How Artificial Intelligence is Changing Web Writing

How #ArtificialIntelligence is Changing Web Writing  #ai

  • In short, in the universe of pages existing in a (at the time almost) shapeless web, Page and Brin wanted to organize that information to make it become knowledge.
  • Out of the more than 200 factors that Google accounts for when deciding whether the content on the web is relevant, RankBrain became the third most relevant.
  • First, the semantic web is a set of rules and standards that make human language readable to machines.
  • In semantic web jargon an entity is a subject which has unambiguous meaning because it has a strong contextual foundation.
  • In other words, instead of going from writing to web writing as unconsciously as the human race transitioned from hunter-gathering to farming, it is time to take this step forward deliberately and intentionally.

When Larry Page and Sergey Brin invented PageRank back in 1996, they had one simple idea in mind: Organize the web based on “link popularity.” In…
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Scientific Computing

How are we advancing science with #AI? Learn more:

  • emergence of big data that has made it possible to create and train a data structure.
  • Big data now exists, and it’s increasingly a huge opportunity.”
  • Will Ramey, senior product manager for Accelerated Computing at NVIDIA, credits a major factor for this “Big Bang of AI.”
  • F rom self-driving cars to hi-tech medical imaging modalities, artificial intelligence (AI) is transforming the landscape of a variety of industries.
  • “With big data, came the new challenge of understanding and extracting insights from that data,” said Ramey.

Scientific Computing provides focused coverage of software and related hardware technologies for the scientific and engineering communities, highlighting the latest applications, best practices and integration strategies that can aid in advancing research and in delivering quality results better, faster and cheaper. Key coverage areas include informatics, data analysis, integration and big data. Full-featured Scientific Computing and HPC Source e-magazines offer immediate interaction through audio, video and rich-media pages. Free subscriptions for these digital magazines, as well as the NewsWire daily e-newsletter, are available at www.ScientificComputing.com, where you can also find new product announcements, in-depth expert commentary and educational webcasts.
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Delivering Smarter Patient Care Decisions With Artificial Intelligence

Artificial Intelligence and the Future of Improved Patient Care #DigitalHealth

  • You probably found the page because one of our subscribers used MailChimp to send you an email campaign, and you traced a link in the email back to investigate.
  • We send more than 1 billion emails every day, and we help our customers comply with spam laws and best practices so they can get their campaigns into their subscribers’ inboxes.
  • MailChimp is an email-marketing service that serves more than 14 million companies of all shapes and sizes, from all over the world.
  • ______
  • / ___M ]__

In this week’s episode of StartUp Health NOW!, Health Transformer and CEO of MDOps Avinash Kodey shares how he is applying AI technology to deliver smarter patient care decisions without compromising efficiency.
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Dmitriy Genzel’s answer to What is the difference between AI, Machine Learning, NLP, and Deep Learning?

#ArtificialIntelligence #MachineLearning #DeepLearning #NLP... what's the difference?

  • PhD in CS, Machine Learning Lead at Quora
  • Deep learning is one kind of machine learning that’s very popular now.
  • To draw a distinction with AI, if I can write a very clever program that has human-like behavior, it can be AI, but unless its parameters are automatically learned from data, it’s not machine learning.
  • It involves a particular kind of mathematical model that can be thought of as a composition of simple blocks (function composition) of a certain type, and where some of these blocks can be adjusted to better predict the final outcome.
  • AI ( Artificial intelligence ) is a subfield of computer science, that was created in the 1960s, and it was (is) concerned with solving tasks that are easy for humans, but hard for computers.

AI (Artificial intelligence) is a subfield of computer science, that was created in the 1960s, and it was (is) concerned with solving tasks that are easy for humans, but hard for computers. In particular, a so-called Strong AI would be a system that can do anything a human can (perhaps without purely physical things). This is fairly generic, and includes all kinds of tasks, such as planning, moving around in the world, recognizing objects and sounds, speaking, translating, performing social or business transactions, creative work (making art or poetry), etc.
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Dmitriy Genzel’s answer to What is the difference between AI, Machine Learning, NLP, and Deep Learning?

What is the difference between AI, ML, NLP, and Deep Learning? by Dmitriy Genzel, PhD in CS

  • Deep learning is one kind of machine learning that’s very popular now.
  • To draw a distinction with AI, if I can write a very clever program that has human-like behavior, it can be AI, but unless its parameters are automatically learned from data, it’s not machine learning.
  • It involves a particular kind of mathematical model that can be thought of as a composition of simple blocks (function composition) of a certain type, and where some of these blocks can be adjusted to better predict the final outcome.
  • AI ( Artificial intelligence ) is a subfield of computer science, that was created in the 1960s, and it was (is) concerned with solving tasks that are easy for humans, but hard for computers.
  • Submit any pending changes before refreshing this page.

AI (Artificial intelligence) is a subfield of computer science, that was created in the 1960s, and it was (is) concerned with solving tasks that are easy for humans, but hard for computers. In particular, a so-called Strong AI would be a system that can do anything a human can (perhaps without purely physical things). This is fairly generic, and includes all kinds of tasks, such as planning, moving around in the world, recognizing objects and sounds, speaking, translating, performing social or business transactions, creative work (making art or poetry), etc.
Continue reading “Dmitriy Genzel’s answer to What is the difference between AI, Machine Learning, NLP, and Deep Learning?”

Listing Objects

Get info on how long it took to create Amazon ML objects to estimate future training:

  • The date and time when Amazon ML finished creating this object.
  • To see a list of the last 1,000 objects that you’ve created, in the Amazon ML console, open the Objects dashboard.
  • The object descriptions include the same information for each of the object types that is displayed in the console, including details that are specific to an object type.
  • The columns on the Objects dashboard show the following information about each object.
  • To see more details about an object, including details that are specific to that object type, choose the object’s name or ID.

Read the full article, click here.


@awscloud: “Get info on how long it took to create Amazon ML objects to estimate future training:”


List Amazon ML objects and their details.


Listing Objects

Yann LeCun’s answer to What are your recommendations for self-studying machine learning?

Facebook director of AI research @ylecun’s recommendations for self-studying deep learning

  • A recent series of 8 lectures on deep learning that I gave at Collège de France in Paris.
  • You can get a broad idea of deep what deep learning is about through tutorial lectures that are available from the Web.
  • Nikhil Dandekar , worked on machine learning at Microsoft, Foursquare and Quora
  • my 2015 course on Deep Learning at NYU: deeplearning2015:schedule | CILVR Lab @ NYU (unfortunately, the videos of the lectures had to be taken down due to stupid legal reasons, but the slides are there).
  • There is tons of on-line material, tutorials and courses on ML, including Coursera lectures.

Read the full article, click here.


@kylebrussell: “Facebook director of AI research @ylecun’s recommendations for self-studying deep learning”


I’ll respond more specifically for deep learning. You can get a broad idea of deep what deep learning is about through tutorial lectures that are available from the Web. Most notably:


Yann LeCun’s answer to What are your recommendations for self-studying machine learning?