Friday, 22 March 2013


How algorithms shape our world
It takes you 500,000 microseconds just to click a mouse. But if you’re a Wall Street algorithm and you’re five microseconds behind, you’re a loser.— Kevin Slavin


Synopsis

Kevin Slavin argues that we're living in a world designed for - and increasingly controlled by - algorithms. In this riveting talk from TEDGlobal, he shows how these complex computer programs determine: espionage tactics, stock prices, movie scripts, and architecture. And he warns that we are writing code we can't understand, with implications we can't control. Talk recorded 13 July 2011.

About the Speaker
·         Kevin Slavin navigates in the algoworld, the expanding space in our lives that’s determined and run by algorithms.
·         Are you addicted to the dead-simple numbers game Drop 7 or Facebook’s Parking Wars? Blame Kevin Slavin and the game development company he co-founded in 2005, Area/Code, which makes clever game entertainments that enter the fabric of reality.
·         All this fun is powered by algorithms - as, increasingly, is our daily life. From the algorithms used by Google, to those that give you “recommendations” online, to those that automatically play the stock markets (and sometimes crash them): we may not realize it, but we live in the algoworld.


Monday, 19 November 2012

Google Builds Artificial Brain Which Can Recognize A Cat


The Google X laboratory has invented some pretty cool stuff: refrigerators that can order groceries when your food runs low, elevators that can perhaps reach outer space, self-driving cars. So it’s no surprise that their most recent design is the most advanced, highest functioning, most awesome invention ever… a computer that likes watching YouTube cats?

Okay, it’s a bit more advanced than that. Several years ago, Google scientists began creating a neural network for machine learning. The technique Google X employed for this project is called the “deep learning,” a method defined by its massive scale. In layman’s terms, they connected 16,000 computer processors and let the network they created roam free on the Internet so as to simulate a human brain learning.

Stanford University computer scientist Andrew Y. Ng, led the Google team in feeding the neural network 10 million random digital images from YouTube videos. The machine was not “supervised,” i.e. it was not told what a cat is or what features a cat has; it simply looked at the data randomly fed to it. Ng found that there was a small part of the computer’s “brain” that taught itself to recognize felines. “It basically invented the concept of a cat,” Google fellow Jeff Dean told the New York Times.

So Google may have created a machine that can teach itself. But what Ng and his team have done is not as new as you may think. Over the years, as the scale of software simulations has grown, machine learning systems have advanced; last year, Microsoft scientists suggested that the “deep learning” technique could be used to build computer systems to understand human speech. This Google X machine is the cream of the crop—twice as accurate as any other machine before it. However, “it is worth noting that our network is still tiny compared to the human visual cortex,” the researchers wrote, “which is a million times larger in terms of the number of neurons and synapses.”

After “viewing” random pictures from random YouTube videos, the neural network created a digital image of a cat based on its “memory” of the shapes it saw in the images. The cat the computer created is not any specific cat, but what the computer imagines to be a cat. Plato had his Forms, and now Google has its computer-generated cat image.

Wednesday, 29 June 2011

hi everybody

hello everybody....................as you know the current time is the time of technology...
and now onwords i will publish some intresting things on my blog that everybody like the most.........

hope you enjoy the blog.
aakash kaushik