In the year 1820, a person could expect to live less than 35 years, 94% of the global population lived in extreme poverty, and less that 20% of the population was literate. Today, human life expectancy is over 70 years, less that 10% of the global population lives in extreme poverty, and over 80% of people are literate. These improvements are due mainly to advances in technology, beginning in the industrial age and continuing today in the information age. There are many exciting new technologies that will continue to transform the world and improve human welfare. Here are eleven of them.

Members of Rajat Monga's team at Google will be teaching tutorials on deep learning with TensorFlow at Strata Hadoop World in Beijing (August 4th) and NYC (September 27th). Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data and data science. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. In this episode of the O'Reilly Data Show, I spoke with Rajat Monga, who serves as a director of engineering at Google and manages the TensorFlow engineering team. We talked about how he ended up working on deep learning, the current state of TensorFlow, and the applications of deep learning to products at Google and other companies. There's not going to be too many areas left that run without machine learning that you can program.

Artificial intelligence can find, map poverty, researchers ...

IN "Minority Report", a policeman, played by Tom Cruise, gleans tip-offs from three psychics and nabs future criminals before they break the law. In the real world, prediction is more difficult. But it may no longer be science fiction, thanks to the growing prognosticatory power of computers. That prospect scares some, but it could be a force for good--if it is done right. Machine learning, a branch of artificial intelligence, can generate remarkably accurate predictions.

The cities of the future will be huge and super-dense -- but will they also be alive? Could the increasingly complex systems needed to manage the next generation of megacities become our first true artificial intelligence? People have speculated before about the idea that the Internet might become self-aware and turn into the first "real" A.I., but could it be more likely to happen to cities, in which humans actually live and work and navigate, generating an even more chaotic system? It's either my worst nightmare or the dawn of a wonderful new future, but scientists are… Read more Read more As cities become more networked and their mixture of urban infrastructure and surveillance infrastructure becomes more complex, eventually we'll have to build cities that can think for themselves. People have speculated about the potential for computer systems to help in urban planning forever, including papers about the use of "fuzzy logic" to automate the decision-making process and A.I. solutions for land use planning, and the an A.I. "spatial decision support system."

Artificial intelligence can find, map poverty, researchers ... Ai Weiwei exhibit extended until Sept. 11 at Warhol AI passenger carrying gold bars worth over Rs 2.5 crore held

You could say the job of the sports fan is not only to cheer but to jeer. American sprinter Justin Gatlin, who has been suspended in the past for doping, entered Olympic Stadium before his 100-meter race to resounding boos. Competitors are also a part of the ritual. After winning a gold medal, American swimmer Lilly King wagged her finger to mock her Russian competitor Yulia Efimova, who previously had been suspended for doping. To philosopher Julian Savulescu, the boos and censures ring with, if not outright hypocrisy, short memory spans. "Caffeine is a performance-enhancer," he says. "It used to be banned and now it's allowed." Savulescu, a native Australian, who directs the Uehiro Center for Practical Ethics at the University of Oxford, has been one of the loudest critics in recent years of doping policies. Sports governing bodies have had restrictions in place for decades, he says, and have had little effect. Athletes will always find a way to beat the system, he says, and like most sports fans, Savulescu laments that doping creates an uneven playing field. But unlike most fans, Savulescu thinks the solution is to make doping legal in sports.

Artificial intelligence can find, map poverty, researchers ... Ai Weiwei exhibit extended until Sept. 11 at Warhol AI passenger carrying gold bars worth over Rs 2.5 crore held

Artificial intelligence can find, map poverty, researchers ... AI passenger carrying gold bars worth over Rs 2.5 crore held

This paper addresses network anomography, that is, the problem of inferring network-level anomalies from indirect link measurements. This problem is cast as a low-rank subspace tracking problem for normal flows under incomplete observations, and an outlier detection problem for abnormal flows. Since traffic data is large-scale time-structured data accompanied with noise and outliers under partial observations, an efficient modeling method is essential. To this end, this paper proposes an online subspace tracking of a Hankelized time-structured traffic tensor for normal flows based on the Candecomp/PARAFAC decomposition exploiting the recursive least squares (RLS) algorithm. We estimate abnormal flows as outlier sparse flows via sparsity maximization in the underlying under-constrained linear-inverse problem. A major advantage is that our algorithm estimates normal flows by low-dimensional matrices with time-directional features as well as the spatial correlation of multiple links without using the past observed measurements and the past model parameters. Extensive numerical evaluations show that the proposed algorithm achieves faster convergence per iteration of model approximation, and better volume anomaly detection performance compared to state-of-the-art algorithms.