OKAY, TELL ME THE DIFFERENCE

March 21, 2018


Portions of this post are taken from the January 2018 article written by John Lewis of “Vision Systems”.

I feel there is considerable confusion between Artificial Intelligence (AI), Machine Learning and Deep Learning.  Seemingly, we use these terms and phrases interchangeably and they certainly have different meanings.  Natural Learning is the intelligence displayed by humans and certain animals. Why don’t we do the numbers:

AI:

Artificial Intelligence refers to machines mimicking human cognitive functions such as problem solving or learning.  When a machine understands human speech or can compete with humans in a game of chess, AI applies.  There are several surprising opinions about AI as follows:

  • Sixty-one percent (61%) of people see artificial intelligence making the world a better place
  • Fifty-seven percent (57%) would prefer an AI doctor perform an eye exam
  • Fifty-five percent (55%) would trust an autonomous car. (I’m really not there as yet.)

The term artificial intelligence was coined in 1956, but AI has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage.

Early AI research in the 1950s explored topics like problem solving and symbolic methods. In the 1960s, the US Department of Defense took interest in this type of work and began training computers to mimic basic human reasoning. For example, the Defense Advanced Research Projects Agency (DARPA) completed street mapping projects in the 1970s. And DARPA produced intelligent personal assistants in 2003, long before Siri, Alexa or Cortana were household names. This early work paved the way for the automation and formal reasoning that we see in computers today, including decision support systems and smart search systems that can be designed to complement and augment human abilities.

While Hollywood movies and science fiction novels depict AI as human-like robots that take over the world, the current evolution of AI technologies isn’t that scary – or quite that smart. Instead, AI has evolved to provide many specific benefits in every industry.

MACHINE LEARNING:

Machine Learning is the current state-of-the-art application of AI and largely responsible for its recent rapid growth. Based upon the idea of giving machines access to data so that they can learn for themselves, machine learning has been enabled by the internet, and the associated rise in digital information being generated, stored and made available for analysis.

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level understanding. Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.

DEEP LEARNING:

Deep Learning concentrates on a subset of machine-learning techniques, with the term “deep” generally referring to the number of hidden layers in the deep neural network.  While conventional neural network may contain a few hidden layers, a deep network may have tens or hundreds of layers.  In deep learning, a computer model learns to perform classification tasks directly from text, sound or image data. In the case of images, deep learning requires substantial computing power and involves feeding large amounts of labeled data through a multi-layer neural network architecture to create a model that can classify the objects contained within the image.

CONCLUSIONS:

Brave new world we are living in.  Someone said that AI is definitely the future of computing power and eventually robotic systems that could possibly replace humans.  I just hope the programmers adhere to Dr. Isaac Asimov’s three laws:

 

  • The First Law of Robotics: A robot may not injure a human being or, through inaction, allow a human being to come to harm.

 

  • The Second Law of Robotics: A robot must obey the orders given to it by human beings, except where such orders would conflict with the First Law.

 

  • The Third Law of Robotics: A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws.

With those words, science-fiction author Isaac Asimov changed how the world saw robots. Where they had largely been Frankenstein-esque, metal monsters in the pulp magazines, Asimov saw the potential for robotics as more domestic: as a labor-saving device; the ultimate worker. In doing so, he continued a literary tradition of speculative tales: What happens when humanity remakes itself in its image?

As always, I welcome your comments.

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