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AI

World's Largest Hedge Fund To Replace Managers With Artificial Intelligence (theguardian.com) 209

An anonymous reader quotes a report from The Guardian: The world's largest hedge fund is building a piece of software to automate the day-to-day management of the firm, including hiring, firing and other strategic decision-making. Bridgewater Associates has a team of software engineers working on the project at the request of billionaire founder Ray Dalio, who wants to ensure the company can run according to his vision even when he's not there, the Wall Street Journal reported. The firm, which manages $160 billion, created the team of programmers specializing in analytics and artificial intelligence, dubbed the Systematized Intelligence Lab, in early 2015. The unit is headed up by David Ferrucci, who previously led IBM's development of Watson, the supercomputer that beat humans at Jeopardy! in 2011. The company is already highly data-driven, with meetings recorded and staff asked to grade each other throughout the day using a ratings system called "dots." The Systematized Intelligence Lab has built a tool that incorporates these ratings into "Baseball Cards" that show employees' strengths and weaknesses. Another app, dubbed The Contract, gets staff to set goals they want to achieve and then tracks how effectively they follow through. These tools are early applications of PriOS, the over-arching management software that Dalio wants to make three-quarters of all management decisions within five years. The kinds of decisions PriOS could make include finding the right staff for particular job openings and ranking opposing perspectives from multiple team members when there's a disagreement about how to proceed. The machine will make the decisions, according to a set of principles laid out by Dalio about the company vision.
China

Chinese Government Moves To Crack Down On Puns 156

FreedomFirstThenPeac (1235064) writes "A story in The Guardian tells us that in an Orwellian move to legislate language, the Chinese government is attempting to stop the use of puns because they are disruptive and may lead to chaos (not the mathematical kind) and as such are unsuitable for use. However, Chinese is rife with puns, with this example quoted in the story: "When couples marry, people will give them dates and peanuts – a reference to the wish Zaosheng guizi or 'May you soon give birth to a son.' The word for dates is also zao and peanuts are huasheng." The powerful date and peanut lobbies are up in arms, claiming that such a ban will cost them more than peanuts. Their claim? "If you outlaw puns. Only criminals will have puns."

Comment Re:Follow the money? (Score 4, Insightful) 329

The medallion owners, and they show their appreciation to the city government in an appropriate fashion.

Same reason they don't allow some stores (in the US, typically liquor stores or car dealers) to open on Sundays. It's all about protecting the incumbents from a new entrant who wants to increase their market share and doesn't mind that the existing businesses would have to start caring about their customers.

AI

The Flaw Lurking In Every Deep Neural Net 230

mikejuk (1801200) writes "A recent paper, 'Intriguing properties of neural networks,' by Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow and Rob Fergus, a team that includes authors from Google's deep learning research project, outlines two pieces of news about the way neural networks behave that run counter to what we believed — and one of them is frankly astonishing. Every deep neural network has 'blind spots' in the sense that there are inputs that are very close to correctly classified examples that are misclassified. To quote the paper: 'For all the networks we studied, for each sample, we always manage to generate very close, visually indistinguishable, adversarial examples that are misclassified by the original network.' To be clear, the adversarial examples looked to a human like the original, but the network misclassified them. You can have two photos that look not only like a cat but the same cat, indeed the same photo, to a human, but the machine gets one right and the other wrong. What is even more shocking is that the adversarial examples seem to have some sort of universality. That is a large fraction were misclassified by different network architectures trained on the same data and by networks trained on a different data set. You might be thinking 'so what if a cat photo that is clearly a photo a cat is recognized as a dog?' If you change the situation just a little and ask what does it matter if a self-driving car that uses a deep neural network misclassifies a view of a pedestrian standing in front of the car as a clear road? There is also the philosophical question raised by these blind spots. If a deep neural network is biologically inspired we can ask the question, does the same result apply to biological networks? Put more bluntly, 'Does the human brain have similar built-in errors?' If it doesn't, how is it so different from the neural networks that are trying to mimic it?"
Google

Protesters Show Up At the Doorstep of Google Self-driving Car Engineer 692

mpicpp sends this report from Ars Technica: "Protests against tech giants and their impact on the San Francisco Bay Area economy just got personal. According to an anonymous submission on local news site Indybay, an unknown group of protesters targeted a Google engineer best known for helping to develop the company's self-driving car. ... The protest against Levandowski came the same day that the San Francisco Municipal Transit Authority (SFMTA) voted for the first time to take action regulating Google, Facebook, Apple, and a number of other large tech companies that shuttle workers in private, Wi-Fi-enabled buses from the Bay Area to points south in Silicon Valley."

Comment Re:Quick question (Score 2) 139

There are indeed reasonable number of fare-free systems. But you neglect the core purpose of public transit as it is seen by most US governments—i.e. distributing cash. Even if a system has 10% farebox recovery, they still get to buy the equipment and employ people to collect the money. Sure, they could go to proof-of-payment (or drop fares entirely), and further reduce costs by putting the Buy America Act and Davis-Bacon out of their misery, but that would reduce the opportunity for graft.

Mars

Craig Venter Wants To Rebuild Martian Life In Earth Lab 142

Hugh Pickens writes "Karen Kaplan reports in the LA Times that Craig Venter is making plans to send a DNA sequencer to Mars. Assuming there is DNA to be found on the Red Planet – a big assumption, to be sure – the sequencer will decode its DNA, beam it back to Earth, put those genetic instructions into a cell and then boot up a Martian life form in a biosecure lab. Venter's 'biological teleporter' (as he dubbed it) would dig under the surface for samples to sequence. If they find anything, 'it would take only 4.3 minutes to get the Martians back to Earth,' says Venter, founder of Celera Genomics and the Institute for Genomic Research (TIGR). 'Now we can rebuild the Martians in a P4 spacesuit lab.' It may sound far-fetched, but the notion of equipping a future Mars rover to sequence the DNA isn't so crazy, and Venter isn't the only one looking for Martian DNA. MIT research scientist Christopher Carr is part of a group that's 'building a a miniature RNA/DNA sequencer to search for life beyond Earth,' according to the MIT website 'The Search for Extra-Terrestrial Genomes.' SETG will test the hypothesis that life on Mars, if it exists, shares a common ancestor with life on Earth. Carr told Tech Review that one of the biggest challenges is shrinking Ion Torrent's 30-kilogram machine down to a mere 3 kg – light enough to fit on a Mars rover."

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