The Future

Before going into the blog, Let me introduce myself to you , I am Sai Ganesh Addala and I am from Andhra Pradesh a state of combination of great history and spiritual mythology and the place where the most critical and awesome language called Telugu is used. I am a student of Amity university Jaipur , trying to give some information on the most essential thing in future . It's Artificial Intelligence Artificial intelligence       Future

  September 19,2021

  

 Welcome to the Future

  

Wʜᴀᴛ ɪs ᴀʀᴛɪғɪᴄɪᴀʟ ɪɴᴛᴇʟʟɪɢᴇɴᴄᴇ ?

Artificial intelligence (AI), is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals. ... As machines become increasingly capable, tasks considered to require "intelligence" are often removed from the definition of AI, a phenomenon known as the AI effect.

              An innovative Artificial Intelligence process helps improve  our understanding of complex connections and describe them using simple equations. These will help machine and system operators become more efficient

             Artificial Intelligence has become the keyword which defines the future and everything that it holds. Not only has Artificial Intelligence taken over traditional methods of computing, but it has also changed the way industries perform. From modernizing healthcare and finance streams to research and manufacturing, everything has changed in the blink of an eye

            Artificial Intelligence has had a positive impact on the way the IT sector works; in other words, there is no denying the fact that it has revolutionized the very essence of the space. Since the IT sector is all about computers, software, and other data transmissions, there is a relatively important role Artificial Intelligence can play in this domain

           Artificial Intelligence is a branch of computer science that aims at turning computers into intelligent machines, which would otherwise not be possible without a human brain. Through the use of algorithms and computer-based training, Artificial Intelligence and Machine Learning can effectively be used to create expert systems that will exhibit intelligent behavior, provide solutions to complicated problems, and further help to develop stimulations equivalent to human intelligence within machines.

Automating Processes : 

The benefit of automation is that almost every piece of work can be done without human intervention. Through the use of deep learning applications, organizations can go a long way in automating backend processes, which help enable cost savings and reduce human intervention. AI enabled methods improve over time as the algorithms adjust to enhance productivity and learn from mistakes.

Future of Artificial Intelligence

Remember those Hollywood science fiction movies that we watched during childhood or even the Bollywood movie ‘Robot’, where the Robot could even understand human emotions?

Well, those may not be ‘fiction’ for long. Artificial Intelligence is the future and as crazy as it may sound, the future could no longer be in our hands – it might be in our machine’s hands! Our brains are focussed on developing AI which is taking over faster than we can imagine.

A lot of visionaries like Stephen Hawking, Steve Wozniak, Elon Musk and others have predicted that AI could be dangerous because if machines started thinking better than humans, then where would humans be? 

Scared?

We have the power to diffuse what we have created. What we need to know is where to draw the line.

RoboticsThe types of AI :

           1. 𝚛𝚎𝚊𝚌𝚝𝚒𝚟𝚎 𝚖𝚊𝚌𝚑𝚒𝚗𝚎𝚜

           2. 𝙻𝚒𝚖𝚒𝚝𝚎𝚍 𝚖𝚎𝚖𝚘𝚛𝚢

           3. 𝚃𝚑𝚎𝚘𝚛𝚢 𝚘𝚏 𝚖𝚒𝚗𝚍𝚜 

           4. 𝚂𝚎𝚕𝚏 𝚊𝚠𝚎𝚛𝚎𝚗𝚎𝚜𝚜

  1.ʀᴇᴀᴄᴛɪᴠᴇ ᴍᴀᴄʜɪɴᴇs :

    The most basic types of AI systems are purely reactive, and have the ability neither to form memories nor to use past experiences to inform current decisions. Deep Blue, IBM’s chess-playing supercomputer, which beat international grandmaster Garry Kasparov in the late 1990s, is the perfect example of this type of machine.

Deep Blue can identify the pieces on a chess board and know how each moves. It can make predictions about what moves might be next for it and its opponent. And it can choose the most optimal moves from among the possibilities.

But it doesn’t have any concept of the past, nor any memory of what has happened before. Apart from a rarely used chess-specific rule against repeating the same move three times, Deep Blue ignores everything before the present moment. All it does is look at the pieces on the chess board as it stands right now, and choose from possible next moves.

  

 2.Lɪᴍɪᴛᴇᴅ ᴍᴇᴍᴏʀʏ

This Type II class contains machines can look into the past. Self-driving cars do some of this already. For example, they observe other cars’ speed and direction. That can’t be done in a just one moment, but rather requires identifying specific objects and monitoring them over time.

These observations are added to the self-driving cars’ preprogrammed representations of the world, which also include lane markings, traffic lights and other important elements, like curves in the road. They’re included when the car decides when to change lanes, to avoid cutting off another driver or being hit by a nearby car.

But these simple pieces of information about the past are only transient. They aren’t saved as part of the car’s library of experience it can learn from, the way human drivers compile experience over years behind the wheel.

So how can we build AI systems that build full representations, remember their experiences and learn how to handle new situations? Brooks was right in that it is very difficult to do this. My own research into methods inspired by Darwinian evolution can start to make up for human shortcomings by letting the machines build their own representations.

3.Tʜᴇᴏʀʏ ᴏғ ᴍɪɴᴅs 

We might stop here, and call this point the important divide between the machines we have and the machines we will build in the future. However, it is better to be more specific to discuss the types of representations machines need to form, and what they need to be about.

Machines in the next, more advanced, class not only form representations about the world, but also about other agents or entities in the world. In psychology, this is called “theory of mind” – the understanding that people, creatures and objects in the world can have thoughts and emotions that affect their own behavior.

This is crucial to how we humans formed societies, because they allowed us to have social interactions. Without understanding each other’s motives and intentions, and without taking into account what somebody else knows either about me or the environment, working together is at best difficult, at worst impossible.

If AI systems are indeed ever to walk among us, they’ll have to be able to understand that each of us has thoughts and feelings and expectations for how we’ll be treated. And they’ll have to adjust their behavior accordingly.

4.Sᴇʟғ ᴀᴡᴀʀᴇɴᴇss

The final step of AI development is to build systems that can form representations about themselves. Ultimately, we AI researchers will have to not only understand consciousness, but build machines that have it.

This is, in a sense, an extension of the “theory of mind” possessed by Type III artificial intelligences. Consciousness is also called “self-awareness” for a reason. (“I want that item” is a very different statement from “I know I want that item.”) Conscious beings are aware of themselves, know about their internal states, and are able to predict feelings of others. We assume someone honking behind us in traffic is angry or impatient, because that’s how we feel when we honk at others. Without a theory of mind, we could not make those sorts of inferences.

While we are probably far from creating machines that are self-aware, we should focus our efforts toward understanding memory, learning and the ability to base decisions on past experiences. This is an important step to understand human intelligence on its own. And it is crucial if we want to design or evolve machines that are more than exceptional at classifying what they see in front of them.

This is the most promising area of AI which will make big strides in the future. Robotic engineers are constantly thinking of ways to create robots who behave like humans, interact like humans and think like humans. The future generation of engineers or today’s young minds are much interested in robotics from as early as 6-7 years and are already learning the basics of robotics. Robotics has the power to transform our future 

CONCLUSION :

AI is at the centre of a new enterprise to build computational models of intelligence. The main assumption is that intelligence (human or otherwise) can be represented in terms of symbol structures and symbolic operations which can be programmed in a digital computer. There is much debate as to whether such an appropriately programmed computer would be a mind, or would merely simulate one, but AI researchers need not wait for the conclusion to that debate, nor for the hypothetical computer that could model all of human intelligence. Aspects of intelligent behaviour, such as solving problems, making inferences, learning, and understanding language, have already been coded as computer programs, and within very limited domains, such as identifying diseases of soybean plants, AI programs can outperform human experts. Now the great challenge of AI is to find ways of representing the commonsense knowledge and experience that enable people to carry out everyday activities such as holding a wide-ranging conversation, or finding their way along a busy street. Conventional digital computers may be capable of running such programs, or we may need to develop new machines that can support the complexity of human thought.

“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.”

                  — Stephen Hawking told the BC

               THANK YOU