Lifeboat Foundation

In a paper published in Nature on 28th January 2016, we describe a new approach to computer Go. This is the first time ever that a computer program “AlphaGo” has defeated a human professional player.

The game of Go is widely viewed as an unsolved “grand challenge” for artificial intelligence. Games are a great testing ground for inventing smarter, more flexible algorithms that have the ability to tackle problems in ways similar to humans. The first classic game mastered by a computer was noughts and crosses (also known as tic-tac-toe) in 1952. But until now, one game has thwarted A.I. researchers: the ancient game of Go.

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An international team of researchers has developed a new algorithm that could one day help scientists reprogram cells to plug any kind of gap in the human body. The computer code model, called Mogrify, is designed to make the process of creating pluripotent stem cells much quicker and more straightforward than ever before.

A pluripotent stem cell is one that has the potential to become any type of specialised cell in the body: eye tissue, or a neural cell, or cells to build a heart. In theory, that would open up the potential for doctors to regrow limbs, make organs to order, and patch up the human body in all kinds of ways that aren’t currently possible.

It was Japanese researcher Shinya Yamanaka who first reprogrammed cells in this way back in 2007 — it later earned him a Nobel Prize — but Yamanaka’s work involved a lot of labourious trial and error, and the process he followed is not an easy one to reproduce. Mogrify aims to compute the required set of factors to change cells instead, and it’s passed its early tests with flying colours.

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Understanding time is one of the big open questions of physics, and it has puzzled philosophers throughout history. What is time? Why does it appear to have a direction? The concept is defined as the “arrow of time,” which is used to indicate that time is asymmetric – even though most laws of the universe are perfectly symmetric.

A potential explanation for this has now been put forward. Physicist Sean Carroll from CalTech and cosmologist Alan Guth from MIT created a simulation that shows that arrows of time can arise naturally from a perfectly symmetric system of equations.

The arrow of time comes from observing that time does indeed seem to pass for us and that the direction of time is consistent with the increase in entropy in the universe. Entropy is the measure of the disorder of the world; an intact egg has less entropy than a broken one, and if we see a broken egg, we know that it used to be unbroken. Our experience tells us that broken eggs don’t jump back together, that ice cubes melt, and that tidying up a room requires a lot more energy than making it messy.

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A new algorithm has been developed that will drastically reduce the time and effort needed to create induced pluripotent stem cells (iPSCs). As a result of this breakthrough, we can expect a dramatic revolution in regenerative medicine in the near future.

What if you could directly reprogram cells to develop into whatever you wished? What if you could take an undifferentiated, incipient cell, full of the unrealized potential to become any one of the many specialized cells in the human body, and nudge it into becoming ocular tissue, or neural cells, even a new heart to replace an old or damaged one?

This is the promise afforded by Mogrify, the result of the application of computational and mathematical science to the problems of medicine and biology. It was developed by an international collaboration of researchers from the Duke-NUS Medical School in Singapore, the University of Bristol in the United Kingdom, Monash University in Australia, and RIKEN in Japan. The new research was published online in the journal Nature Genetics.

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I have seen this model so many times over the decades. And, I even was engaged in some of these experiments in the past. The continued problem we saw is “subjective reasoning” by humans which makes the experiments flawed.

And, as Yampolskiy suggested this is not true AI; it is using human insights and identifying patterns based on human input whch also includes subjective reasoning.

While AI focuses on creating intelligent machines that perform human tasks, a human-based algorithm, harnessing the power of the crowd to make predictions, shows remarkable accuracy.

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Chrome is about to load web pages a lot faster than you’ve experienced up until now. Thanks to a new compression algorithm called Brotli, which Google introduced last September, Chrome will be able to compress data up to 26 percent more than its existing compression engine, Zopfli, which is an impressive jump.

According to Google’s web performance engineer Ilya Grigorik, Brotli is ready to roll out, so Chrome users should expect to see a bump in load times once the next version of Chrome is released. Google also says Brotli will help mobile Chrome users experience “lower data transfer fees and reduced battery use.” The company is hailing Brotli as “a new data format” that Google hopes will be adopted by other web browsers in the near future, with Firefox seemingly next in line to adopt it. But for now, expect to notice your web pages loading a bit faster in the coming weeks.

Update: January 20th 10:30AM: Updated to note that Firefox will also adopt Brotli in a future update.

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This totally makes sense to me. Whenever, you’re monitoring any type of patterns for collective reasoning or predictive analysis such measuring what voters clap to or respond positively to as well as build out your entire campaign strategy and speeches; AI is your go to solution. So, AI is a must have tool for politicians who strategically plan to win in future elections. No more need for a campaign manager like Karl Rove, etc.

Political speeches are often written for politicians by trusted aides and confidantes. Could an AI algorithm do as well?

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Ask the average passerby on the street to describe artificial intelligence and you’re apt to get answers like C-3PO and Apple’s Siri. But for those who follow AI developments on a regular basis and swim just below the surface of the broad field , the idea that the foreseeable AI future might be driven more by Big Data rather than big discoveries is probably not a huge surprise. In a recent interview with Data Scientist and Entrepreneur Eyal Amir, we discussed how companies are using AI to connect the dots between data and innovation.

Image credit: Startup Leadership Program Chicago

According to Amir, the ability to make connections between big data together has quietly become a strong force in a number of industries. In advertising for example, companies can now tease apart data to discern the basics of who you are, what you’re doing, and where you’re going, and tailor ads to you based on that information.

“What we need to understand is that, most of the time, the data is not actually available out there in the way we think that it is. So, for example I don’t know if a user is a man or woman. I don’t know what amounts of money she’s making every year. I don’t know where she’s working,” said Eyal. “There are a bunch of pieces of data out there, but they are all suggestive. (But) we can connect the dots and say, ‘she’s likely working in banking based on her contacts and friends.’ It’s big machines that are crunching this.”

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Humor, a distinctly human quality, could arguably be one of the most efficient ways to distinguish humans from machines. But not anymore.

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