Google’s X Lab designed a particular neural network to discern whether an algorithm could learn to recognize faces without being fed information on exactly what a face was. It did great at that task.
It also found cat videos quite well:
The “brain” simulation was exposed to 10 million randomly selected YouTube video thumbnails over the course of three days and, after being presented with a list of 20,000 different items, it began to recognize pictures of cats using a “deep learning” algorithm. This was despite being fed no information on distinguishing features that might help identify one.
On the surface, it’s a joke about the impending cat video singularity. But it’s a pretty awesome example of machine learning, too. It means that with careful programming, a synthetic network can learn fairly advanced patterns in completely novel data, like cat faces, or what a cat even IS.
“Beyond pornography, futuresex promises emancipation from constraints and scripts. Judith (Jack) Halberstam, who teaches English and gender studies at the University of Southern California, predicted that “the tyranny of the biological family” will dissipate with changing sexual and emotional configurations. As divorce rates rise above 50 percent, she sees a new openness to alternative arrangements. “Marriage might have been OK back when people died at the age of 45,” she said, “but nowadays, ‘till death do us part’ is a lot harder.” The future of sex will see the subversion of dysfunctional and crumbling institutions, Halberstam asserted, in favor of potentially fresher and stronger kinship structures like queer families and community parenting.”—Sex 2.0 - The Chronicle Review - The Chronicle of Higher Education (via wildcat2030)
Robotics today is like the Internet in the 1990s: Fuel it with the right combination of technology, people, and money, and it will explode into a formidable new industry that will profoundly reshape people’s lives.
“Yesterday, during a World Science Festival panel on human origins and why our species outlasted other species of Homo, geneticist Ed Green mentioned that there were thousands of sequenced human genomes, from all over the world, that had been made publicly available. Our code is open source.”
ScienceDaily (June 1, 2012) — Neuroscientists at Cold Spring Harbor Laboratory (CSHL) just reached an important milestone, publicly releasing the first installment of data from the 500 terabytes so far collected in their pathbreaking project to construct the first…
“FOR half a century, the essence of progress in the computer industry has been to do more with less. Moore’s law famously observes that the number of transistors which can be crammed into a given space doubles every 18 months. The amount of data that can be stored has grown at a similar rate. Yet as components get smaller, making them gets harder and more expensive. On May 10th Paul Otellini, the boss of Intel, a big American chipmaker, put the price of a new chip factory (known as a fab) at around $10 billion. Happily for those that lack Intel’s resources, there may be a cheaper option—namely to mimic Mother Nature, who has been building tiny devices, in the form of living cells and their components, for billions of years, and has thus got rather good at it. A paper published in Small, a nanotechnology journal, sets out the latest example of the technique. In it, a group of researchers led by Sarah Staniland at the University of Leeds, in Britain, describe using naturally occurring proteins to make arrays of tiny magnets, similar to those employed to store information in disk drives. The researchers took their inspiration from Magnetospirillum magneticum, a bacterium that is sensitive to the Earth’s magnetic field thanks to the presence within its cells of flecks of magnetite, a form of iron oxide. Previous work has isolated the protein that makes these miniature compasses. Using genetic engineering, the team managed to persuade a different bacterium—Escherichia coli, a ubiquitous critter that is a workhorse of biotechnology—to manufacture this protein in bulk.”—Nanotechnology: A fab result | The Economist (via wildcat2030)