post summarizes Elon Musk's projects: SpaceX, Hyperloop, Tesla, Neuralink, OpenAI. It summarizes from the series from Wait But Why.

SpaceX makes Mars spaceships and other space things, Tesla makes electric cars. Neuralink makes BMI (brain-machine interface).

Let's watch: ColdFusion videos

Today we'll just watch a bunch of videos.

The Strange Story of the Mp3 Player (begins at 1:50)
Portable music players were invented in 1979 by Kane Kramer and the way it distributes music without the internet was basically transmitting over the telephone-net at terminal vending machines in bars and music stores and such. It went bankrupt though.
Saehan made MPMan in 1998. RIAA sued Diamond Multimedia in 1998 over its MP3 player but lost, and this very publicized case made MP3 players popular. iPod, 2001, made it super popular.
Kramer got acknowledged as original inventor of iPod by Apple for some legal reasons.

Let's read: Norvig's AI, chap 24, 25, 26, 27

Continuing from last post.

Chapter 24: Perception

This chapter is about feelings, or how to sense the world through sensors. It's too engineering for me so I skipped it.

Chapter 25: Robotics

This chapter is about robotics, actuators, or how to actually move around in the world. This is about the most traditional and engineering part of the textbook, and quite out of my part, so I'll skim it as much as I skimmed technical stuff in mechanical engineering during my study of Newtonian physics.

My favorite part from the chapter is a game:

Exercise 25.11: pretend to be a robot! A game for people from kindergarten to PhD! 

I can think of a few variations on this game: First, to make communication strictly minimal, players should only communicate through text messages and webcams. Second, instead of one person playing the brain, why not use two? One for each hemisphere! The left brain can only see the right eye and control the right hand, and vice versa. Then there will be six players. 

And we can even imagine a game of epiphenomenon.

Wait a minute, this sounds just like specialization...

Let's read: Norvig's AI, chap 22, 23

Continuing from last post.

Chapter 22-25 are about interactions with the environment:

• 22 is about reading and 
• 23 is about writing. 

Listening and speaking are not touched upon, but it's not a problem, considering that current technologies for speech-to-text and text-to-speech are pretty much perfect.

• 24 is about feeling (perception) and 
• 25 is about moving (robotics).

Let's read: Norvig's AI, chap 3

I'm tired of Norvig's AI now. It's too long. Much better if I can just refer to specific chapters of it when I need to get an introduction to a particular topic, rather than reading it in one go.
I will just post reading notes from what I've already accomplished.

---

Continuing from last post.

Chapter 3-6 are about solving given, well-defined problems by various kinds of searching. It is quite basic algorithmic stuff. There's no learning yet, and the agent can't improve itself.

Let's read: Norvig's AI, chap 2

Continuing from last post.

Chapter 2 overviews the idea of a rational agent: agents, environments, rationality, and some basic designs.

Agent

An agent in an environment receives percepts from sensors, and acts by actuators. Mathematically, we can model it as an agent function:
\[\text{Agent}: \{\text{Percept}\}^* \to \{\text{Action}\} \]

Let's read: Norvig's AI, chap 1

This is the first post in a series of posts as I read through Artificial Intelligence: A Modern Approach (3rd edition, 2009), by Peter Norvig, Stuart J. Russell. It's a behemoth with 1152 pages, eww. The book is unfortunately not free, but its pdf file is pretty easy to find online anyway, and most schools have a copy, too, just because it's so popular, as the official site says:

• The leading textbook in Artificial Intelligence. 
• Used in over 1300 universities in over 110 countries. 

We will study this book, not fully, it'd take about a year to do that! We'll just read as fast as possible to get the overview.

Today we read chapter 1.

Let's read: Machine Super Intelligence, preface and outline

Machine Super Intelligence (2008) is the PhD thesis of Shane Legg, a previous student of Marcus Hutter, and a cofounder of DeepMind.

Let's start at the Preface:

Meaning of UAI

This thesis concerns the optimal behaviour of agents in unknown computable environments, also known as universal artificial intelligence [UAI]. These theoretical agents are able to learn to perform optimally in many types of environments... Moreover, these agents can be proven to upper bound the performance of general purpose computable agents.

Okay, the first paragraph is heavy, and summarizes the whole point of UAI. Let me unpack it for you.

Let's read: Spinoza's Ethics, You Can't Not Believe Everything You Read, and why Elephants don't play chess

Descartes and Spinoza are two 17th century philosophers. Descartes's philosophy is the one that's shaped how people think the world works, but are they true? Today we read two papers that suggest otherwise.

You Can't Not Believe Everything You Read (1993), Daniel T. Gilbert, Romin W. Tafarodi, Patrick S. Malone. It's a paper written by psychologists, but touches on a lot of philosophy and neurosciences in it.

Let's start by the abstract:

Can people comprehend assertions without believing them? Descartes suggested that people can and should, whereas Spinoza suggested that people should but cannot.