Artificial Intelligence

?What is Artificial Intelligence, what's the first thing that comes to your mind about thinking it?

AI is the technology which has recently been trending all over the world , it's rapid pace in growing the industry irrespective of the domain sets up a bright future in it. But what is AI? In simpler terms we can call it as the intelligence which is not of human brain or computer intelligence developed by human brain . Yes that in simple words will explore more about it its real meaning, uses in industry currently, types of AI , software's used in AI, future applications and its pros and cons . So let's explore what is AI.

Definition of AI

Artificial intelligence (AI) is intelligence demonstrated by machines, as opposed to natural intelligence displayed by animals including humans. Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism, followed by disappointment and the loss of funding (known as an "AI winter"), followed by new approaches, success and renewed funding. AI research has tried and discarded many different approaches since its founding, including simulating the brain, modeling human problem solving, formal logic, large databases of knowledge and imitating animal behavior. In the first decades of the 21st century, highly mathematical statistical machine learning has dominated the field, and this technique has proved highly successful, helping to solve many challenging problems throughout industry and academia.

The various sub-fields of AI research are centered around particular goals and the use of particular tools. The traditional goals of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception, and the ability to move and manipulate objects. AI works by combining large amounts of data with fast, iterative processing and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data. AI is a broad field of study that includes many theories, methods and technology as well as the following major subfield

1. Machine learning?

2. Neural networks?

3. Deep learning?

4. Internet of things .

Types of AI?

According to the system of classification ,there are 4 types of AI based systems Reactive machines, limited memory machines, theory of mind and self aware AI.

1. Reactive machines -?These are the oldest forms of AI systems that have extremely limited capability. They emulate the human mind’s ability to respond to different kinds of stimuli. These machines do not have memory-based functionality. This means such machines cannot use previously gained experiences to inform their present actions, i.e., these machines do not have the ability to “learn.”?A popular example of a reactive AI machine is?IBM’s Deep Blue, a machine that beat chess Grandmaster Garry Kasparov in 1997.

2.Limited memory -?Limited memory machines are machines that, in addition to having the capabilities of purely reactive machines, are also capable of learning from historical data to make decisions. Nearly all existing applications that we know of come under this category of AI. All present-day AI systems, such as those using deep learning, are trained by large volumes of training data that they store in their memory to form a reference model for solving future problems.?Almost all present-day AI applications, from chatbots and virtual assistants to self-driving vehicles are all driven by limited memory AI.

?3.Theory of mind -?While the previous two types of AI have been and are found in abundance, the next two types of AI exist, for now, either as a concept or a work in progress. Theory of mind AI is the next level of AI systems that researchers are currently engaged in innovating. A theory of mind level AI will be able to better understand the entities it is interacting with by discerning their needs, emotions, beliefs, and thought processes. While?artificial emotional intelligence?is already a budding industry and an area of interest for leading AI researchers, achieving Theory of mind level of AI will require development in other branches of AI as well.?

4.Self aware -?This is the final stage of AI development which currently exists only hypothetically. Self-aware AI, which, self explanatorily, is an AI that has evolved to be so akin to the human brain that it has developed self-awareness. Creating this type of Ai, which is decades, if not centuries away from materializing, is and will always be the ultimate objective of all AI research. This type of AI will not only be able to understand and evoke emotions in those it interacts with, but also have emotions, needs, beliefs, and potentially desires of its own.?The alternate system of classification that is more generally used in tech parlance is the classification of the technology into Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Superintelligence (ASI).

Uses in Industry of AI

• Virtual Assistant or Chatbots
• Agriculture and Farming
• Autonomous Flying
• Retail, Shopping and Fashion
• Security and Surveillance
• Sports Analytics and Activities
• Manufacturing and Production
• Live Stock and Inventory Management
• Self-driving Cars or Autonomous Vehicles
• Healthcare and Medical Imaging Analysis
• Warehousing and Logistic Supply Chain
• Google Search
• Smart home devices

Software used in AI.

As AI is used with the term computers , generally computer languages do come into play. Today AI marks the use of Python, the latest and trending computer language, Except from Python there are lot many computer languages used in AI, such as java, advance Javascript, C, C++,?R, Prolog, Lisp, Haskell, Wolfram, Small talk and Rust.

Post pandemic, AI has become one of the top agendas for businesses as it offers enhanced customer experience, resilience, and reliability. With the advancements in machine learning, data analytics, and conversational AI, companies are finding it feasible and affordable to deploy AI tools that allow them to solve problems and increase efficiency.

Building an AI solution not only requires a clear set of requirements but also the right selection of technologies and AI programming languages that make?AI development?practically possible and smooth. To make the selection easier, here we are with the?top 10 best languages for ai?that are widely used to develop AI applications across a wide range of industry segments.

Future Applications of AI

Future applications means the applications of AI after 30 to 40 years so what are the applications of AI in future so lets see.

1. AI in Science and Research.

2. Ai in Cyber security.

3. AI in Data Analysis.

4. AI in Transport.

5. AI in Home.?

6. AI in Healthcare.

Advantages and Disadvantages of AI

Advantages?

1. Reduction in Human Error -?The phrase “human error” was born because humans make mistakes from time to time. Computers, however, do not make these mistakes if they are programmed properly. With Artificial intelligence, the decisions are taken from the previously gathered information applying a certain set of algorithms. So errors are reduced and the chance of reaching accuracy with a greater degree of precision is a possibility.?Example:?In Weather Forecasting using AI they have reduced the majority of human error.

2. Takes risk instead of Humans -?This is one of the biggest advantages of Artificial intelligence. We can overcome many risky limitations of humans by developing an?AI Robot?which in turn can do the risky things for us. Let it be going to mars, defuse a bomb, explore the deepest parts of oceans, mining for coal and oil, it can be used effectively in any kind of natural or man-made disasters.

3. Available 24/7 -?An Average human will work for 4–6 hours a day excluding the breaks. Humans are built in such a way to get some time out for refreshing themselves and get ready for a new day of work and they even have weekly offed to stay intact with their work-life and personal life. But using AI we can make machines work 24x7 without any breaks and they don’t even get bored, unlike humans.?Example:?Educational Institutes and Helpline centers are getting many queries and issues which can be handled effectively using AI.

4. Digital Assistance?-?Some of the highly advanced organizations use digital assistants to interact with users which saves the need for human resources. The digital assistants also used in many websites to provide things that users want. We can chat with them about what we are looking for.?Example:?We all know that organizations have a customer support team that needs to clarify the doubts and queries of the customers. Using AI the organizations can set up a Voice bot or Chatbot which can help customers with all their queries. We can see many organizations already started using them on their websites and mobile applications.

5. Daily Applications -?Daily applications such as Apple’s?Siri, Window’s?Cortana, Google’s?OK Google?are frequently used in our daily routine whether it is for searching a location, taking a selfie, making a phone call, replying to a mail and many more.?Example:?Around 20 years ago, when we are planning to go somewhere we used to ask a person who already went there for the directions. But now all we have to do is say “OK Google?where is Visakhapatnam”. It will show you Visakhapatnam’s location on google map and the best path between you and Visakhapatnam.

As every brighter side has a darker version in it . So lets look at the disadvantages of AI

Disadvantages

1. High costs of creation -?As AI is updating every day the hardware and software need to get updated with time to meet the latest requirements. Machines need repairing and maintenance which need plenty of costs. It’ s creation requires huge costs as they are very complex machines.

2. Making Humans lazy -?AI is making humans lazy with its applications automating the majority of the work. Humans tend to get?addicted?to these inventions which can cause a problem to future generations.

3. Unemployment -?As AI is replacing the majority of the repetitive tasks and other works with robots, human interference is becoming less which will cause a major problem in the employment standards. Every organization is looking to replace the minimum qualified individuals with AI robots which can do similar work with more efficiency.

4. No emotions -?There is no doubt that machines are much better when it comes to working efficiently but they cannot replace the human connection that makes the team. Machines cannot develop a bond with humans which is an essential attribute when comes to Team Management.

5. Lacking out of box thinking -?Machines can perform only those tasks which they are designed or programmed to do, anything out of that they tend to crash or give irrelevant outputs which could be a major backdrop.

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