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It’s Official: Moore’s Law Is Nearing Its End

The 51-year-old computing principle is now butting heads with the realities of physics and economics.

In 1965 Gordon Moore, who would go on to co-found Intel, wrote a paper in which he described what has become known as “Moore’s law.” It stated that the number of transistors on a microprocessor will double roughly every two years, meaning, in theory, that every two years the processors inside our devices would get twice as fast and be able to do twice as much. For the better part of the ’70s, ’80s, ’90s, and into the first decade of the 21st century, Moore’s law proved to be correct—but only because it was a self-fulfilling prophecy, according to a recent article in the science journal Nature, which argues that the prophecy is about to come to an end.

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The Number Of Twitter Users Did Not Grow At All In The Final Quarter Of 2015

During Twitter’s fourth-quarter earnings announcement, the company reported troubling user numbers, as well as its agenda for 2016.

Twitter revealed startling data on Wednesday: for the fourth quarter of 2015, the social network’s total number of monthly active users remained completely flat, at 320 million. Excluding SMS Fast Followers, who access Twitter solely via text message, the total number of monthly active users actually declined, from 307 million to 305 million. In the United States, the number of active users fell from 66 million to 65 million.

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Marc Andreessen Riles Up Twitter After Defending Colonialism In India

In his defense of Facebook’s Free Basics Internet service, Andreessen suggested India was better off under colonial rule.

Venture capitalist and Facebook board member Marc Andreessen was, unsurprisingly, disappointed that India’s telecom regulator recently thwarted Facebook’s plans to expand Free Basics, the company’s free but limited Internet service aimed at developing markets. On Tuesday, Andreessen turned to Twitter to air his grievances:

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This Chip Will Give Your Phone AI Modeled On The Human Brain

MIT’s “Eyeriss” chip would allow for neural networks to run locally on your phone without an Internet connection.

In computing, a neural network is a collection of processors that mimic the way the human brain works. Simply put, a neural network analyzes data, learns about it, and then decides how to act upon that data. It is because of neural networks, which don’t rely on standard rule-based programing, that we have software that can recognize and distinguish between different human voices or that can recognize individual objects. Both Google Now and Apple’s Siri are examples of consumer neural networks.

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