How Atomic AI Measures The Emotion In Your Content

How Atomic #AI Measures The Emotion In Your #Content ​#contentmarketing

  • 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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Awesome Deep Learning: Most Cited Deep Learning Papers

Awesome #DeepLearning: Most Cited Deep Learning Papers  @TerryUm_ML

  • This post introduces a curated list of the most cited deep learning papers (since 2012), provides the inclusion criteria, shares a few entry examples, and points to the full listing for those interested in investigating further.
  • Rather than providing overwhelming amount of papers, We would like to provide a curated list of the awesome deep learning papers which are considered as must-reads in certain research domains.
  • Background

     

    Before this list, there exist other awesome deep learning lists, for example, Deep Vision and Awesome Recurrent Neural Networks.

  • Also, after this list comes out, another awesome list for deep learning beginners, called Deep Learning Papers Reading Roadmap, has been created and loved by many deep learning researchers.
  • Although the Roadmap List includes lots of important deep learning papers, it feels overwhelming for me to read them all.


This post introduces a curated list of the most cited deep learning papers (since 2012), provides the inclusion criteria, shares a few entry examples, and points to the full listing for those interested in investigating further.

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GitHub

Nice work by @hereismari getting started with @TensorFlow on Android!

  • If you want to make your own version of this app or want to know how to save your model and export it for Android or other devices check the very simple tutorial bellow.
  • A full example can be seen here

    Keep an in memory copy of eveything your model learned (like biases and weights) Example: , where w was learned from training.

  • Rewrite your model changing the variables for constants with value = in memory copy of learned variables.
  • Example: Also make sure to put names in the input and output of the model, this will be needed for the model later.
  • Example:

    Export your model with:

    tf.train.write_graph(, , .

mnist-android-tensorflow – Handwritten digits classification from MNIST with TensorFlow in Android; Featuring Tutorial!
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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.
Continue reading “How Atomic AI Measures The Emotion In Your Content”

Digital Transformation in Banking: Making Progress and Hitting Roadblocks

#Digital Transformation in #Banking: Progress and Roadblocks

 

#fintech #CIO #AI #IT #tech

  • One third of banking executives participating in a study said that marketing owns the end-to-end customer relationship, but only 14% feel that marketing should own their institution’s digital strategy.
  • As financial institutions look at how best to adapt their current practices to meet the needs of customers across an expanding array of digital channels, banking executives look for insights to inform their digital transformation strategies.
  • With 87% of the financial institution respondents saying that technology is intrinsic to digital transformation and must be considered in tandem with strategy, it’s a natural fit for CIOs to lead the way in vetting and implementing the technical platforms and solutions that will form the backbone of an organization’s digital strategy.
  • Still, a financial organization that can establish a culture free of silos – and carry out effective digital transformation quickly and successfully – will certainly earn itself an effective competitive advantage and be able to deliver a differentiated level of customer experience.
  • By incorporating advice from other industry leaders and fostering a company culture ready to embrace cooperation alongside new technology, financial institutions can best execute the digital transformations necessary to keep pace and potentially stand out in their industry.

Two out of every five financial institutions say they are only in the infancy of their digital transformation strategy.
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Demis Hassabis: The World’s 100 Most Influential People

How Demis Hassabis is revolutionizing artificial intelligence #TIME100

  • At least a decade ahead of expectations, Demis Hassabis and his team at DeepMind created AlphaGo, a software program that defeated Lee Sedol, one of the world’s best players, at the complex game of Go.
  • Demis is one of the leading scientists creating AI breakthroughs, with three Nature papers in the past two years.
  • Of equal importance, however, Demis is deeply committed to keeping AI safe.
  • Demis has been a leader in establishing ethical guidelines to keep AI accountable.
  • If we achieve this vision, it’s likely Demis will have played a large part.

Inventor of intelligence
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Is Artificial Intelligence the Next Dot-Com Bubble?

Is #ArtificialIntelligence the Next Dot-Com Bubble? 

 #fintech #VC #AI @nanalyzetweets

  • We’ll stick to playing rock-paper-scissors with AI, but all of this is leading to some serious visibility for AI as an emerging technology – which as investors make us want to get some skin in the game.
  • The recent news that artificial intelligence (AI) startup Afiniti may have confidentially filed for IPO was the first time that we started to feel like this thing might be revving up for real now.
  • It wasn’t just because this would be the first pure-play AI startup to see an IPO, it was because we really couldn’t believe how effective Afiniti’s technology was in adding value.
  • Secondly we’re also seeing a very large number of AI startups getting into the game (over 1,500) which is the same sort of pile-on mentality we saw in the dot-com era.
  • Now you just add a tagline to that same website that says “powered by AI” and now you’re an “AI company”.

If you’ve played Texas Hold’em, then you know how tough it is to be a good poker player. Lots of venture capitalists like to play poker, so it wasn’t surprising to see one who thought to himself “let’s see how good artificial intelligence (AI) really is“. He consulted a team of engineers and computer scientists to see where they might be able to exploit the AI agent named Lengpudashi. They then played 36,000 hands over 5 days and the AI agent kicked the isht out of them. We’ll stick to playing rock-paper-scissors with AI, but all of this is leading to some serious visibility for AI as an emerging technology – which as investors make us want to get some skin in the game. The problem is, there aren’t many ways to do that yet.
Continue reading “Is Artificial Intelligence the Next Dot-Com Bubble?”