[Popular STEM] Curating the Internet: Science and technology digest for October 15, 2020

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Intel's OpenBot makes robots out of smart phones; Using machine learning to measure the "age" of our brains; A defense of bats in the age of COVID-19; Private investment in fusion energy prospects is growing; and researchers suggest that biased social-media influencers cause increases in polarization


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  1. How Intel's OpenBot Wants to Make Robots Out of Smartphones - A project from Intel Labs is combining about $50 worth of DIY hardware and an owner's cell phone to make a functional robot as part of the OpenBot initiative. The robot uses neural network learning to make an "inexepensive and capable robot" that can do things like following a person or autonomously navigating through an office. They hope that the device can be used for "education and large-scale learning". Smart phones also provide additional capabilities that have not yet been exploited, including microphones, screens, and speakers. Which is why the company says,
    These may enable research and applications at the confluence of human-robot interaction and natural language processing. We also expect the basic ideas presented in this work to extend to other forms of robot embodiment, such as manipulators, aerial vehicles, and watercraft.
    The most surprising thing about the concept may be that it's not a new idea. In fact, the general idea has been around since a Kickstarter project in 2012, if not before.

    Here is a video:



  2. How Old is Your Brain? - I'm not particularly fond of the term "brain age", but what it means is that - at any particular age - some people's brains look older than others in an MRI scan. The article compares this phenomenon to the way some people get grey hair sooner than others. This is important because older looking brains have been linked to Alzheimer's disease, dementia, slower walking, poorer lung functioning, and even early death. Researchers want to be able to screen for older looking brains so they can follow-up with more accurate tests. Until about ten years ago, this wasn't really practical because MRI images required analysis and other processing by humans. With the emergence of the big-data era, however, it is now possible to apply machine learning techniques to raw MRI data in massive data sets and use that to predict which brains will appear to be older. Even now, though, the quality of the image and the type of the MRI scanner have a big impact on the reliability of the model, so the technique is still a work in progress. One thing researchers have noticed with twin studies is that twins' brains generally age at roughly similar rates, suggesting that there is a strong genetic component to the way our brains appear to age.

  3. Covid: Why bats are not to blame, say scientists - This article acknowledges that the SARS-CoV-2 virus likely crossed from bats into humans, but says that the bats aren't to blame for the COVID-19 pandemic. Instead, it argues that the proportion of viruses crossing from bats into humans is similar to that of other species of animals and that it's people who need to reassess our relationship with nature. In fact, it points out that insect-eating bats are responsible for reducing crop damage, and that hundreds of plant species rely on bats for pollination. They are the only flying mammal, and they are under great threat from habitat destruction, hunting, and other pressures. -h/t RealClear Science

  4. Investments in privately funded fusion ventures grow - Conventional wisdom says that "Fusion power is 30 years away, and always will be", but there are hints that conventional wisdom may be wrong. The international $25 billion ITER project intends to start delivering fusion power in France by the year 2035, and there are at least five private ventures hoping to deliver nuclear power first. Fueled with hundreds of millions of dollars in private venture capital, including investments from heavy-weights like Bill Gates and Jeff Bezos, each of these five firms say that they may be able to deliver on the hopes for clean and virtually unlimited power within a decade. The approaches vary from conventional to exotic, but the firms all face common challenges, including the need for materials that can withstand bombardment from highly energetic particles and the need to manage temperatures in a highly energetic enclosure. -h/t RealClear Science

  5. Why Social Media Make Us More Polarized, and How to Fix It - Short version, it's the influencers not the crowd. Researchers divided trial participants into groups based on their political leanings and intentionally placed them in echo chambers where their views were dominant. Then, the discussions were seeded with political hot-button topics. Surprisingly, discussions tended to drift towards the center, and participants on both sides of the divide adopted views that were closer to their political "opposites". The article summarizes it like this:
    In a centralized echo chamber, if the influencer at the middle shows even a small amount of partisan bias, it can become amplified throughout the entire group. But in egalitarian networks, ideas spread based on their quality, and not the person touting them. There is a lot of wisdom in network peripheries, in regular people with good ideas. When the social network enables those people to talk with each other, new thinking that challenge a group’s biases can take hold and spread.
    As a response to polarization, then, the researchers suggest that the goal should be to rethink our online communities to lessen the impact of biased influencers and craft a more egalitarian style of interaction.


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