Why the Benefits of Artificial Intelligence Outweigh the Risks

Why #Benefits of Artificial Intelligence Outweigh the #Risks  #AI #Innovation #startup #tech

  • The argument against artificial intelligence (AI) is driven by fear.
  • The most realistic fear today is that AI will take people’s jobs.
  • Undoubtedly technology is taking people’s jobs in droves.
  • Google is a great example of machine learning that many people use every day and it truly does make life easier.
  • While the fear of job loss is understandable, there is another point to make: because of artificial intelligence many people are currently doing jobs that weren’t available even just a few years back.

According to Stephen Hawkings we do have reason to beware of the consequences of artificial intelligence (AI) including the possibility of the end of the human race.
Continue reading “Why the Benefits of Artificial Intelligence Outweigh the Risks”

IBM Cloud Industry expertise matters

#AI 
#Blockchain 
#IoT 
#ibminterconnect 2017. Register today!

  • “Cognitive and cloud are not separate phenomena.
  • Advance your world at InterConnect.
  • View the curriculum

    Address your industry challenges and move ahead of your peers using the world’s first cloud-based data + your data to create cognitive insights and actions.

  • View the roles

    Join more than 20,000 thought leaders and industry experts and explore a reimagined workforce fueled by cloud technologies.

  • View the industries

    Get hands-on experience with more than 200+ exhibitors and Business Partners.

Tap into the most advanced cloud technology in the market today at IBM InterConnect 2017, March 19–23 in Las Vegas.
Continue reading “IBM Cloud Industry expertise matters”

Book: Machine Learning Algorithms From Scratch

Book: Machine Learning Algorithms From Scratch | #BigData #MachineLearning #RT

  • From First Principles With Pure Python and

    Use them on Real-World Datasets

    You must understand algorithms to get good at machine learning.

  • In this mega Ebook written in the friendly Machine Learning Mastery style that you’re used to, finally cut through the math and learn exactly how machine learning algorithms work.
  • I’ve written books on algorithms, won and ranked in the top 10% in machine learning competitions, consulted for startups and spent a long time working on systems for forecasting tropical cyclones.
  • (yes I have written tons of code that runs operationally)

    I get a lot of satisfaction helping developers get started and get really good at machine learning.

  • I teach an unconventional top-down and results-first approach to machine learning where we start by working through tutorials and problems, then later wade into theory as we need it.

Discover How to Code Machine Algorithms
From First Principles With Pure Python and
Use them on Real-World Datasets

$37 USD
You must understand algorithms t…
Continue reading “Book: Machine Learning Algorithms From Scratch”

Deep Learning Research Review: Natural Language Processing

#ICYMI #DeepLearning Research Review: Natural Language Processing  #NLP

  • Since deep learning loves math, we’re going to represent each word as a d-dimensional vector.
  • Extracting the rows from this matrix can give us a simple initialization of our word vectors.
  • The above cost function is basically saying that we’re going to add the log probabilities of ‘I’ and ‘love’ as well as ‘NLP’ and ‘love’ (where ‘love’ is the center word in both cases).
  • One Sentence Summary: Word2Vec seeks to find vector representations of different words by maximizing the log probability of context words given a center word and modifying the vectors through SGD.
  • Bonus: Another cool word vector initialization method: GloVe (Combines the ideas of coocurence matrices with Word2Vec)


This edition of Deep Learning Research Review explains recent research papers in Natural Language Processing (NLP). If you don’t have the time to read the top papers yourself, or need an overview of NLP with Deep Learning, this post is for you.

Continue reading “Deep Learning Research Review: Natural Language Processing”

Britain Banks on Robots, Artificial Intelligence to Boost Growth

Britain is banking on robots and artificial intelligence to boost growth

  • Britain Banks on Robots, Artificial Intelligence to Boost Growth

    by

    February 25, 2017, 7:01 PM EST

    Britain is betting that the rise of the machines will boost the economy as the country exits the European Union.As part of its strategy to champion specific industries, the U.K. government said in a statement on Sunday that it would invest 17.3 million pounds ($21.6 million) in university research on robotics and artificial intelligence.

  • The government cited an estimate from consultancy Accenture that AI could add 654 billion pounds to the U.K. economy by 2035.
  • “We are already pioneers in today’s artificial intelligence revolution and the digital strategy will build on our strengths to make sure U.K.-based scientists, researchers and entrepreneurs continue to be at the forefront,” Culture Secretary Karen Bradley said in the statement, which referenced AI’s contribution to smartphone voice and touch recognition technologies.
  • The U.K.’s digital strategy proposal, set to be unveiled on Wednesday, also includes a review of AI to determine how the government and industry can provide further support.
  • “Investment in robotics and artificial intelligence will help make our economy more competitive, build on our world-leading reputation in these cutting-edge sectors and help us create new products, develop more innovative services and establish better ways of doing business,” Business Secretary Greg Clark said in the statement.

Britain is betting that the rise of the machines will boost the economy as the country exits the European Union.
Continue reading “Britain Banks on Robots, Artificial Intelligence to Boost Growth”

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”

Wearable adoption more than doubled in past two years

Wearable adoption more than doubled in past two years | #MachineLearning #Apple #RT

  • The adoption of wearables has skyrocketed, rising from 21 percent of the U.S. population in 2014 to 49 percent in 2016, according to a report by consulting firm PwC.
  • And parents are significantly more likely to own not just one, but multiple wearable devices, the report said.
  • PwC created the report to better understand the wearable tech landscape and identify trends and opportunities.
  • The wearables include fitness trackers/bands, smart glasses, smart watches, smart clothing, and other wearable devices.
  • Both men and women like their wearables, however, men are more likely to own smart watches and smart glasses than their female counterparts, PwC said.

The adoption of wearables has skyrocketed, rising from 21 percent of the U.S. population in 2014 to 49 percent in 2016, according to a report by consulting firm PwC.
Continue reading “Wearable adoption more than doubled in past two years”