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Sci/Tech

How Docker Is Helping to Save The World (Literally)

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Server
Sci/Tech

There are many different things that individuals might consider to be a life threatening event and then there are extinction level events, for example an asteroid hitting Earth.

While the idea of an asteroid hitting Earth and ending all life is the stuff of Hollywood movie like Armageddon, it's an actual, though remote, possibility that NASA is investigating, with the help of Docker containers.

NASA is currently developing a mission known as DART - the Double Asteroid Redirection Test, which is a spacecraft that will deploy a kinetic impact technique to deflect an asteroid. Christopher Heistand, DART Flight Software Lead, at the The Johns Hopkins University Applied Physics Laboratory (APL) that is helping to build the DART ship, detailed how his group is using Docker.

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Google's do no evil AI style likely to clash with open source approach

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Google
OSS
Sci/Tech
  • Google's do no evil AI style likely to clash with open source approach

    Google outlined its artificial intelligence principles in a move to placate employees who were worried about their work and research winding up in U.S. weapons systems.

    Guess what? It's already too late. There's no way that Google's open source approach and its headline principle to not allow its AI into weapons is going to mesh. Chances are fairly good that the technology already open sourced is in some fledgling weapon system somewhere. After all, TensorFlow and a bunch of other neural network tools are pretty damn handy.

  • Read Google's AI ethics memo: 'We are not developing AI for use in weapons'
  • Google Plans Not to Renew Its Contract for Project Maven, a Controversial Pentagon Drone AI Imaging Program
  • Google promises not to use A.I. for weapons or surveillance, for the most part
  • Google pledges not to develop AI weapons, but says it will still work with the military

    Google has released a set of principles to guide its work in artificial intelligence, making good on a promise to do so last month following controversy over its involvement in a Department of Defense drone project. The document, titled “Artificial Intelligence at Google: our principles,” does not directly reference this work, but makes clear that the company will not develop AI for use in weaponry. It also outlines a number of broad guidelines for AI, touching issues like bias, privacy, and human oversight.

    While the new principles forbid the development of AI weaponry, they state that Google will continue to work with the military “in many other areas.” Speaking to The Verge, a Google representative said that had these principles been published earlier, the company would likely not have become involved in the Pentagon’s drone project, which used AI to analyze surveillance footage. Although this application was for “non-offensive purposes,” and therefore hypothetically permitted under these guidelines, the representative said it was too close for comfort — suggesting Google will play it safe with future military contracts.

Free/Open Source AI Projects

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OSS
Sci/Tech
  • How open-source computing is making AI affordable

    computing and the cloud have brought many previously unaffordable IT options to small and medium-sized enterprises (SMEs). The same is becoming true of artificial intelligence (AI), although it brings new challenges to all sizes of company.

    Even though many of the commercial, high-profile products are aimed at Global 2000 companies, and others marketed at SMEs are perhaps heavier on hype than intelligence, the smarter smaller organisations can learn, build on and use AI techniques right now, with those same open-source and
    .

  • Free Ebook Offers Insight on 16 Open Source AI Projects

    Open source AI is flourishing, with companies developing and open sourcing new AI and machine learning tools at a rapid pace. To help you keep up with the changes and stay informed about the latest projects, The Linux Foundation has published a free ebook by Ibrahim Haddad examining popular open source AI projects, including Acumos AI, Apache Spark, Caffe, TensorFlow, and others.

    “It is increasingly common to see AI as open source projects,” Haddad said. And, “as with any technology where talent premiums are high, the network effects of open source are very strong.”

Scientific Linux 7.5 Released As RHEL 7.5 Rebuild

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Red Hat
Sci/Tech

Testing of the release candidate earlier this month went well and out now is the official Scientific Linux 7.5 release.

Scientific Linux 7.5 is the re-spin derived from upstream Red Hat Enterprise Linux 7.5 and its many changes/improvements.

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How Netflix Deploys Open Source AI to Reveal Your Favorites

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Sci/Tech

In this AI based Science article, we explore How Netflix adopted an Open Source Model to improve their Entertainment Recommender Systems.
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Open Sourcing the Hunt for Exoplanets

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Google
OSS
Sci/Tech

Why is cryptocurrency open source? This paper from 1999 explains

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OSS
Security
Sci/Tech

Cryptocurrency's roots go back further than bitcoin. In fact, bitcoin was just the first cryptocurrency to use the blockchain rather than the first cryptocurrency ever.

Other early cryptocurrencies include now venerable names like World of Warcraft (WoW) gold, a digital currency designed for use as a store of value and a transfer medium in the gaming universe of World of Warcraft. It used a proof-of-work mining algorithm in which users would engage with the WoW ecosystem via their computer's graphical interface and complete various digital tasks to be rewarded with gold.

As the fiat currency value of WoW gold increased, it attracted more miners without any corresponding difficulty adjustment, eventually leading to substantial inflation and a collapsing economy.

Today's cryptocurrencies seem to have learned from the problems of the past. For example, bitcoin and many others will adjust mining difficulty to prevent massive inflation when mining power increases.

It's no surprise that almost everything cryptocurrency, from the coins to the exchanges to the wallets, are built on open-source software. This paper from 1999 might be more relevant than ever, especially with a few wallets and coins still being partly or entirely closed source.

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Openwashing Surveillance

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OSS
Sci/Tech
  • Facebook Open Sources Detectron Object Detection

    The way big companies are open sourcing significant AI is both gratifying and slightly worrying. AI is the biggest revolution since we discovered fire and started making tools. FaceBook AI Research has added to the list of what is available by open sourcing its Detectron project.

  • Facebook open-sources object detection research

    Facebook's artificial intelligence research (FAIR) team today announced it would open-source its object detection platform Detectron, as well as the research the team has done on it.

  • Facebook open-sources object detection work: Watch out, Google CAPTCHA

    acebook has brought us one step closer to a Skynet future made a commitment to computer vision boffinry by open-sourcing its codebase for object detection, Detectron.

    Written in Python and powered by the Caffe2 deep learning framework, the codebase – which implements object-sniffing algos such as Mask R-CNN and RetinaNet – is available under the Apache 2.0 licence.

From lab to libre software: how can academic software research become open source?

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OSS
Sci/Tech

Academics generate enormous amounts of software, some of which inspires commercial innovations in networking and other areas. But little academic software gets released to the public and even less enters common use. Is some vast "dark matter" being overlooked in the academic community? Would the world benefit from academics turning more of their software into free and open projects?

I asked myself these questions a few months ago when Red Hat, at its opening of a new innovation center in Boston's high-tech Fort Point neighborhood, announced a unique partnership with the goal of tapping academia. Red Hat is joining with Boston-area computer science departments—starting with Boston University—to identify promising software developed in academic projects and to turn it into viable free-software projects. Because all software released by Red Hat is under free licenses, the partnership suggests a new channel by which academic software could find wider use.

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FOSS in Science: Harvard, Xiaopeng, Georgia Tech

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OSS
Sci/Tech
  • Making transparency work for Harvard's Dataverse Project

    A culture of transparency permeates the Dataverse project, contributing to its adoption in dozens of research institutions around the world. Headquartered at Harvard University, the Dataverse development team has more than a decade of experience operating as an open source project within an organization that values transparency: the Institute of Quantitative Social Science (IQSS). Working transparently helps the Dataverse team communicate changes to current development efforts, provides opportunities for the community to support each other, and facilitates contribution to the project.

  • Chinese Startup Goes All Out Cloning Tesla Via Open-Source Patents

    Thanks to Tesla’s decision to open-source its patents, Chinese startup Xiaopeng Motors has already manufactured several Model X clones.

  • Open Source Machine Learning Helps the Fight Against Cancer

    Here's an open invitation to steal. It goes out to cancer fighters and tempts them with a new program that predicts cancer drug effectiveness via machine learning and raw genetic data.

    The researchers who built the program at the Georgia Institute of Technology would like cancer fighters to take it for free, or even just swipe parts of their programming code, so they've made it open source. They hope to attract a crowd of researchers who will also share their own cancer and computer expertise and data to improve upon the program and save more lives together.

  • Georgia Tech researchers release open-source AI algorithm to predict effectiveness of cancer drugs

    A team of researchers from Atlanta-based Georgia Institute of Technology introduced an open-source algorithm Oct. 26 that predicts a cancer drug's effectiveness based on a patient's genetic data.

    The researchers developed the machine learning algorithm using gene expression and drug response data from the National Cancer Institute's panel of 60 human cancer cell lines. Their goal was to create an algorithm that predicts optimal drug therapies based on individual patient tumors.

    In a study of 273 cancer patients, researchers found the algorithm to be about 85 percent accurate in assessing the effectiveness of nine drugs. By releasing the algorithm on an open-source platform, they hope other researchers will participate in refining their work.

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