These programmers taught an AI how to understand tattoos

These programmers taught an #AI how to understand tattoos

  • The process involved using a deep-learning framework called Caffe, and feeding it data-sets with images representative of different tattoo styles.
  • Once the initial training session was complete, the AI could identify the style of a tattoo with pretty impressive accuracy.
  • While the AI isn’t implemented into the app yet (they’re still feeding it data) they intend to finish training the AI then go forward from there.
  • AI will help us to classify the remaining 250k pictures… Classification is really important for us because, based on it, we can show users personalized feeds depending on what styles they like, what artists they follow, what those artists are specialized in, etc.
  • Without AI to sort images, a person has to view each one, decide what style it represents, tag the image, and then create hashtags so that other users can find it.

A pair of developers at Tattoodo developed a neural-network capable of processing pictures of tattoos and determining the style of the ink in the images.
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Facebook’s advice to students interested in artificial intelligence – Besim on Data

Facebook’s advice to students interested in artificial intelligence.  #WomenScienceDay

  • That’s the gist of the advice to students interested in AI from Facebook’s Yann LeCun and Joaquin Quiñonero Candela who run the company’s Artificial Intelligence Lab and Applied Machine Learning group respectively.
  • If differential equations represents the electricity that powers machine learning, statistics represents the gears of the machine itself — as the company touches on in a series of AI explainer videos we linked to at the bottom of this post.
  • How else would a fledgling machine learning student learn to leverage neuroeconomics and cognitive bias to target ads?
  • Amidst all the talk of News Feed bias, it’s important to remember that there is a human behind every application of machine learning.
  • Most of these tips are self-explanatory: find a professor to work with, consider working with PhD students who have more time on their hands and try to secure an industry-focused internship regardless of your future aspirations to understand how AI works in the real world.

That’s the gist of the advice to students interested in AI from Facebook’s Yann LeCun and Joaquin Quiñonero Candela

 who run the company’s Artificial Intelligence Lab and Applied Machine Learning group respectively.
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Facebook’s advice to students interested in artificial intelligence

Facebook’s advice to students interested in #DeepLearning #AI #MachineLearning #DataScience

  • Facebook turns its attention to the actual mechanics of getting a job in the field of machine learning.
  • XNOR.ai frees AI from the prison of the supercomputer
  • With a $1.5M seed round, Eloquent Labs mixes AI and Mechanical Turk to fix customer service
  • Kristen Stewart co-authored a paper on style transfer and the AI community lost its mind
  • Amidst all the talk of News Feed bias , it’s important to remember that there is a human behind every application of machine learning.

Math. Math. Oh and perhaps some more math. That’s the gist of the advice to students interested in AI from Facebook’s Yann LeCun and Joaquin Quiñonero..
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CHATBOTS EXPLAINED: Why businesses should be paying attention to the chatbot revolution

#Chatbots Ecosystem Explained: #BigData #DeepLearning #MachineLearning #DataScience #AI

  • We compare the potential of chatbot monetization on a platform like Facebook Messenger against the iOS App Store and Google Play store.
  • CHATBOTS EXPLAINED: Why businesses should be paying attention to the chatbot revolution
  • Chatbots could be lucrative for messaging apps and the developers who build bots for these platforms, similar to how app stores have developed into moneymaking ecosystems.
  • In a new report from BI Intelligence, we explore the growing and disruptive bot landscape by investigating what bots are, how businesses are leveraging them, and where they will have the biggest impact.
  • The chatbot ecosystem is already robust, encompassing many different third-party chat bots, native bots, distribution channels, and enabling technology companies.

In this report, we explore the growing chatbot landscape by investigating what chatbots are, how businesses leverage them, and where they will have the…
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Facebook’s advice to students interested in artificial intelligence

  • Facebook turns its attention to the actual mechanics of getting a job in the field of machine learning.
  • Amazon isn’t playing nice with Plex’s new cloud service
  • Posted yesterday by John Mannes ( @JohnMannes )
  • Logojoy turns design into an AI-powered, iterative process
  • Once there, students should work to address a specific problem and try to release a piece of open source code before all is said and done.

Math. Math. Oh and perhaps some more math. That’s the gist of the advice to students interested in AI from Facebook’s Yann LeCun and Joaquin Quiñonero..
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Google DeepMind AI destroys human expert in lip reading competition

.@Google DeepMind #AI destroys human expert in lip reading competition

  • Google DeepMind also recently was able to get its AI systems to sound more human with advanced text-to-speech technology innovations.
  • Oxford University researchers partnered with Google on a new AI tool that reads lips, and the results were significant.
  • Oxford University and Google DeepMind have built an AI tool that can read lips far better than a professional human lip-reader, which could help the hearing impaired.
  • Google DeepMind wins again: AI trounces human expert in lip-reading face-off (ZDNet)
  • According to a report from New Scientist , the human expert deciphered 12.4% of their words, while the AI system got 46.8% correct.

Oxford University researchers partnered with Google on a new AI tool that reads lips, and the results were significant.
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CHATBOTS EXPLAINED: Why businesses should be paying attention to the chatbot revolution

CHATBOTS EXPLAINED! @Supertextnow Why they are the next big thing #AI #FinTech #Startups

  • We compare the potential of chatbot monetization on a platform like Facebook Messenger against the iOS App Store and Google Play store.
  • CHATBOTS EXPLAINED: Why businesses should be paying attention to the chatbot revolution
  • The chatbot ecosystem is already robust, encompassing many different third-party chat bots, native bots, distribution channels, and enabling technology companies.
  • Chatbots could be lucrative for messaging apps and the developers who build bots for these platforms, similar to how app stores have developed into moneymaking ecosystems.
  • Chatbots are particularly well suited for mobile – perhaps more so than apps.

Read the full article, click here.


@sbcFinTech: “CHATBOTS EXPLAINED! @Supertextnow Why they are the next big thing #AI #FinTech #Startups”


Advancements in artificial intelligence…


CHATBOTS EXPLAINED: Why businesses should be paying attention to the chatbot revolution