neural network and machine learning

Live blogging the sc symposium
i showed up late for the talk on neural networks, which sucks, but i needed my coffee.
Tje speaker is demonstarting using a neural network to process gestural input from a wiimote. It makes 64 vectors describing the motion of the wimotes. He can train the neural net by making the same gesture over and over.
The auditorium speakers are making a high pitched squeal.
Now he’s talking about continious time recurrent nueral networks. These are used in robotics. They evolve instead of being trained. (Trained ones are called feet forward)
Ollie Brown did some code for this. He sugges that the smoothibg function be rep;aces with hyperbolic tans and become excitation functions and it does not reach equilibrium. You can use this for interactive evolution.
Squeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeazle.
The 60 hz hum has just caused a problem with the demo. The power to the av thing has cut out. Ron is cursing. People in the audience are whistling difference tones to go with the squeal. Somebody od making multiphonics. Now somebody is playing a sine tone on their laptop. Somebody is sampling and granularizing the feedback. The talk has paused. I wish i’d been here for the start because it’s awesome, but without coffee, i’d still have missed it.
A grad student has just come sprinting in with a cable. And the squal has ceased! Applause!
And the source of the squeal was an uniterruptible power supply. Which is why the av input died. Ohhhhhh! We are nearly back online. I wish this disaster had been at the start so i could have seem the whole thing.
The presenter, by the way is Chris Kiefer. Who is now resuming.
He is using a ctrnn to control a synth. And it can be reinitialized and mutated. This sounds cool, but i don’t under stand how it differs from random numbers. Oh, you pick ones you like and evolve from there.
Http://bit.ly/SC-NNs
http://bit.ly/SC-CTRNNS
HTTP://www.olliebrown.com/files/papers/ . . .