How-to

Tech

  • At BlackRock, Machines Are Rising Over Managers to Pick Stocks.

    On Tuesday, BlackRock laid out an ambitious plan to consolidate a large number of actively managed mutual funds with peers that rely more on algorithms and models to pick stocks.

    The initiative is the most explicit action by a major fund management firm in reaction to the exodus of investors from actively managed stock funds to cheaper funds that track every variety of index and investment theme.

  • Building an AI Chip Saved Google From Building a Dozen New Data Centers.

    Rather than double its data center footprint, Google instead built its own computer chip specifically for running deep neural networks, called the Tensor Processing Unit, or TPU. "It makes sense to have a solution there that is much more energy efficient," says Norm Jouppi, one of the more than 70 engineers who worked on the chip. In fact, the TPU outperforms standard processors by 30 to 80 times in the TOPS/Watt measure, a metric of efficiency.

  • IBM, Intel, Stanford Bet on AI to Speed Up Disease Diagnosis and Drug Discovery.

    IBM Research, the innovation arm of multinational tech giant IBM, and collaborators have developed a machine learning model that predicts heart failure up to two years before a patient would typically be diagnosed. The researchers trained the model using hidden signals gleaned from electronic health records and doctors' notes.

  • Machine Learning Will Save India's Cows from Bad Drivers.

    Cows on roads are a big problem in India, where rapid urbanization and industrialization has meant that new roads are increasingly being laid through rangeland. A 2015 study found that some 6 percent of accidents in India can be attributed to animals on the road.

    Enter Indian computer scientists Sachin Sharma and Dharmesh Shah. The duo has crafted a cow identification algorithm that, if deployed, could reduce the incidence of cow-car collisions, they argue.

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Data Links is a periodic blog post published on Sundays (specific time may vary) which contains interesting links about data science, machine learning and related topics. You can subscribe to it using the general blog RSS feed or this one, which only contains these articles, if you are not interested in other things I might publish.

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