Stellar explanation from Harvard business school...love it

How to Spot a Machine Learning Opportunity, Even If You Aren't a Data Scientist https://hbr.org/2017/10/how-to-spot-a-machine-learning-opportunity-even-if-you-arent-a-data-scientist Shared from my Google feed

Artificial Intelligence & Machine learning

If any one ask to a sincere boy for a glass of water ....surely that boy will keep in  mind several points such as ;
1: whether the water is fit for drinking or not
2: water is odourless and colourless or not  ..........

so this is the small example that shows human have its own ability to think while doing a task and this is called intelligency of human. A human knows very well that what is good for his health and what not.   but what is in the case of computer or we may say a digital machine......↠↠↠surely a computer totally works on the instructions that user give without an instruction computer can'nt perform a single task 

I am not as intelligent as u are

think about the case when a computer start thinking by itself...........

we can call this an example ARTIFICIAL INTELLIGENCE.

A branch of Computer Science named Artificial Intelligence pursues creating the computers or machines as intelligent as human beings.

According to the father of Artificial Intelligence, John McCarthy, it is “The science and engineering of making intelligent machines, especially intelligent computer programs”.

at present time all the tech giants such as Google ( google lens) , Facebook (mission jarvis) spending their lot of times and money on Machine learning and  Artificial intelligence

Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.

AI is accomplished by studying how human brain thinks, and how humans learn, decide, and work while trying to solve a problem, and then using the outcomes of this study as a basis of developing intelligent software and systems.

Idea behind AI ....

While dealing with the power of the computer systems, the curiosity of human, lead him to wonder, “Can a machine think and behave like humans do?”

Targets of AI ;

1: TO CREATE A GENIUS MACHINE

2: TO IMPLEMENT THE HUMAN INTELLIGENCY IN THE TECHNOLOGY SO THAT THE AREA OF TECHNOLOGY COVER INCREASEs  ( in the field of DNA observation, in observing various deseases such as different types of cancers, in space researches , in various mineral and petroleum explorations in land and sea and many more)

Content of AI ;

Artificial intelligence is a science and technology based on disciplines such as Computer Science, Biology, Psychology, Linguistics, Mathematics, and Engineering. A major thrust of AI is in the development of computer functions associated with human intelligence, such as reasoning, learning, and problem solving.

Is AI is safer to us ......?

In the long term, an important question is what will happen if the quest for strong AI succeeds and an AI system becomes better than humans at all cognitive tasks. As pointed out by I.J. Good in 1965, designing smarter AI systems is itself a cognitive task. Such a system could potentially undergo recursive self-improvement, triggering an intelligence explosion leaving human intellect far behind. By inventing revolutionary new technologies, such a superintelligence might help us eradicate war, disease, and poverty, and so the creation of strong AI might be the biggest event in human history. Some experts have expressed concern, though, that it might also be the last, unless we learn to align the goals of the AI with ours before it becomes superintelligent.

HOW CAN AI BE DANGEROUS?

Most researchers agree that  AI is unlikely to exhibit human emotions like love or hate, and that there is no reason to expect AI to become intentionally benevolent or malevolent. Instead, when considering how AI might become a risk, experts think two scenarios most likely:

1. The AI is programmed to do something devastating: Autonomous weapons are artificial intelligence systems that are programmed to kill. In the hands of the wrong person, these weapons could easily cause mass casualties. Moreover, an AI arms race could inadvertently lead to an AI war that also results in mass casualties. To avoid being thwarted by the enemy, these weapons would be designed to be extremely difficult to simply “turn off,” so humans could plausibly lose control of such a situation. This risk is one that’s present even with narrow AI, but grows as levels of AI intelligence and autonomy increase.
2. The AI is programmed to do something beneficial, but it develops a destructive method for achieving its goal: This can happen whenever we fail to fully align the AI’s goals with ours, which is strikingly difficult. If you ask an obedient intelligent car to take you to the airport as fast as possible, it might get you there chased by helicopters and covered in vomit, doing not what you wanted but literally what you asked for. If a superintelligent system is tasked with a ambitious geoengineering project, it might wreak havoc with our ecosystem as a side effect, and view human attempts to stop it as a threat to be met.

   

   If human can evolve then why not AI....?

As these examples shows, the concern about advanced AI isn’t malevolence but competence. An AI will be extremely good at accomplishing its goals, and if those goals aren’t aligned with ours, we have a problem. You’re probably not an evil ant-hater who steps on ants out of malice, but if you’re in charge of a hydroelectric green energy project and there’s an anthill in the region to be flooded, too bad for the ants. A key goal of AI safety research is to never place humanity in the position of those ants.

we will discuss AI in depth in my next blog......

Machine Learning;

Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that machines should be able to learn and adapt through experience.

IMPORTANCE OF MACHINE LEARNING;

Resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. Things like growing volumes and varieties of available data, computational processing that is cheaper and more powerful, and affordable data storage.

All of these things mean it's possible to quickly and automatically produce models that can analyze bigger, more complex data and deliver faster, more accurate results – even on a very large scale. And by building precise models, an organization has a better chance of identifying profitable opportunities – or avoiding unknown risks.

Difference b/w AI and Machine learning........................

Artificial Intelligence (AI) and Machine Learning (ML) are two very hot tech topic right now, and often seem to be used interchangeably.

They are not  the same thing, but the perception that they can sometimes lead to some confusion. So I thought it would be worth writing a piece to explain the difference.

Both terms crop up very frequently when the topic is Big Data, analytics, and the broader waves of technological change which are sweeping through our world.

THE GIST OF THE DOUBT IS.......

Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart”.

And,

Machine Learning is a current application of AI based around the idea that we should really just be able to give machines access to data and let them learn for themselves.

 GUY'S HOPE U LIKE IT.....Write ur views and must reply ..... and suggest me too for my future blog ....

there is need of strong and healthy discussion b/w us as its truely said that " every great movements consisty of three stages  1 ridicule ...2 discussion ....3 adoption..... so lets start a movement