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2016: The Year of Space
April 30, 2016

2016 is shaping up to be the most interesting year for space flight since the days of Apollo, especially if you book-end it with the tale end of 2015.

Dec 2015
First successful Falcon 9 landing (on land)
First flight of Falcon 9 v 1.2
Return to flight after June mishap
April 2016: First successful barge landing
April 2016: SpaceX announces plans for 2018 landing of 5 tonnes on Mars (huge surprise)
July/August/Sept: First re-flight of Falcon 9 booster
August: SpaceX Hyperloop Pod Competition
September: Reveal of Mars plans
Nov/Dec/Jan: First flight of Falcon Heavy
On top of all of that: Up to 18 flights and landing attempts of Falcon 9
Blue Origin's first re-flight of their rocket (and in late 2015, the first landing)

(Also of recent was the reveal of Pluto)

The above represents a lot of very momentous events, all packed into little more than a year. If you're someone intrigued by spaceflight, it's perhaps analogous to the year a sports nutt's favorite hockey team won the Stanley Cup and set all sorts of records.

It could all come to a grinding half if and when the next rocket blows up, but if all goes according to plan, it will be a crazy year.

Widening the scope technology wise, we've also recently had:

Sept 2015: Autopilot beta goes live -- first compelling semi-autonomous technology on the market
Sept 2015: Release/reveal of Tesla Model X
March 2016: Reveal of Tesla Model 3, with 400,000 reservations
Gigafactory phase 1 starting to come on line
Volvo's announcement of 2017 program that will feature real families driving fully autonomous vehicles on select roads
AlphaGo beats world "Go" champion
Deep Learning making big strides
Gravitational waves

There's a lot happening...


Computation And The Illusion of Being Cared For
March 20, 2016

Mysterious title to this blog post...

Last year I created some code to take the Netflix movie recommendations on my account and my wife's account and combine our projected ratings for the movies. Then I sorted the list.

For some time now, I've enjoyed this type of strategy for helping people decide on shared things, whether it be a baby name, or a movie. It seems to work pretty well!

After watching a couple of movies taken from this list recently, I was quite smitten with the result. In both cases, the movies were ones I probably never would have picked off of the shelf, and yet we really did enjoy watching them.

After yet more reflection, I think I've realized that part of what made the end result so nice is that it almost felt like we had hired a person to sift through a bunch of facts about who we are, what our values are, the kind of things that delight us, and then that person went off and spent a few days looking through movies, trying to find ones that would be a perfect fit for the two of us.

Of course, that didn't happen. It was just computer code at Netflix -- lots of machine learning / modeling techniques, and then a simple match rank algorithm to combine Meredith's and my recommendations.

This makes me curious about the future: How often will people feel "cared for" in a sense when in fact it's just algorithms optimizing their lives. Maybe I'm unusual, but in reflecting on this, I actually did feel kind of cared for after watching those two movies. It felt like someone was looking out for me, being thoughtful, on my behalf.


Modeling a Person
February 5, 2016

One of the odd things that Ray Kurzweil has talked about is the idea of recreating his father as an artificial intelligence, and to do so using old photographs and writings of his father's. Upon hearing this, even though it sounds bizarre, I felt compassion for him -- he lost his father at a relatively young age, and it was obviously a huge loss for him. His faith in bringing him back seems to have grown out of his deep hope that it might be possible, however unlikely.

All this said, something struck me today that isn't completely unrelated. In past months I've pondered the (not new, I don't think) idea of building up an AI by feeding it a stream of video, sound, and touch, and having its algorithms attempt to build a model that can predict the next "frame" of sensory data. Thus, one gets "free" supervised training data.

Let's connect this idea to Ray's dream of modeling his father, but let's assume his father was still living. What we'll do is have his father wear something like Google Glass, which will record everything his father is seeing and hearing. We'll also have him wear a thin nylon-like suit that will record the X/Y/Z position of his body parts and what touch stimuli he is receiving. The system will then record everything that he says, everything he types, and every motor control that he does.

Once we've done this, we again have a "supervised" training set... the stimuli he is receiving are the inputs, and his behaviors are the outputs... everything from what he says, to the exact tone of his voice, to the precise way he holds his head, or how often he blinks.

Let's imagine we capture a few petabytes of this data, and then we use a fancy computer in 2065 with an insane amount of neural network capability to train a neural net that tries to predict what his father's behavior will be in a given situation.

Finally, we'll run the neural net, and have it run in VR, creating a photo-realistic representation of the man, and to interact with him, you strap on a VR headset, and enter that virtual world.

I'm curious what this might be like in a year like 2065... would such a technique exist?  Would it be in any way compelling?  And how about the limit... given enough time, might we be able to "model" a person well enough to create a VR likeness of them that was very compelling?

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