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Articles related to "computing"


Startup Lightmatter Tries to Speed Up Computing in Data Centers Using Light

  • It is pitching the solution to big data center operators, such as Amazon.com Inc., Facebook Inc. and Google, which is an investor via GV, venture capital arm of parent Alphabet Inc. The startup’s technology uses tiny structures called “wave guides” that redirect light.
  • The system can send data between components 100 times quicker than the fastest PC and uses 10% of the energy, according to Lightmatter co-founder Nick Harris.
  • It could also replace the giant spaghetti of cables that data center owners use to connect thousands of computer servers, saving money, he added.
  • With data centers forecast to account for more than 15% of global power use in the next five years, anything that saves electricity is valuable, Harris said.
  • With $33 million in venture funding, it’s one of a growing number of chip startups pitching novel approaches to try to win data center business from traditional suppliers such as Intel Corp.

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Object-oriented programming: History, and challenges for the next fifty years

  • Object-oriented programming is inextricably linked to the pioneering work of Ole-Johan Dahl and Kristen Nygaard on the design of the Simula language, which started at the Norwegian Computing Centre in the Spring of 1961.
  • However, object-orientation, as we think of it today—fifty years later—is the result of a complex interplay of ideas, constraints and people.
  • Dahl and Nygaard would certainly recognise it as their progeny, but might also be amazed at how much it has grown up.
  • This article is based on a lecture given on 22nd August 2011, on the occasion of the scientific opening of the Ole-Johan Dahl hus at the University of Oslo.
  • It looks at the foundational ideas from Simula that stand behind object-orientation, how those ideas have evolved to become the dominant programming paradigm, and what they have to offer as we approach the challenges of the next fifty years of informatics.

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Python Is About to Get the Squeeze

  • Businesses urgently required a language for quick development with low barriers of entry that could help manage large-scale data and scientific computing tasks.
  • Rust is still trying to catch up with the machine learning community, and so I believe Swift and Julia are the languages that will dethrone Python and eventually rule data science.
  • The JIT compiler either generates the machine code right before it’s executed or uses previously stored, cached compilations, which makes it as performant as statically typed languages.
  • As compiled languages that offer type annotations, Swift and Julia are a lot faster and robust for development than Python.
  • Instead Swift, thanks to its differential programming support and ability to work at a low level like C, will potentially be used to replace the underlying deep learning tools.

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Python Is About to Get the Squeeze

  • Businesses urgently required a language for quick development with low barriers of entry that could help manage large-scale data and scientific computing tasks.
  • Rust is still trying to catch up with the machine learning community, and so I believe Swift and Julia are the languages that will dethrone Python and eventually rule data science.
  • The JIT compiler either generates the machine code right before it’s executed or uses previously stored, cached compilations, which makes it as performant as statically typed languages.
  • As compiled languages that offer type annotations, Swift and Julia are a lot faster and robust for development than Python.
  • Instead Swift, thanks to its differential programming support and ability to work at a low level like C, will potentially be used to replace the underlying deep learning tools.

save | comments | report | share on


Python Is About to Get the Squeeze

  • Businesses urgently required a language for quick development with low barriers of entry that could help manage large-scale data and scientific computing tasks.
  • Rust is still trying to catch up with the machine learning community, and so I believe Swift and Julia are the languages that will dethrone Python and eventually rule data science.
  • The JIT compiler either generates the machine code right before it’s executed or uses previously stored, cached compilations, which makes it as performant as statically typed languages.
  • As compiled languages that offer type annotations, Swift and Julia are a lot faster and robust for development than Python.
  • Instead Swift, thanks to its differential programming support and ability to work at a low level like C, will potentially be used to replace the underlying deep learning tools.

save | comments | report | share on


Python Is About to Get the Squeeze

  • Businesses urgently required a language for quick development with low barriers of entry that could help manage large-scale data and scientific computing tasks.
  • Rust is still trying to catch up with the machine learning community, and so I believe Swift and Julia are the languages that will dethrone Python and eventually rule data science.
  • The JIT compiler either generates the machine code right before it’s executed or uses previously stored, cached compilations, which makes it as performant as statically typed languages.
  • As compiled languages that offer type annotations, Swift and Julia are a lot faster and robust for development than Python.
  • Instead Swift, thanks to its differential programming support and ability to work at a low level like C, will potentially be used to replace the underlying deep learning tools.

save | comments | report | share on


Review: We do not recommend the $299 Oculus Quest 2 as your next VR system

  • Part of that comes from Facebook's aggressive policy about making Facebook social media accounts (whose terms of service revolve around a "real name" policy) mandatory to use new Oculus VR headsets, including the Quest 2.
  • Attachment of a social media account and its massive Web of personally identifying data (as accumulated by everything from service log-ins to average Web-browsing cookies) to computing hardware (VR headsets, phones, computers, TVs, etc) is quite frankly an irresponsible move on Facebook's part.
  • Or maybe in spite of all of the bad news, you'd make a deal with the Mephi-zuck-eles for a higher-performing, "all-in-one" Oculus Quest that's now powered by a Snapdragon 865-equivalent SoC with more RAM, more pixels, and a higher refresh rate.
  • Those piled up to the point where Facebook will need to launch a Quest "2+" revision before I'm ready to recommend this headset.

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