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Articles related to "language"


The future of AI journalism is less hyperbole and smarter readers

  • The Guardian’s Oscar Schwartz wrote an article in 2018 titled “The discourse is unhinged: how the media gets AI alarmingly wrong.” In it, he discusses the 2017 hype-explosion surrounding Facebook’s AI research lab developing a pair of chat bots that created a short-hand language for negotiating.
  • While it’s true that there’s a resource gap between AI journalists and the researchers and developers we cover, there’s also, typically, an education gap too.
  • Experts can point to the inevitable failure of the most hyperbolic claims to manifest as proof that journalists are messing up, but it takes more than just due diligence and rigor to avoid the toughest trappings.
  • Many of us aren’t trained developers or researchers, we’re technology journalists who cover AI.
  • With keynotes by experts from companies like Spotify and RSA, our Neural track will take a deep dive into new innovations, ethical problems, and how AI can transform businesses.

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HP offers its investors billions in shareholder returns to avoid a Xerox tie-up

  • All investors have to do to get the goods is reject the Xerox deal.
  • What HP is telling investors is that it intends to use all of the cash it generates to reward their ownership of shares in its business.
  • This will come in the form of buybacks (concentrating future earnings on fewer shares, raising the value of held equity) and dividends (rising payouts to owners as HP itself makes more money), powered in part by cost-cutting (boosting cash generation and profitability).
  • Shares of HP are up 6% as of the time of writing, raising the value of HP’s consumer-focused spinout to just under $34 billion.
  • And more recently, in an attempt to convince shareholders to vote in favor of the deal, Xerox sweetened the deal to $34 billion or $24 a share.

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SwiftUI Defaults Considered Harmful

  • First, the general approach SwiftUI is taking (reactive declarative data-driven UI framework) is really solid and considered state-of-the-art as of the current day of the year.
  • IMO the most difficult thing about SwiftUI is it is very non-discoverable and the documentation is incredibly sparse, and so you can only really know that by digging into the system quite a lot (that one is pretty easy, but alignments are incredibly subtle beasts).
  • You might be happy with your layout in a simulator, but somewhere on some weird iPad model in a particular orientation SwiftUI kindly sets padding to a bigger value and breaks your layout.
  • Fourth, even if you’ve made a perfect application and tested it thoroughly in all possible variations, who guarantees that tomorrow Apple will not get bored with the current design language and release SwiftUI 5.6.7 with completely different defaults?

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Is Flux Better Than Tensorflow?

  • Fl ux is a machine-learning library for the multi-paradigm, fast, MIT-developed statistical programming language, Julia.
  • Tensorflow powers the gradient models behind a lot of modern machine-learning algorithms, including those used by Google, Nvidia, QualComm, Lenovo, and hundreds more.
  • Flux is a great machine-learning framework because it brings with it a lot of interesting ideas and some really cool and easy syntax.
  • In this situation, Julia loses a lot of the support that an enormous language like Python carries with it.
  • Julia is certainly still a baby, and lots of packages are teetering on the edge of being inclusive enough to be depended on, but regardless of its young age Julia definitely stands out as a great language for now and the future in Data Science.

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Modern, functional Common Lisp: Myths and best practices

  • In particular, note that slime-who-specializes lists the methods of a given class, which answers a common complaint coming from people used to languages from the Algol family: the ability to complete the methods of the foo class by typing foo.<TAB>.
  • As with many languages, Common Lisp packages can be use-d, which means all symbols will be merged in the current name space, or import-ed, which means all symbols will be accessible only via the package prefix.
  • Sadly, since it’s a function, it won’t be called at compilation time and thus will yield an error if you attempt to access the symbol from a foreign package at this point.
  • Since this is rather lengthy, I recommend you use Serapeum’s export-* macros: https://github.com/ruricolist/serapeum/blob/master/REFERENCE.md#export-always-symbols-optional-package-nil-package-supplied.

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Is Flux Better Than Tensorflow?

  • Fl ux is a machine-learning library for the multi-paradigm, fast, MIT-developed statistical programming language, Julia.
  • Tensorflow powers the gradient models behind a lot of modern machine-learning algorithms, including those used by Google, Nvidia, QualComm, Lenovo, and hundreds more.
  • Flux is a great machine-learning framework because it brings with it a lot of interesting ideas and some really cool and easy syntax.
  • In this situation, Julia loses a lot of the support that an enormous language like Python carries with it.
  • Julia is certainly still a baby, and lots of packages are teetering on the edge of being inclusive enough to be depended on, but regardless of its young age Julia definitely stands out as a great language for now and the future in Data Science.

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Fuchsia Programming Language Policy

  • This document describes which programming languages the Fuchsia project uses and supports for production software on the target device, both within the Fuchsia Platform Source Tree and for end-developers building for Fuchsia outside the Fuchsia Source Platform Tree.
  • For example, this policy does not apply to zxdb (a debugger) because zxdb is a developer tool; the policy does apply to pkgfs because pkgfs (a file system) executes in the normal, end-user operation of the device.
  • The Fuchsia Platform Source Tree can absorb larger changes to the Fuchsia system and its underlying technologies than end-developers because changes that impact only the Fuchsia Platform Source Tree can be executed without coordination with other groups of people.
  • End-developers are people who write software for Fuchsia outside of the Fuchsia Platform Source Tree.

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What the Data is Telling Us About Machine Translation

  • A brief historical survey of the state of neural machine translation models and how they compare with each other and human translation.
  • In this approach, the entire passage to be translated was input and processed by data structures and algorithms for various internal and external connections.
  • The structure is simpler than phrased-based approaches: a single sequence model predicts one word at a time, based on deep learning and representation learning techniques of the entire source sentence.
  • In recent years, Facebook’s AI group leveraged the unmatched database of the conversations and posts of billions of FB users to beat the competition in several tasks 2019’s Fourth Conference on Machine Translation (known as WMT).
  • It is ironic that evaluations of NMT quality to data have been done by human experts comparing the translations of machines to those of humans.

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What the Data is Telling Us About Machine Translation

  • A brief historical survey of the state of neural machine translation models and how they compare with each other and human translation.
  • In this approach, the entire passage to be translated was input and processed by data structures and algorithms for various internal and external connections.
  • The structure is simpler than phrased-based approaches: a single sequence model predicts one word at a time, based on deep learning and representation learning techniques of the entire source sentence.
  • In recent years, Facebook’s AI group leveraged the unmatched database of the conversations and posts of billions of FB users to beat the competition in several tasks 2019’s Fourth Conference on Machine Translation (known as WMT).
  • It is ironic that evaluations of NMT quality to data have been done by human experts comparing the translations of machines to those of humans.

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What people in tech had to say about JavaScript when it debuted in 1995 (2017)

  • Time and time again JavaScript is crowned the most popular programming language in the World.
  • Whilst BrendanEich was hard at work creating the now much loved language some twenty-plus years ago, the O.J Simpson trial was well underway, Ross and Rachel weren’t quite on a break, yet — and Toy Story was mere weeks away from hitting theatres.
  • Oh, and Wikipedia informs me that 1995 also marks the year in which ISP’s like AOL and Prodigy offered up mainstream access to the World Wide Web for the first time, releasing browsers that made ‘surfing the web’ easily accessible to the general public.
  • Sounds like it was the perfect time to be creating a programming language for browsers.
  • To mark the release of JavaScript a joint press release was issued from Netscape and Sun Microsystems on December 4, 1995.
  • The press release then went on to share praise from then industry bigwigs.

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