Rat Brain Cells Fly Jet Aircraft Simulator

[NY3V]

http://www.youtube.com/watch?v=nXncJZCMog0&feature=youtu.be

Republicans are Obsolete! :doh:

[WØTKX]

Coming this fall! Rat Patrol II, the Drones!

http://www.webtvwire.com/wp-content/uploads/2010/08/Rat-Patrol-logo.JPG

[N2NH]

Well computers read our resumes and choose which of us will get a job. They have to power to starve us.

Why not have rats fly planes and drop bombs on us?

Scientific delirium madness.

[N8YX]

Republicans are Obsolete! :doh:
Did any of you folks catch the "No politics outside Forbidden Zone" news sticky which was posted by Jeff?

We're getting very tired of this.

[NY3V]

Did any of you folks catch the "No politics outside Forbidden Zone" news sticky which was posted by Jeff?

We're getting very tired of this.

Oops! Mea Culpa! I apologize. :ashamed:

[WØTKX]

Mine wasn't political, but it was satirical. Once could always link to this thread from the political section.

That being said, it is tiring... we know how you feel Dan. And many here agree with you, but still...
Once could always link to this thread from the political section.

Back on topic, I like the premise of wetware. Neuron computing is capable of better decision trees.
Especially when learning and adapting to new patterns. Duplicating nature is fascinating.

[N8YX]

Back on topic, I like the premise of wetware. Neuron computing is capable of better decision trees.
Especially when learning and adapting to new patterns. Duplicating nature is fascinating.
There was a decent article in Omni many years ago which detailed a logic equivalent of a cockroach brain in TTL and gave insight as to how knowledge retention and application could be effected with the circuit. Given the power of the average embedded microcomputer in today's world, it would be fascinating to see what could be derived from a marriage between the cognitive abilities of an animal brain with the processing power of, say, a fast PIC.

[WØTKX]

When I was working as an AV tech at a large conference center, HP gave a series of talks about some wetware designs they were working on. I got to video the whole series for them. It was very cool. I wonder what happened to all that excellent work?

Probably got buried by the nonsense that has gone on with their board. Running a business on short term gains and all that. Sigh.

Oh well. Such is the premise of false utopias.

http://joshblackman.com/blog/wp-content/uploads/2012/08/635.jpeg

[NY3V]

When I was working as an AV tech at a large conference center, HP gave a series of talks about some wetware designs they were working on. I got to video the whole series for them. It was very cool. I wonder what happened to all that excellent work?

Probably got buried by the nonsense that has gone on with their board. Running a business on short term gains and all that. Sigh.

Oh well. Such is the premise of false utopias.

http://joshblackman.com/blog/wp-content/uploads/2012/08/635.jpeg

I just finished reading this book:
http://www.amazon.com/Bloodline-Sigma-Force-James-Rollins/dp/0061784796/ref=sr_1_1?s=books&ie=UTF8&qid=1347129258&sr=1-1&keywords=bloodline+james+rollins

At the back of the book he gave the previous link I posted about rat brain cells.

I remember back around 1987 when I first stumbled across an article about ANN AI and I was fascinated by the future applications. http://www.neuroshell.com/Successful%20Trading%20Using%20Artificial%20Intell igence.pdf

The book was very entertaining. :)

[WØTKX]

So is Marvin Minsky, eh?

[kb2vxa]

Born in 1927 New York makes me wonder if he's related to the Minskys of burlesque fame. The City would probably still have good entertainment if Fiorello "little flower" LaGuardia wasn't such a prude.

[ab1ga]

...
I wonder what happened to all that excellent work?
...


Much of the ANN work got lost in the tall grass, less a victim of outside influence as lack of suitable hardware (which persists to this day) and intellectual navel-gazing.

Neural processing involves slow logic elements with extremely high levels of interconnectivity. Unfortunately, semiconductor technology excels at high speed, but making a large number of connections (dozens to thousands for some ganglia cells) is difficult and expensive. The answer was to simulate the former using the latter. The simple early models using an output determined by weighted sums of multiple inputs, was encouraging once the field decided to ignore Minsky's early detractions.

Then things got stupid. People started "refining" the network behavior and trying to get a theoretical model of the new systems. The simple sharp threshold was replaced with a sigmoid function, feedback was added, etc. The journal Neural Networks was filled with papers presenting new systems of differential equations to describe some new type of network. Then, custom coprocessor boards were developed to accelerate the calculations, performing millions of highly precise computations per second, and pumping the results through the fastest, latest PC bus available.

As time went on, the ANN looked less and less like a biological NN, and the field had devolved into finding ever faster ways to compute the behavior of a system which operates using pulse frequency modulation on a time scale of several milliseconds. By the time I lost interest, I had yet to see a paper which considered modeling NNs using stochastic methods, and I lacked the background to jump in myself. After a while, the whole field seemed to fade away.

It's kind of sad, because I think many of the problems we use supercomputers for today would be more usefully handled by neural-like computing. Our current computational modeling methods are almost all susceptible to the flapping of a butterfly's wing, and the draw our attention to the local detail rather than the overall picture. Fuzzy logic was an area which received plenty of academic scorn in it's day, although it demonstrably solved difficult control problems with relative, the primary example being the double inverted pendulum. Maybe some day we'll lose interest in the next decimal place and start paying more attention to the ones that matter.

73,