Intro to Artificial Intelligence(AI)

Original article was published on Artificial Intelligence on Medium

source: Google images

“Predicting future isn’t magic, it’s Artificial Intelligence” -Dave Waters

Before diving into the AI, we need to know the term intelligence

What is intelligence?

We, humans have innate intelligence, that governs every activity in the human body. This intelligence is what causes an oak tree to grow out of a little seed and an elephant to form from a single-celled organism, it’s really an amazing art of nature.

Origin of AI

Sources tell us intelligent robots and artificial beings first appeared in the ancient Greek myths of Antiquity. Aristotle’s development of the syllogism and its use of deductive reasoning was a key moment in mankind’s quest to understand its own intelligence.

Can machines think? — Alan Turing, 1950

But Alan Turing’s paper “Computing Machinery and Intelligence” (1950), and it’s subsequent Turing Test, established the fundamental goal and vision of artificial intelligence and later after 1956 researchers made a shape to it.

What is Artificial Intelligence?

Initially it was defined as building machines that are intelligent but unable to answer what’s actually the artificial intelligence.

Artificial Intelligence is the intelligence exhibited by machines and the capability of a machine to imitate human behaviour as like how human can take decisions based on surroundings same as machine can make its own decisions based on situations. It can be anything that make machines to act more intelligently.

AI is the new electricity. It will transform every industry and create huge economic value — Andrew Ng

AI is a multi-disciplinary field

AI modeled after human brain. In fact, AI is a multi-disciplinary field it mean it is not limited to computer science but also the combination of electrical engineering, mathematics, statistics, Psychology, linguistics and philosophy.

Okay we got to know about AI

How to AI learn?

Is it possible to teach machines by taking them to school, giving home works and putting exams with cut-off marks? here’s big no, non-conventional to the way humans learn.

Main quality in the artificial intelligence is learn and applying i.e learning from external experiences altering its perceptions based on them.

teaching machines to learn

According to IBM, AI learns by creating machine learning models based on provided inputs and desired outputs.

Data has a better idea, we need to know how to feed and train machines with the help of data sets with a process called as modelling. Better ways to train machines possibly explained with the help of machine learning and deep learning.

Myths of Artificial Intelligence(AI)

source: Towards datascience
  1. All jobs will be replaced by AI

Reality is it more create more jobs for humans, according to analysis by 2030, AI value creation is about $13 trillion in all sectors.

World Economic Forum: Automation will displace 75 million jobs but generate 133 million new ones worldwide by 2022

2. Only low-skilled and manual workers will be replaced by AI

It’s a big myth. AI-equipped robots and machinery are carrying out work generally reserved for the most highly trained and professional researchers. True, a lot of their focus has been on reducing the “drudgery” of day-to-day aspects of the work.

For example: in the legal field, AI is used to scan thousands of documents at lightning speed, drawing out the points which may be relevant in an ongoing case. In medicine, machine learning algorithms assess images such as scans and x-rays, looking for early warning signs of disease, which they are proving highly competent at spotting. human touch” procedures. These aspects of the job are less likely to be automated.

3. Companies don’t need an AI strategy

Reality is sources tell us over the next decade, there is no organization, industry, or business segment that is going to completely avoid being touched by AI. It is a risky proposition not to have an AI plan because the competition certainly will and they will be able to respond to market changes much quicker. Hard need of AI in business like A/B testing.

4. Modeling determines outcome

Surely can’t be certain of that, All AI initiatives begin as test projects. As we may get excellent results during the testing phase, but find that your model is far less accurate when we deploy it into production. That’s because AI and machine learning models must be trained on data, and that training data must be representative of the real data, or results will suffer.

5. AI eliminates humans in Earth

We mayn’t sure about it at now. As AI is in research stage not in able to its complete application. What AI we see today is basic only also AI is as smarter as we train them. It work based on trained data only. More the data more accuracy but never get full accuracy.

Is AI dangerous destroy humankind?

source: RNZ

As we know everything has its own pros and cons. Here also applies same. Great scientists and researchers foresee the adverse effects of full development of artificial intelligence.

The development of full Artificial intelligence could spell the end of human race — Stephen Hawking

As we can see a humanoid robot like Sophia robot, is a mediocre application of AI but beyond that intelligence will may end human race.

We need to be super careful with AI, potentially more dangerous than nukes — Elon Musk

Humans should be worried about the threat posed by artificial intelligence as said before and be cautious about the development stages of AI, failed to do so will make humans to pay lives.

Kudos, you did it. I feel you you have learned at least a new line of information about Artificial intelligence than before.

Thanks for reading.