Herself’s Artificial Intelligence

Originally 20 teams had hoped to compete in the Urban Challenge, 11 made the first cut.  Some didn’t pass the ‘safe for road’ test. The 11 finalists VictorTango, CarOLO, Ben Franklin, Cornell, Stanford, Tartan, MIT, Knight Rider, AnnieWAY, Intelligent Vehicle Systems, Terra Max all competed for a three and a half million dollar prize.Six of the vehicles crossed the finish, and the three winners were Stanford ( $1 million ), Carnegie Mellon ( Tartan )( $2 million ) , and Virginia Tech ( Ben Franklin ) ( half a million ) finishing in less than 6 hours each.The course was 60 miles long, and vehicles had to avoid obstacles including 50 human driven cars.

More information:
Darpa, Urban Challenge
Memory leak does in Princeton Team

. . . The idea of evolutionary algorithms is not new. Until recently, however, their use has been confined to projects such as refining the aerodynamic profiles of car bodies, aircraft fuselages and wings. That is because only large firms have been able to afford the supercomputers needed to mutate and crossbreed large virtual genomes—and then simulate the behaviour of their offspring—for perhaps 20m generations before the perfect design emerges.What has changed, in this as in so much else, is the availability and cheapness of computing power. According to John Koza of Stanford University, who is one of the pioneers of the field, evolutionary designs that would have taken many months to run on PCs are now feasible in days.The result is that the range of applications to which the principles of evolutionary design are being applied is growing fast. Among those revealed at the Genetic and Evolutionary Computation Conference held in London this summer were long-life USB memory sticks, superfast racing-yacht keels, ultra-high-bandwidth optical fibres, high performance Wi-Fi antennae (evolved to avoid patent fees), cochlear implants that can optimise themselves to individual patients and a cancer-biopsy analyser that was evolved to match a human pathologist’s tumour-spotting skills.

How can evolution help improve a USB stick? It turns out that the storage transistors in these flash-memory devices are prone to being gummed up with electrostatic charge that they cannot dissipate. That prevents them being erased, limiting the stick’s useful life. A team at the University of Limerick in Ireland therefore evolved new signal-timing patterns that minimise the build-up of the disabling charge. The result: USB sticks that last up to 30 times longer than their predecessors. At the University of Sydney, in Australia, Steve Manos let an evolutionary algorithm come up with novel patterns in a type of optical fibre that has air holes shot through its length. Normally, these holes are arranged in a hexagonal pattern, but the algorithm generated a bizarre flower-like pattern of holes that no human would have thought of trying. It doubled the fibre’s bandwidth. . . . [ read more Don't invent evolve]

See also:
Evolutionary computation: An overview(pdf)
Adrian Thompson’s Hardware Evolution Page ( He uses evolution to improve computer chips. )

If not yet then soon it will be. Think of the advantages for employers. Employers, the government, the military can use software like this to learn how to get the most out of each person and to drive them harder and make them more productive.

Tufts University researchers are developing techniques that could allow computers to respond to users’ thoughts of frustration — too much work — or boredom—too little work. Applying non-invasive and easily portable imaging technology in new ways, they hope to gain real-time insight into the brain’s more subtle emotional cues and help provide a more efficient way to get work done.
“New evaluation techniques that monitor user experiences while working with computers are increasingly necessary,” said Robert Jacob, computer science professor and researcher. “One moment a user may be bored, and the next moment, the same user may be overwhelmed. Measuring mental workload, frustration and distraction is typically limited to qualitatively observing computer users or to administering surveys after completion of a task, potentially missing valuable insight into the users’ changing experiences.”

Sergio Fantini, biomedical engineering professor, in conjunction with Jacob’s human-computer interaction (HCI) group, is studying functional near-infrared spectroscopy (fNIRS) technology that uses light to monitor brain blood flow as a proxy for workload stress a user may experience when performing an increasingly difficult task. A $445,000 grant from the National Science Foundation will allow the interdisciplinary team to incorporate real-time biomedical data with machine learning to produce a more in-tune computer user experience. . . . [ read more Technology could enable computers to 'read the minds' of users ]

Functional near infrared spectroscopy measures changes in blood concentrations of oxygen and sugar that happen in your brain with neural activity. This is non-invasive, physically. It appears for now you must wear headgear when the test is done. I wonder how long it will be before you can point a laser type light as someone and find out what that person is thinking?

See also:
Human-Computer Interaction and Brain Measurement Using Functional Near- Infrared Spectroscopy (pdf)

Tufts research aims to ‘read the minds’ of computer users
M$ patents frustration detecting system