How Atomic AI Measures The Emotion In Your Content

How Atomic #AI Measures The Emotion In Your #Content - by @suhash_talwar @atomic_reach

  • Why Writing With Emotion is Important
    Emotional language can greatly impact how engaged a reader is with your content.
  • The emotional factor was looked at on a per article basis – using “hot” and “cold” as the indicator for the overall emotional intensity of a piece of content.
  • Soon after, we updated the feature to flag specific words as hot (emotional) or cold (not emotional) so that users had a better idea of what words were contributing to the level of emotion within a piece of content.
  • We noticed that our users would look at the emotional intensity of a piece of content, then haphazardly try and replace words.
  • After various iterations, the team was finally able to settle on a solid model for measuring emotion and was able to bake in the ability to provide recommendations to either increase or decrease the emotional intensity of the word.

If there is a single feature in our platform that has generated the most interest (but also the most confusion), it is our Emotion measure.
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The Science of AI and the Art of Social Responsibility

The @HuffingtonPost take a look at the science of #AI and the art of social responsibility:

  • But the transformational nature of artificial intelligence requires new metrics of success for our profession.
  • This year alone at least 1 billion people will be touched in some way by artificial intelligence, which is transforming everything from financial services to transportation, energy, education and retail.
  • And why IBM is a founding member of the Partnership on AI, a collaboration among Google, Amazon, Facebook, Microsoft, Apple and many scientific and nonprofit organizations charged with guiding the development of artificial intelligence to the benefit of society.
  • Opportunity: Developers of AI applications should accept the responsibility of enabling students, workers and citizens to take advantage of every opportunity in the new economy powered by cognitive systems.
  • They should help them acquire the skills and knowledge to engage safely, securely and effectively in a relationship with cognitive systems, and to perform the new kinds of work and jobs that will emerge in a cognitive economy.

By Guru Banavar, IBM’s Chief Science Officer for Cognitive Computing
I am a computer scientist and engineer, inspired by the art of the possible an…
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Facebook uses Artificial Intelligence to help spot potentially suicidal users

  • On Wednesday, Facebook announced that it is ready to take a first and significant step in building a safer and more supportive Facebook community by significantly strengthening its own suicide prevention tools (Facebook has had suicide reporting and tools for a decade).
  • Noting that live suicides had occurred on similar platforms before, Facebook is now testing a system that relies on pattern recognition based on posts previously reported for suicide risk.
  • Now, when suicide-like behavior is detected, Facebook will provide the at-risk user with resources that range from the ability to contact a friend or helpline to a few potentially helpful tips for dealing with depression without halting their stream.
  • However, Vanessa Callison-Burch, a Facebook product manager, told BBC that the social media company is hoping to avoid invading anyone’s privacy or tampering with personal dynamics between friends.
  • While Facebook’s system is still new, it is reassuring to see that the social media company is dedicated to protecting its users from adding to this troubling statistic.

On Wednesday, Facebook announced that it is ready to take a first and significant step in building a safer and more supportive Facebook community by
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The Science of AI and the Art of Social Responsibility

The science of #AI and the art of social responsibility:  via @HuffingtonPost

  • But the transformational nature of artificial intelligence requires new metrics of success for our profession.
  • This year alone at least 1 billion people will be touched in some way by artificial intelligence, which is transforming everything from financial services to transportation, energy, education and retail.
  • And why IBM is a founding member of the Partnership on AI, a collaboration among Google, Amazon, Facebook, Microsoft, Apple and many scientific and nonprofit organizations charged with guiding the development of artificial intelligence to the benefit of society.
  • Opportunity: Developers of AI applications should accept the responsibility of enabling students, workers and citizens to take advantage of every opportunity in the new economy powered by cognitive systems.
  • They should help them acquire the skills and knowledge to engage safely, securely and effectively in a relationship with cognitive systems, and to perform the new kinds of work and jobs that will emerge in a cognitive economy.

By Guru Banavar, IBM’s Chief Science Officer for Cognitive Computing
I am a computer scientist and engineer, inspired by the art of the possible an…
Continue reading “The Science of AI and the Art of Social Responsibility”

Valve wants to take a ‘machine learning’ approach to Counter-Strike anti-cheat

Valve wants to take a 'machine learning' approach to Counter-Strike anti-cheat

  • That may be true, but according to a Valve spokesperson writing in the thread, it wouldn’t be the best approach.
  • “Instead, you’d want to take a machine-learning approach, training (and continuously retraining) a classifier that can detect the differences between cheaters and normal/highly-skilled players.”
  • “The process of parsing, training, and classifying player data places serious demands on hardware, which means you want a machine other than the server doing the work.
  • And because you don’t know ahead of time who might be using this kind of cheat, you’d have to monitor matches as they take place, from all ten players’ perspectives.”
  • The spokesperson continued: “There are over a million CS:GO matches played every day, so to avoid falling behind you’d need a system capable of parsing and processing every demo of every match from every player’s perspective, which currently means you’d need a datacenter capable of powering thousands of CPU cores.”

Anti-cheat software has a lot of weight to pull in the modern age, with few major games going to market without some form of online competitive mode. Detecting and smiting cheaters is a thankless task too, with most folk ignoring anti-cheat technology unless it stops working effectively. Typically enough, Valve has a new approach in mind.During a discussion on the Counter-Strike: Global Offensive Reddit page, one user asked why Valve doesn’t implement auto-detection for spinbots – bots that literally spin on the spot, auto-killing every player in range. Other users posit quite reasonably that it wouldn’t be hard to detect this supernaturally quick and effective player behavior. That may be true, but according to a Valve spokesperson writing in the thread, it wouldn’t be the best approach.”So some bad news: any hard-coded detection of spin-botting leads to an arms race with cheat developers – if they can find the edges of the heuristic you’re using t
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Active Voice

PwC: Five Global Shifts Reshaping the World #Tech #AI #IoT #Blockchain #Drones #Robotics

  • I have always enjoyed reading the Paper Lis created by others, so thought it was about time I started one as well.
  • As a young child, I was taught that the path to success looked something like this: Study hard.
  • Google Scholar is a search engine that provides academic results to its users for free, showing links to journal articles or theses on a selected topic.
  • According to PwC, there are five global shifts reshaping the world and their implications for organizations, industries and wider society will be s…
  • Active Voice

According to PwC, there are five global shifts reshaping the world and their implications for organizations, industries and wider society will be s…
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Google is using machine learning to reduce the data needed for high-resolution images

Google is using machine learning to reduce the data needed for high-resolution images

  • Doing so reduces the data cost of each image by up to 75 percent, says Google.
  • While traditional upsampling uses fixed rules to work out which new pixels to use where, RAISR adapts its methods to each image.
  • The company says its techniques reduce data costs up to 75 percent per image
  • Last November, Google unveiled a prototype technology called RAISR that uses machine learning to make low-resolution images appear more detailed.
  • Google is using machine learning to reduce the data needed for high-resolution images

Last November, Google unveiled a prototype technology called RAISR that uses machine learning to make low-resolution images appear more detailed. Now, the company has begun the process of…
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