HomeTech and GadgetsArtificial IntelligenceAutomated Machine and Deep Learning Are Making AI a Human Necessity

Automated Machine and Deep Learning Are Making AI a Human Necessity

January 29, 2019 – Today’s guest post is written by Danish Wadhwa, a specialist in digital marketing, cloud computing, and web design. In this contribution, he describes the necessity for all of us who are today users of personal digital assistants from smartphones to home devices like Alexa, to take courses on and about artificial intelligence (AI) so that we can master its use to our advantage in the 21st century. As always your comments are welcomed.


The computer scientist and one of the world’s AI experts, Andrew Ng, recently announced the need to train not only experts but also the masses about machine intelligence. It is his aim to educate people about AI and other sophisticated technologies and feels everyone needs to know about it. That’s because human beings in the near future may not dare to live without AI.

Statistics and trends point to a world where as many as 1.8 billion of us will be using personal digital AI assistants by 2021. With such a level of usage, it makes sense then that even the non-technical person should consider enrolling in some kind of AI course whether it be one for professionals like the Artificial Intelligence Course being offered at Simplilearn or some other venue. There are artificial intelligence courses for anyone today, and they are designed to equip a person with enough information to tackle the changing nature of AI and its profound implications for both the personal and the world of work. 

What Constitutes AI?

It is comprised of many different technologies with one consistent purpose, to make machines capable to think and learn like us. The words most often associated with AI are machine learning, and deep learning.

Machine learning algorithms are pieces of software that enable a computer or robot to learn from past experiences and apply the knowledge to future activities. Deep learning algorithms expose a computer or robot to enormous amounts of data to then recognize commonalities in new data presented to it. Deep learning employs neural networks, computers designed to mimic the structure of neurons in the human brain.

The image that follows presents how traditional machine learning works. It is a time-consuming and costly investment for a small business to implement. That’s why shortcuts are being sought. One of these is AutoML.

Source: DataRobot.

 

AutoML

Businesses and data scientists today have discovered that a shortcut like AutoML which compares best practices and results from numerous machine learning models, can help solve business problems and do it at an affordable cost. Both Google and Microsoft allow organizations to make use of their own AutoML offerings. With Microsoft it is called CustomVisionAI. The tool allows a business to get started for $29 USD per month in developing what it calls robust convolutional neural networks (CNN). Google’s try-for-free equivalent is Cloud AutoML, a suite of machine learning products using the company’s state-of-the-art transfer learning, and neural architecture search technology.

These Google tools include:

Will AI Alter the Job Market?

With the technology giants engaged in a battle for AI supremacy in the market, we should see a growth in new jobs from this industry segment. The World Economic Forum in its 2018 report predicts that AI will add 58 million net new jobs by 2022. For those who fear job losses from AI’s emergence into mainstream business, the impact will largely be for data entry work.

Companies like IBM, Google and Microsoft in North America, and Alibaba, and Tencent in China want to make AutoML an affordable option for businesses of any size. That should make for all kinds of new job opportunities and should have those seeking employment taking all kinds of emerging AI courses.

 

lenrosen4
lenrosen4https://www.21stcentech.com
Len Rosen lives in Oakville, Ontario, Canada. He is a former management consultant who worked with high-tech and telecommunications companies. In retirement, he has returned to a childhood passion to explore advances in science and technology. More...

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