An Interview With David Kenny – The Innovator news

  • — D.K.:We are at the point in AI that we were with the Internet in 1993 and mobile around 2003.
  • So I would say, view AI as something in the fabric of your company like electricity — like data flowing through your company in fundamental ways.Is it a threat or an opportunity?
  • — D.K.: The digital and mobile disruptions largely favor distribution, so most of the real value is held by a handful of companies who have consolidated distribution.
  • To take advantage of AI we really encourage companies to maintain control of their data — their intellectual property — because the value is in using it to train the AI.Don’t feed it to (an outside) platform that will serve as a distribution chokehold.
  • Companies need to establish their data and knowledge strategy first — extending their own knowledge and not just turning it over to someone else.

David Kenny, IBM Watson’s Chief and a scheduled keynote speaker at Viva Technology recently spoke to The Innovator about what executives should do to prepare for AI. — D.K.: When you can predict…
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Spotlight

5 essential #TEDtalks on the #FutureOfWork  
@KM_Spotlight #AI #Robot #KMspotlight

  • As inventors rush to create mind-blowing bits of kit that have the power to transform our daily lives forever, is there anyone out there pausing to think about the real impacts of technology on our lives, our psyches and our society?
  • In the following TED talks, you’ll be able to navigate all the possibilities, and equip yourself with wisdom that will carry you through the changes.
  • Apart from a paycheck, there are intangible values that, Barry Schwartz suggests, our current way of thinking about work simply ignores.
  • Lisa Gansky, author of “The Mesh,” talks about a future of business that’s about sharing all kinds of stuff, either via smart and tech-enabled rental or, more boldly, peer-to-peer.
  • In this talk about the future of work, economist David Autor addresses the question of why there are still so many jobs and comes up with a surprising, hopeful answer.

5 TED talks for anyone interested in the changing work landscape
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What Is The Difference Between Artificial Intelligence And Machine Learning?

This is the difference between artificial intelligence and machine learning:

  • Believe in what you do and think hard about what kind of changes you want your work to make.
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There is little doubt that Machine Learning (ML) and Artificial Intelligence (AI) are transformative technologies in most areas of our lives. While the two concepts are often used interchangeably there are important ways in which they are different. Let’s explore the key differences between them.
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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?”

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?