(AI) accentuates the creation of technology that works and reacts as intelligently as humans. Artificial intelligence uses machine learning to work like human intelligence. While some people embrace this new development gladly with open arms, others have fearful and even pessimistic views about it.
The latter reaction is absolutely normal as it confirms that different individuals have variant ways they perceive and approach situations. There’s a lot of fear surrounding artificial intelligence these days.
Over the years, we have been fed with several doomsday events involving scenarios where our own creations have ruined us like the popular Terminator movie series where Skynet, an evil AI takes over the world; the C-3P0 and R2-D2 of the Stars Wars working against the Empire. This, however, remains science fiction.
The fact that various AI-related technologies are already in widespread use is already known and accepted. Learn more We have become so comfortable with them because not only have they become a source of entertainment, they have provided us unlimited utilities that the majority of the population are now so dependent on.
The positive impact of technology gets deeper as they get more intelligent with every passing year. We are also assured that this is just the beginning; there is more to come. So what then could possibly be wrong with AI?
The accelerating pace of progress in AI development is currently generating a frenzied mix of anxiety and excitement. Debates on the threats of forms of AI by public figures have received extensive coverage.
The billionaire CEO of Tesla and SpaceX, Elon Musk, has expressed deep worries about the potential of artificial intelligence(AI).
“I have exposure to the most cutting-edge AI, and I think people should be really concerned about it. AI is a fundamental risk to the existence of human civilization in a way that car accidents, airplane crashes, faulty drugs, or bad food were not — they were harmful to a set of individuals within society, of course, but they were not harmful to society as a whole.”, Musk said.
He believes AI poses a greater threat to mankind than nuclear weapons.
Although statements have received lots of backlash from AI proponents, there are a few more people that have this view. One of them is a prominent British scientist, Prof.
He said that the primitive forms of artificial intelligence developed so far have already proved very useful, but he fears the consequences of creating something that can match or surpass humans. He also said that the development of full artificial intelligence could spell the end of the human race.
Another very prominent person, Microsoft co-founder Bill Gates says that in the near future robots doing more work will be positive, but he does express concern about the potential of artificial intelligence in the long run.
“I am in the camp that is concerned about super intelligence,” Gates said.
The advocates of artificial intelligence, however, are having none of the “negativity”.
The CEO of Facebook, Mark Zuckerberg said, “I have pretty strong opinions on this. I am optimistic. I think you can build things and the world gets better.
Artificial intelligence machine learning
But with AI especially, I am really optimistic”.
He went on to say that he thinks people who are naysayers and try to drum up these doomsday scenarios are really pessimistic and in some ways, he thinks, pretty irresponsible.
“In the next five to 10 years, AI is going to deliver so many improvements in the quality of our lives,” Zuckerberg says.
Chinese e-commerce billionaire and Alibaba Co-founder, Jack Ma, has invested greatly in artificial intelligence as his company expands into new sectors beyond its e-commerce business.
He says that artificial intelligence (AI) is not a threat to humans.
“There is no competition between computers and humans as the latter was responsible for the former. Don’t worry about the machines. A computer is a computer. A computer is just a toy.
I think because of artificial intelligence, people will have more time enjoying being human beings,” Ma said.
The controversial nature of artificial intelligence has given rise to the uncertainty we feel about it.
There are several claims about artificial intelligence ranging from its potential to shake the foundation of democracy to the possibility of creating a rogue AI overlord. Fears and speculations have come up about the potential impact of artificial intelligence and automation on our society.
The first concern is the influence AI will have on our workforce.
The CEO of Tesla and SpaceX, Elon Musk is certain that robots will be able to do jobs better than humans. “There certainly will be job disruption. Because what’s going to happen is robots will be able to do everything better than us. … I mean all of us,” says Musk.
Musk was talking about the mass unemployment that would hit society and affect the young and old alike.
Microsoft co-founder Bill Gates is more optimistic as he looks at the prospects of robots taking over human jobs. “I think robots taking over jobs can be a good thing. The macro picture that it enables is an opportunity,” says Gates.
Kai-Fu Lee, a longtime expert on AI believes that job-displacing artificial intelligence will force people to look beyond work in order to define who they are.
“We were all brainwashed by the Industrial Revolution-era value that our work equals the meaning of our life.
Perhaps AI is a wake-up call, for us to realize that there’s something else”, Lee said.
The second concern is that artificial intelligence will surpass human intelligence. It cannot be denied that the pace of development and progress with machine learning is outstanding.
Driver-less cars, chess computers, and bulldozers can and have surpassed human capabilities.
Gary Marcus, a cognitive science professor expresses his fears, “Once computers can effectively reprogram themselves, and successively improve themselves, leading to a so-called technological singularity or intelligence explosion, the risks of machines outwitting humans in battles for resources and self-preservation cannot simply be dismissed”.
“You can see robots that can learn to walk from nothing within hours, way faster than any biological being,” the billionaire CEO of Tesla, Elon Musk says.
This technological advancement being of a positive or negative effect on human society solely depends on the truth of the next concern.
That concern is whether or not AI experts will be able to develop a conscious AI. There are people who believe robots can be programmed to have desires or emotions.
Tesla CEO, Elon Musk also hints at this in a statement:
“AI would become weary of trying to communicate with humans, as we would be much slower thinkers in comparison.
Human speech to a computer will sound like very slow tonal wheezing, kind of like whale sounds. So, the computer will just get impatient if nothing else.
It’ll be like talking to a tree – that’s humans”.
There’s however, a school of thought that believes that robots can NEVER have emotions. There are trillions of neural connections utilized to provide our motivational processes.
They believe that the neural networks that create the process of symbolism, memory, emotion, and then action are too vast. These are capabilities only for the human brain.
Jaron Lanie, a virtual reality pioneer, states:
“We’re still pretending that we’re inventing a brain when all we’ve come up with is a giant mash-up of real brains.
We don’t yet understand how brains work, so we can’t build one”.
There’s no doubt that AI experts can develop a very intelligent robot. But can intelligence really be measured? Yes, they may be more accurate and faster but do they possess the same cognitive skills as the human brain. It’s a possibility for an AI may be programmed to do something beneficial, but it develops a destructive method for achieving its goal.
This is also feared by Nick Bilton, a former New York Times tech columnist as he states;
“Imagine how a medical robot, originally programmed to rid cancer, could conclude that the best way to obliterate cancer is to exterminate humans who are genetically prone to the disease”
This is funny but possible speculation.
This automatically brings up the most important question of the day. Will AI bring about the destruction of the Human Race??
People in the pessimistic camp of these discussions are more likely to say an instant yes.
Prof Stephen Hawking said that that the development of full artificial intelligence could spell the end of the human race. It would take off on its own, and re-design itself at an ever-increasing rate.
Humans, who are limited by slow biological evolution, couldn’t compete and would be superseded.
The Christian religious community also has views on this. The Christian Holy Book (The Bible) gives statements about how the world will likely end in the last section (The Book of Revelation). There is not hinting of a technological dominance over mankind as the way the human race will end.
This is faith for Christians.
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Optimism towards artificial intelligence will do immense good here as we can only hope for the best.
“Machine shouldn’t replace humans at what they do best, it must rather focus on making machines do what humans can’t. This approach would help in trusting machines as a “human partner,” than an opponent.” (Alibaba Co-founder Jack Ma)
“Whenever I hear people saying AI is going to hurt people in the future, I think, yeah, technology can generally always be used for good and bad, and you need to be careful about how you build it, and you need to be careful about what you build and how it’s going to be used. AI has had improvements in basic research to improve systems across so many different fields — from diagnosing diseases to keep us healthy, to improving self-driving cars to keep us safe, and from showing you better content in News Feed to delivering you more relevant search results,”
(Facebook CEO Mark Zuckerberg) Artificial intelligence machine learning deep learning
“I think we need to make it immoral to have killer robots. We need to change the culture, and that includes changing laws and treaties. That can go a long way.” (Canadian Computer Scientist Yoshua Bengio)
Artificial intelligence machine learning
How Will Artificial Intelligence Affect Our Lives In The Next Ten Years?
The primary focus of this essay is the future of Artificial Intelligence (AI). In order to better understand how AI is likely to grow, I intend to first explore the history and the current state of AI. By showing how its role in our lives has changed and expanded so far, I will be better able to predict its future trends.
John McCarthy first coined the term artificial intelligence in 1956 at Dartmouth College. At this time electronic computers, the obvious platform for such technology was still less than thirty years old, the size of lecture halls, and had storage systems and processing systems that were too slow to do the concept justice. It wasn’t until the digital boom of the ’80s and 90’s that the hardware to build the systems began to gain ground on the ambitions of the AI theorists and the field really started to pick up.
EVER thought of How Artificial Intelligence WILL Affect Our Lives In The Next Ten Years?
If artificial intelligence can match the advances made last decade in the decade to come it is set to be as common a part of our daily lives as computers have in our lifetimes. Artificial intelligence has had many different descriptions put to it since its birth and the most important shift it’s made in its history so far is in how it has defined its aims. When AI was young its aims were limited to replicating the function of the human mind, as the research developed new intelligent things to replicate such as insects or genetic material became apparent.
The limitations of the field were also becoming clear and out of this AI as we understand it today emerged. The first AI systems followed a purely symbolic approach. Classic AI’s approach was to build intelligence on a set of symbols and rules for manipulating them. One of the main problems with such a system is that of symbol grounding.
If every bit of knowledge in a system is represented by a set of symbol and a particular set of symbols (“Dog” for example) has a definition made up of a set of symbols (“Canine mammal”) then the definition needs a definition (“mammal: a creature with four limbs, and a constant internal temperature”) and this definition needs a definition and so on. When does this symbolically represented knowledge get described in a manner that doesn’t need further definition to be complete? These symbols need to be defined outside of the symbolic world to avoid an eternal recursion of definitions.
The way the human mind does this is to link symbols with stimulation. For example, when we think dog we don’t think canine mammal, we remember what a dog looks like, smells like, feels like, etc. This is known as sensorimotor categorization. By allowing an AI system access to senses beyond a typed message it could ground the knowledge it has in sensory input in the same manner we do.
That’s not to say that classic AI was a completely flawed strategy as it turned out to be successful for a lot of its applications. Chess-playing algorithms can beat grandmasters, expert systems can diagnose diseases with greater accuracy than doctors in controlled situations and guidance systems can fly planes better than pilots.
This model of AI developed in a time when the understanding of the brain wasn’t as complete as it is today. Early AI theorists believed that the classic AI approach could achieve the goals set out in AI because computational theory supported it. Computation is largely based on symbol manipulation, and according to the Church/Turing thesis computation can potentially simulate anything symbolically.
However, classic AI’s methods don’t scale up well to more complex tasks. Turing also proposed a test to judge the worth of an artificial intelligence system known as the Turing test. In the Turing test, two rooms with terminals capable of communicating with each other are set up. The person judging the test sits in one room. In the second room, there is either another person or an AI system designed to emulate a person.
The judge communicates with the person or system in the second room and if he eventually cannot distinguish between the person and the system then the test has been passed. However, this test isn’t broad enough (or is too broad…) to be applied to modern AI systems.
The philosopher Searle made the Chinese room argument in 1980 stating that if a computer system passed the Turing test for speaking and understanding Chinese this doesn’t necessarily mean that it understands Chinese because Searle himself could execute the same program thus giving the impression that he understands Chinese, he wouldn’t actually be understanding the language, just manipulating symbols in a system.
If he could give the impression that he understood Chinese while not actually understanding a single word then the true test of intelligence must go beyond what this test lays out.
you can share your own thoughts on this topic
How Will Artificial Intelligence Affect Our Lives In The Next Ten Years?
A Brief Introduction to Artificial Intelligence
Read and commend on this topic: A Brief Introduction to Artificial Intelligence
In short, they help find useful information when you ask for it is using your voice; you can say “Where’s the nearest Indian restaurant?”, “What’s on my schedule today?”, “Remind me to call Mom or Dad at eight o’clock,” and the assistant will respond by finding information, relaying information from your phone, or sending commands to other apps.
AI is important in these apps, as they collect information on your requests and use that information to better recognize your speech and serve you results that are tailored to your preferences.
Microsoft says that Cortana “continually learns about its user” and that it will eventually develop the ability to anticipate users’ needs. Virtual personal assistants process a huge amount of data from a variety of sources to learn about users and be more effective in helping them organize and track their information.
A Brief Introduction to Artificial Intelligence and it important
Your smartphone, calculator, video games, car, bank & your house all use artificial intelligence daily; sometimes it’s obvious what it’s’ doing, like when you ask Siri to get you directions to the nearest gas station.
Sometimes it’s less obvious, like when you make an abnormal purchase on your credit card and don’t get a fraud alert from your bank. AI is everywhere, and it’s making a huge difference in our lives every day.
So, we can say that Artificial Intelligence (AI) is the branch of computer sciences that emphasizes the development of intelligent machines, thinking and working like humans. For example, speech recognition, problem-solving, learning, and planning.
Today, Artificial Intelligence is a very popular subject that is widely discussed in technology and business circles. Many experts and industry analysts argue that AI or machine learning is the future – but if we look around, we are convinced that it’s not the future – it is the present.
Yes, the technology is in its initial phase and more and more companies are investing resources in machine learning, indicating a robust growth in AI products and apps soon. Artificial intelligence or machine intelligence is the simulation of human intelligence processes by machines, especially computer systems.
Vision systems. The need to interpret, fully understand, and make sense of visual input on the computer, i.e. AI is used to try and interpret and understand an image – industrial, military use, satellite photo interpretation.
What is the purpose of AI?
When AI researchers first began to aim for the goal of artificial intelligence, the main interest was human reasoning… The specific functions that are programmed into a computer may be able to account for many of the requirements that allow it to match human intelligence
What is ASI artificial intelligence?
A superintelligence is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds.
What is the goal of AI?
Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem-solving”. General intelligence is among the field’s long-term goals.
What are the different types of AI?
We need to overcome the boundaries that define the four different types of artificial intelligence, the barriers that separate machines from us – and us from them.
Type I AI: Reactive machines
Type II AI: Limited memory
Type III AI: Theory of mind
Type IV AI: Self-awareness
Is the computer vision part of AI?
Artificial intelligence and computer vision share other topics such as pattern recognition and learning techniques. Consequently, computer vision is sometimes seen as a part of the artificial intelligence field or the computer science field in general.
Is machine learning the same as artificial intelligence?
Increasingly, machine learning (ML) and artificial intelligence (AI) are cropping up as solutions for handling data. The two are often used interchangeably, and although there are some parallels, they’re not the same thing.
What are the fields of artificial intelligence?
· List of applications
· Optical character recognition.
· Handwriting recognition.
· Speech recognition.
· Face recognition.
· Artificial creativity.
· Computer vision, Virtual reality, and Image processing.
· Diagnosis (AI)
· Game theory and strategic planning.
How important is Artificial Intelligence?
AI is the machine that is designed and programmed in such a manner that they and think and act like a human. Artificial Intelligence becomes an important part of our daily life. Our life is changed by AI because this technology is used in a wide area of day to day services.
For most of us, the most obvious results of the improved powers of AI are neat new gadgets and experiences such as smart speakers or being able to unlock your iPhone with your face. But AI is also poised to reinvent other areas of life. One is health care.
Hospitals in India are testing software that checks images of a person’s retina for signs of diabetic retinopathy, a condition frequently diagnosed too late to prevent vision loss.
Machine learning is vital to projects in autonomous driving, where it allows a vehicle to make sense of its surroundings. Artificial intelligence is already present in plenty of applications, from search algorithms and tools you use every day to bionic limbs for the disabled.
finally why we give A Brief Introduction to Artificial Intelligence
Sometimes it seems like every other website, app, or productivity tool is citing AI as the secret ingredient in their recipe for success.
What’s less common is an explanation of what AI is, why it’s so cool, and how companies are leveraging it to provide better user experiences.
If you don’t know much about AI, the absence of an explanation can be confusing. Today, the field of artificial intelligence is more vibrant than ever and some believe that we’re on the threshold of discoveries that could change human society irreversibly, for better or worse.
artificial intelligence will destroy humanity
General Artificial Intelligence is a term used to describe the kind of artificial intelligence we are expecting to be human-like in intelligence. We cannot even come up with a perfect definition for intelligence, yet we are already on our way to build several of them. The question is whether the artificial intelligence we build will work for us or we work for it.
If we have to understand the concerns, first we will have to understand intelligence and then anticipate where we are in the process. Intelligence could be said as the necessary process to formulate information based on available information. That is basic. If you can formulate new information based on existing information, then you are intelligent.
General Artificial Intelligence Will Be More Than Intelligence
Since this is much scientific than spiritual, let’s speak in terms of science. I will try not to put a lot of scientific terminologies so that a common man or woman could understand the content easily. There is a term involved in building artificial intelligence. It is called the Turing Test. A Turing test is to test artificial intelligence to see if we could recognize it as a computer or we couldn’t see any difference between that and human intelligence. The evaluation of the test is that if you communicate to artificial intelligence and along the process, you forget to remember that it is actually a computing system and not a person, then the system passes the test. That is, the system is truly artificially intelligent. We have several systems today that can pass this test within a short while. They are not perfectly artificially intelligent because we get to remember that it is a computing system along the process somewhere else.
artificial intelligence in manufacturing
An example of artificial intelligence would be the Jarvis in all Iron Man movies and the Avengers movies. It is a system that understands human communications, predicts human nature, and even gets frustrated in points. That is what the computing community or the coding community calls General Artificial Intelligence.
To put it up in regular terms, you could communicate to that system as you do with a person and the system would interact with you like a person. The problem is people have limited knowledge or memory. Sometimes we cannot remember some names. We know that we know the name of the other guy, but we just cannot get it on time. We will remember it somehow, but later at some other instance. This is not called parallel computing in the coding world, but it is something similar to that. Our brain function is not fully understood but our neuron functions are mostly understood. This is equivalent to say that we don’t understand computers but we understand transistors; because transistors are the building blocks of all computer memory and function.
When a human can parallel process information, we call it memory. While talking about something, we remember something else. We say “by the way, I forgot to tell you” and then we continue on a different subject. Now imagine the power of the computing systems. They never forget something at all. This is the most important part. As much as their processing capacity grows, the better their information processing would be. We are not like that. It seems that the human brain has a limited capacity for processing; on average.
introduction to artificial intelligence
The rest of the brain is information storage. Some people have traded off the skills to be the other way around. You might have met people that are very bad at remembering something but are very good at doing math just with their heads. These people have actually allocated parts of their brain that is regularly allocated for memory into processing. This enables them to process better, but they lose the memory part.
The human brain has an average size and therefore there is a limited amount of neurons. It is estimated that there are around 100 billion neurons in an average human brain. That is at a minimum of 100 billion connections. I will get to the maximum number of connections at a later point in this article. So, if we wanted to have approximately 100 billion connections with transistors, we will need something like 33.333 billion transistors. That is because each transistor can contribute to 3 connections.
artificial intelligence and machine learning
Coming back to the point; we have achieved that level of computing in about 2012. IBM had accomplished simulating 10 billion neurons to represent 100 trillion synapses. You have to understand that a computer synapse is not a biological neural synapse. We cannot compare one transistor to one neuron because neurons are much more complicated than transistors. To represent one neuron we will need several transistors. In fact, IBM had built a supercomputer with 1 million neurons to represent 256 million synapses. To do this, they had 530 billion transistors in 4096 neurosynaptic cores according to research.ibm.com/cognitive-computing/neurosynaptic-chips.shtml.
Now you can understand how complicated the actual human neuron should be. The problem is we haven’t been able to build an artificial neuron at a hardware level. We have built transistors and then have incorporated software to manage them. Neither a transistor nor an artificial neuron could manage itself, but an actual neuron can. So the computing capacity of a biological brain starts at the neuron level but artificial intelligence starts at much higher levels after at least several thousand basic units or transistors.
The advantageous side of artificial intelligence is that it is not limited within a skull where it has a space limitation. If you figured out how to connect 100 trillion neurosynaptic cores and had big enough facilities, then you can build a supercomputer with that. You can’t do that with your brain; your brain is limited to the number of neurons. According to Moore’s law, computers will at some point take over the limited connections that a human brain has. That is the critical point of time when the information singularity will be reached and computers become essentially more intelligent than humans. This is the general thought on it. I think it is wrong and I will explain why I think so.