Andrew Ng: Why AI Is the New Electricity

What’s slowing down #AI adoption? 

Two problems: scarcity of data and talent. —@AndrewYNg

  • Still, computer scientist and Coursera co-founder Andrew Ng says, fears that AI will replace humans are misplaced: “Despite all the hype and excitement about AI, it’s still extremely limited today relative to what human intelligence is.”
  • “Just as electricity transformed almost everything 100 years ago, today I actually have a hard time thinking of an industry that I don’t think AI will transform in the next several years,” Ng says.
  • “I would say the most scarce resource today is actually talent, because AI needs to be customized for your business context,” Ng says.
  • “Worrying about evil AI killer robots today is a little bit like worrying about overpopulation on the planet Mars.”
  • Evil AI hype, he says, is being used to whitewash a much more serious issue, which is job displacement.

A computer scientist discusses artificial intelligence’s promise, hype, and biggest obstacles.
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How 4 Agencies Are Using Artificial Intelligence as Part of the Creative Process – Adweek

How 4 agencies are using artificial intelligence as part of the creative process:

A couple of weeks ago, Coca-Cola’s global senior digital director Mariano Bosaz told Adweek he wanted “to start experimenting” with “automated narratives,” including using bots for music and editing the closing credits of commercials.
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From algorithms to advertising: 7 steps to introducing AI to marketing

7 Steps to Introducing AI to Marketing  @DerinCag #AI #DigitalMarketing #cmo

  • The coming wave of AI in marketing will be defined by the automation of complex, multi-step processes — not just one-off aspects of a larger campaign.
  • Creating artificial intelligence for “self-driving” marketing technology is not so different from creating AI for a self-driving car.
  • Often, things that seem trivial — like determining which image and headline combo work best for Facebook, how much budget to spend where, or picking keywords for a search campaign — are critical parts of a larger process.
  • A machine, on the other hand, needs to be told (or programmed) with this knowledge in order to be able to judge images and text, determine where they should appear along the journey, and not have to rely on humans to make these decisions for it.
  • These built-in rules ensure that the AI doesn’t make decisions that are so out of sync with what a human would do in a given situation that the technology is at cross-purposes with the people or organization it’s serving.

Contributor Tomer Naveh provides a simplified look at how artificial intelligence (AI) is applied to automate digital marketing programs from start to finish.
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Listen To A Song Written By Artificial Intelligence, Inspired By The Beatles

Listen to a song written by artificial intelligence, inspired by The Beatles:

  • Sony CSL Research Laboratory is releasing an album next year of songs written by Artificial intelligence, and the first hit track may be this uncanny number programmed in the style of The Beatles (in all honesty it sounds a little more like The Beach Boys to me, at least through the intro).
  • French composer Benoît Carré arranged and produced the harmonies for the songs.
  • Using Sony’s Flowmachines system, the team selected a Beatles style and, well, here it is:

Sony CSL Research Laboratory is releasing an album next year of songs written by Artificial intelligence, and the first hit track may be this uncanny number programmed in the style of The Beatles.
Continue reading “Listen To A Song Written By Artificial Intelligence, Inspired By The Beatles”

4 challenges Artificial Intelligence must address

4 challenges Artificial Intelligence must address

  • Huge leaps in AI have accelerated this process dramatically and propagated it to other domains previously imagined to remain indefinitely in the monopoly of human intelligence

    From driving trucks to writing news and performing accounting tasks, AI algorithms are threatening middle class jobs like never before.

  • It’s also true that the AI revolution will create plenty of new data science, machine learning, engineering and IT job positions to develop and maintain the systems and software that will be running those AI algorithms.
  • Teaching new tech skills to people who are losing or might lose their jobs to AI in the future can complement the efforts.
  • Machine Learning, the popular branch of AI that is behind face recognition algorithms, product suggestions, advertising engines, and much more, depends on data to train and hone its algorithms.
  • Unless companies developing and using AI technology regulate their information collection and sharing practices and take necessary steps to anonymize and protect user data, they’ll end up causing harm than good to users.


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Understanding the differences between AI, machine learning, and deep learning

Understanding the differences between #AI, #machinelearning, and #deeplearning ▷

  • IBM’s Deep Blue, which beat chess grand master Garry Kasparov at the game in 1996, or Google DeepMind’s AlphaGo, which in 2016 beat Lee Sedol at Go, are examples of narrow AI—AI that is skilled at one specific task.
  • DeepMind, on the other hand, is: It beat the world champion in Go by training itself on a large data set of expert moves.SEE: Machine learning: The smart person’s guide (TechRepublic)Is your business interested in integrating machine learning into its strategy?
  • Amazon, Baidu, Google, IBM, Microsoft and others offer machine learning platforms that businesses can use.Deep Learning Deep learning is a subset of ML.
  • It would take a very massive data set of images for it to understand the very minor details that distinguish a cat from, say, a cheetah or a panther or a fox.As mentioned above, in March 2016, a major AI victory was achieved when DeepMind’s AlphaGo program beat world champion Lee Sedol in 4 out of 5 games of Go using deep learning.
  • Sundown AI, for instance, has mastered automated customer interactions using a combination of ML and policy graph algorithms—not deep learning.Also see… The 6 most exciting AI advances of 2016 (TechRepublic)3 major AI trends to watch in 2017 (TechRepublic)Microsoft’s new breakthrough: AI that’s as good as humans at listening… on the phone (ZDNet)Five ways your company can get started implementing AI and ML (ZDNet)Research: 63% say business will benefit from AI (Tech Pro Research)How Google’s DeepMind beat the game of Go, which is even more complex than chess (TechRepublic)Smart machines are about to run the world: Here’s how to prepare (TechRepublic)Why AI could destroy more jobs than it creates, and how to save them (TechRepublic)7 trends for artificial intelligence in 2016: ‘Like 2015 on steroids’ (TechRepublic)

Artificial intelligence, machine learning, and deep learning have become integral for many businesses. But, the terms are often used interchangeably. Here’s how to tell them apart.
Continue reading “Understanding the differences between AI, machine learning, and deep learning”

Understanding the differences between AI, machine learning, and deep learning

Understanding the differences between AI, machine learning, and deep learning

  • IBM’s Deep Blue, which beat chess grand master Garry Kasparov at the game in 1996, or Google DeepMind’s AlphaGo, which in 2016 beat Lee Sedol at Go, are examples of narrow AI—AI that is skilled at one specific task.
  • DeepMind, on the other hand, is: It beat the world champion in Go by training itself on a large data set of expert moves.SEE: Machine learning: The smart person’s guide (TechRepublic)Is your business interested in integrating machine learning into its strategy?
  • Amazon, Baidu, Google, IBM, Microsoft and others offer machine learning platforms that businesses can use.Deep Learning Deep learning is a subset of ML.
  • It would take a very massive data set of images for it to understand the very minor details that distinguish a cat from, say, a cheetah or a panther or a fox.As mentioned above, in March 2016, a major AI victory was achieved when DeepMind’s AlphaGo program beat world champion Lee Sedol in 4 out of 5 games of Go using deep learning.
  • Sundown AI, for instance, has mastered automated customer interactions using a combination of ML and policy graph algorithms—not deep learning.Also see… The 6 most exciting AI advances of 2016 (TechRepublic)3 major AI trends to watch in 2017 (TechRepublic)Microsoft’s new breakthrough: AI that’s as good as humans at listening… on the phone (ZDNet)Five ways your company can get started implementing AI and ML (ZDNet)Research: 63% say business will benefit from AI (Tech Pro Research)How Google’s DeepMind beat the game of Go, which is even more complex than chess (TechRepublic)Smart machines are about to run the world: Here’s how to prepare (TechRepublic)Why AI could destroy more jobs than it creates, and how to save them (TechRepublic)7 trends for artificial intelligence in 2016: ‘Like 2015 on steroids’ (TechRepublic)

Artificial intelligence, machine learning, and deep learning have become integral for many businesses. But, the terms are often used interchangeably. Here’s how to tell them apart.
Continue reading “Understanding the differences between AI, machine learning, and deep learning”