Herself’s Artificial Intelligence

We’ve all heard of UAVs. Over in Iraq they have played a huge helping role to US troops. Lesser known is their benefits to scientists exploring ocean life, and the Antarctic. More recently they have begun to show up in the news as ways to patrol the US/Mexico border and the city of Miami.

UAVs have been used along the US Mexico border and are soon to join the Miami police. ( pending FAA approval ) One of the problems we’ve had with Predators used along the border is crashes. FAA approval will depend on whether Miami’s police can convince the FAA they won’t be dropping UAVs on grandma’s car.

A more troubling question that we will have to answer if we allow UAVs over US cities is do we want our police to have weapon laden UAVs? The ones in Miami do not have weapons now but it is just a matter of time before some one finds a good reason to blow up several blocks in a US city. And it is far more likely to be our own guys than any terrorist.

Miami police could soon be the first in the United States to use cutting-edge, spy-in-the-sky technology to beef up their fight against crime.

A small pilotless drone manufactured by Honeywell International (HON.N), capable of hovering and “staring” using electro-optic or infrared sensors, is expected to make its debut soon in the skies over the Florida Everglades.

If use of the drone wins Federal Aviation Administration approval after tests, the Miami-Dade Police Department will start flying the 14-pound (6.3 kg) drone over urban areas with an eye toward full-fledged employment in crime fighting.

“Our intentions are to use it only in tactical situations as an extra set of eyes,” said police department spokesman Juan Villalba.

“We intend to use this to benefit us in carrying out our mission,” he added, saying the wingless Honeywell aircraft, which fits into a backpack and is capable of vertical takeoff and landing, seems ideally suited for use by SWAT teams in hostage situations or dealing with “barricaded subjects.” . . . [ read more Spy in the sky drone sets sights on Miami

More information:
PaparazzI The Free Autopilot, open source auto pilot software
DIY Drones ( in case you want to build your own )
Giz Mag: UAV news
DIY Drones, build your own drone

See also:
Powerline urban sentry finds a hack around battery problems

Sparse distributed memory first appeared in 1998 as a model of long term memory in humans. The main idea is that distances between concepts in our brains can be represented as distances between points in a high dimension world. Since distances between points are far apart in many dimensions, the distance between concepts is large. The large distance between concepts means I only have to come closer to it than another idea for a match to be made.

For example if I give each letter of the alphabet its own dimension then map it by position in a word then ‘aeple’ is closer to ‘apple’ than ‘ample’ and I can guess that the correct word for the mistyped word. Or a four legged creature that is tall and is spotted is closer to a giraffe than a short legged spotted leopard.

This type of storage of data means you can store far fewer examples you need to match allowing you to store more information in a much smaller memory footprint.

All input is represented in binary form in sparse distributed memory. The algorithm works by calculating the ‘Hamming distance’ between data input and existing examples in memory.

Books:
Reinforcement Learning: An Introduction (pdf download )

More information:
Sparse Distributed Memory
Kevin Kelly ‘Out of Control’ Chapter 2
Sparse Distributed Memory and Related Models Chapter 3 (pdf)

Papers:
Kanerva’s Sparse Distributed Memory An associative memory algorithm well suited to the connection machine. (pdf) ( exellent starting point )
Kanerva’s Sparse Distributed Memory, Multiple Hamming Thresholds ( pdf )

I ran across a story a while back on Engadget, Researchers create a nanobot-controlling brain, and realized I hadn’t looked to see where we are in nanotechnology in a long time.

Nano is a prefix representing one one-billionth of something, a nanobot is a robotic device less than 1 billionth of a meter in size. One billionth of a meter is enough length to hold about 7 hydrogen atoms. In actuality, nanotechnology refers to just about any technology that is ultra-tiny in size.

Early hopes were to develop nanobots that could be injected into humans to cure what ails us. So far that hasn’t happened. But some small progress is being made using nanomachines to kill cancer cells as medication delivery systems.

Some recent sci-fi books ( ‘Next’, ‘Post Singular’) have brought up some of the scarier possibilities nanobots bring to us. What happens if the nanoparticles behave like swarms? What happens if those swarms turn deadly? Or how do we protect ourselves from self-replicating nanoparticles that turn out to be dangerous?

Most recently nanosilver has been in the news. Its value is in its antibacterial properties. The hope was it would be added to clothing, laundry detergent and in medical devices. Not too long after nano-silver stories hit the main news media nano-silver pollution stories hit the news. You may also remember a few Y2K nutcases who dyed themselves blue drinking silver. If nano-silver contaminates the water supply what happens? We just don’t know yet? Will we all become smurfs?

Like any new technology bringing great promise, nanotechnology also brings great dangers. Until we have some progress on usable nanotechnology for the masses the concerns are likely to dampen interest in nanotechnology and government funding. So here’s hoping for some useful nanobots in our near future.

More information:
Are nanobots on their way?
Howard Lovy’s NanoBot ( blog )
International Society of Nanoscale Science, Computation and Engineering
Nanularity
Nanosoccer debuts at RoboCup 2007
International Nanotechnology and Society Network
Nanotechnology portal
A Billionth of a Meter is a Big Deal
I, nanobot

See also:
Shape shifting robots escape Lost set
Living Neural Net Created

One of the wonderful things the internet has done is to bring to life the ‘Mechanical Turk’. Together we can all do small things and create something wonderful, like the internet. Google’s search engine works so well because we all contribute to it. Amazon works fantastically because of the book reviews users contribute.

Loren Carpenter did an experiment at Siggraph 91 that demonstrated how quickly and easily we can work together even with out communicating.

Probably the most unique event of SIGGRAPH ’91 was Loren Carpenter’s Audience Participation piece presented during the Electronic Theater. Each person in the audience was given a wand with a red side and a green side. The colored retro-reflective material was scanned in by video cameras at the back of the auditorium, frame-grabbed and processed, and used to drive a video display that was projected on the big screen, all in real time. In its standby mode the system created a map of the auditorium, with enough resolution to show each seat, indicating whether the person in that seat was holding up the red or green (or neither) side of their wand. It was described as “being a pixel in a huge raster scan display”. Various games were played with this setup, from simple voting and “stadium flash card” type displays, to a round of massively parallel Pong. The Pong game was stunning because of how quickly the 5000 “autonomous agents” in the audience learned to cooperate and regulate their aggregate behavior. The way it worked was that each side of the auditorium controlled one of the Pong paddles, red moved the paddles up and green moved it down. In order to move the paddle to the correct position, just the right number of people had to signal with the appropriate color. Too many or too few and the paddle would overshoot or undershoot its mark. The final exercise was massively parallel control of a flight simulator. We crashed. [Phreak.org - archives ]

Before too much time goes by we will all have a smart computer with an internet connection in our shirt pocket everywhere we go. How much quicker will you be able to commute when the public’s telephones all communicate the quickest route home with out any interaction from the users?

The commute is already a perfect example of a human hive mind at work. On route 128 about Boston millions of cars travel an old cow path that is now a 2, 3 or 4 lane highway depending on your location. It curves and winds and there are on and off ramps every few feet it seems. Yet an amazingly large amount of drivers manage to get on, bounce between lanes, go forward, get off all while playing with the radio, phone, texting, reading and avoiding all the unskilled drivers. ( Because everyone besides ourselves is an unskilled driver. ) No central command directs each car. We manage it autonomously, with little contact between the drivers and very little thinking.

Capitalism is an excellent example of the human hive mind. When we need more of a thing, the price goes up and more people begin creating more things. No plan or central authority is needed. When the economy slows in one place and picks up in another, the right number of people move to level both locations at sustainable levels.

This is all going to begin to happen faster and much more effectively thanks not only to the internet but the fact the net will soon be portable in everyone’s pocket.

More information:

The Technodiva Speaks
The Year in Ideas; Smart Mobs
Rheingold: Smart Mobs
Real Time Traffic Routing from the Comfort of your Car

Books:
‘Out of Control’ Kevin Kelly

See also:
Human generated artificial intelligence