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Articles related to "data"


Box Shield launches in private beta to prevent data compromise

  • Last year, Box took the wraps off of Box Shield, a machine learning-based security platform that provides admins an overview of their company’s content while flagging potential instances of data compromise.
  • Account admins can define custom labels and per-label policies that combine multiple protocols, including (but not limited to) shared link, external collaborator, download, application, and file transfer protocol (FTP) restrictions.
  • With the policies in place, a manager could prevent unauthorized external or internal users (or domains) from accessing files on unapproved devices and apps (like mobile or desktop), or ensure that only whitelisted files and folders can be transferred and uploaded via FTP.
  • Today’s announcement follows Box Skills, a suite of third-party apps that add features and functionality to uploaded files, and the Box Skills Kit, a set of APIs, developer tools, and documentation for designing custom Box Skills on platforms like Amazon Web Services, Google Cloud, IBM’s Watson, and Microsoft Azure.

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The State of Transfer Learning in NLP

  • In the span of little more than a year, transfer learning in the form of pretrained language models has become ubiquitous in NLP and has contributed to the state of the art on a wide range of tasks.
  • Recent examples of this trend are ERNIE 2.0, XLNet, GPT-2 8B, and RoBERTa. The latter in particular finds that simply training BERT for longer and on more data improves results, while GPT-2 8B reduces perplexity on a language modelling dataset (though only by a comparatively small factor).
  • The information that a model captures also depends how you look at it: Visualizing activations or attention weights provides a bird's eye view of the model's knowledge, but focuses on a few samples; probes that train a classifier on top of learned representations in order to predict certain properties (as can be seen above) discover corpus-wide specific characteristics, but may introduce their own biases; finally, network ablations are great for improving the model, but may be task-specific.

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Writing Tests with PyTest and Factory

  • I like to use pytest with pytest-factoryboy to generate testing data.
  • Fixtures defined in conftest.py file will be recognized in any test file.
  • "Registering" the factories lets you inject them into your tests with a lowercase-underscore class name.
  • In this same file, I'm defining fixtures with @pytest.fixture() which I'll use in my tests, and injecting them with the factories I just registered.
  • I'm passing in my fixture data into my test method, and also passing in a factory called move because that's what I'm mainly testing here.
  • In order to test player moves, I first needed to have created the players, the game, and the round, which is what I did in my conftest.py file.
  • I only need to do this once, and I don't need to import the fixtures because anything declared in conftest.py is visible to the test files.

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Announcing Cisco Data Intelligence Platform

  • One such area is Artificial Intelligence/Machine Learning (AI/ML), which has seen tremendous development with bringing in new frameworks and new forms of compute (CPU, GPU and FPGA) to work on data to provide key insights.
  • While data lakes have historically been data intensive workloads, these advancements in technologies have led to a new growing demand of compute intensive workloads to operate on the same data.
  • IT is demanding newer solutions to enable data scientists to operate on both a data lake and an AI/ML platform (or a compute farm) without worrying about the underlying infrastructure.
  • Cisco Data Intelligence Platform caters to the evolving architecture bringing together a fully scalable infrastructure with centralized management and fully supported software stack (in partnership with industry leaders in the space) to each of these three independently scalable components of the architecture including data lake, AI/ML and Object stores.

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EU antitrust regulators have Facebook’s Libra currency in their sights

  • European Union antitrust regulators have begun conducting a preliminary investigation into Facebook’s plans to launch a digital currency, according to a new report from Bloomberg.
  • The EU is also examining the integration of Libra wallets into Facebook’s WhatsApp and Messenger services, according to Bloomberg.
  • Facebook and the European Commission declined to comment to Bloomberg on the potential investigation.
  • The European Commission would not be the first regulator to have raised concerns about the digital currency, which will be run by a group of companies, including Facebook, as part of the Libra Association.
  • In the US, Facebook’s cryptocurrency chief David Marcus has faced questions from the House Financial Services committee, during which one representative told him that they didn’t think Facebook should launch Libra at all.
  • Facebook itself has said that it won’t launch Libra until it has “fully addressed regulatory concerns” surrounding the digital currency.

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Tupelo as it relates to IPLD and IPFS

  • At the highest level, IPLD is a way to link data in such a way that the links are what is called “content addressable.” In practice, that means that the link to a piece of data includes a hash of the data and so you can always be sure of the data you receive as a result of following a link.
  • Tupelo adds in a DLT layer to make sure that the whole world knows the state of a certain object.
  • Preventing double-states of ChainTrees (IPLD Trees) and enforcing transactions allows for both token exchange and object ownership on top of the IPLD/IPFS primitives, while allowing data exchange and availability to happen in the IPFS-standard way.
  • If you are coming from the IPLD stack, you can think of Tupelo as a trusted pointer into the IPLD merkle forest, both making sure that the content you are seeing is the content shown to the world and making sure the data has followed the rules around payments and ownership.

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🎉Announcing Floodgate: a "load more" component for React 🌊

  • Floodgate is a "load more" component for React.js that takes the complexity of managing and updating queued data and turns it into an intuitive experience.
  • Strings, parsed JSON objects, React components, even JavaScript functions can be passed in; remember that Floodgate leaves the rendering and implementation of these items up to the developer.
  • By utilizing React's lifecycle methods and custom callback props, Floodgate's props can be entirely managed by a parent component's state, allowing the instance's data to be asynchronously updated or end-users to have more control over how many items are loaded.
  • The render prop function exposes a number of Floodgate methods to be called by its children components; namely, those are loadNext, loadAll, reset, and exportState.
  • Floodgate utilizes the React's Context API as of v0.6.0, preventing the need for developers to pass down methods exposed in the render prop to wherever they are needed using the FloodgateContext export.

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'Record number of fires' in Brazilian rainforest

  • Brazil's Amazon rainforest has seen a record number of fires this year, according to new data from the country's space research agency.
  • The National Institute for Space Research (Inpe) said its satellite data showed an 83% increase on the same period in 2018.
  • It comes weeks after President Jair Bolsonaro sacked the head of the agency amid rows over its deforestation data.
  • Ricardo Mello, head of the World Wide Fund for Nature (WWF) Amazon Programme, said the fires were "a consequence of the increase in deforestation seen in recent figures".
  • Last month, the far-right president accused Inpe's director of lying about the scale of deforestation in the Amazon and trying to undermine the government.
  • It came after Inpe published data showing an 88% increase in deforestation there in June compared to the same month a year ago.

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Facebook’s ‘cryptocurrency’ Libra reportedly facing EU competition probe

  • The European Union’s antitrust regulators are “currently investigating potential anti-competitive behavior” amid concerns Facebook would monopolize the payments realm and unfairly shut out competitors.
  • Unsurprisingly, regulators are worried about Libra creating “possible competition restrictions” on the customer information that will be exchanged and the use of consumer data.
  • This investigation follows on from another preliminary probe led by the EU that’s looking at how Facebook could potentially use its power to shut out the competition.
  • As such, Switzerland‘s privacy regulator, the Federal Data Protection and Information Commissioner (FDPIC), is expecting to receive details on Libra by the end of this month, Reuters reports.
  • It comes after David Marcus, Facebook’s Libra project lead told US senators earlier this year that he expected the Swiss agency to be the ‘cryptocurrency’s’ privacy regulator.
  • Back in July, the FDPIC requested additional information from the Libra Association.

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🎉Announcing Floodgate: a "load more" component for React 🌊

  • Floodgate is a "load more" component for React.js that takes the complexity of managing and updating queued data and turns it into an intuitive experience.
  • Strings, parsed JSON objects, React components, even JavaScript functions can be passed in; remember that Floodgate leaves the rendering and implementation of these items up to the developer.
  • By utilizing React's lifecycle methods and custom callback props, Floodgate's props can be entirely managed by a parent component's state, allowing the instance's data to be asynchronously updated or end-users to have more control over how many items are loaded.
  • The render prop function exposes a number of Floodgate methods to be called by its children components; namely, those are loadNext, loadAll, reset, and exportState.
  • Floodgate utilizes the React's Context API as of v0.6.0, preventing the need for developers to pass down methods exposed in the render prop to wherever they are needed using the FloodgateContext export.

save | comments | report | share on