Everything that is not used wisely could pose a potential threat, and the same applies to Artificial Intelligence. From IT industries to automobiles and aviation, AI is present everywhere and continuously evolving. It gives a machine the ability to learn, reason, apply logic, and produce results in a way similar to the human brain.

The accuracy of the prediction is directly proportional to the amount of data fed into the system. AI has major advantages that make our lives simpler and easier. However, it has some disadvantages too. So, let’s discuss them in detail, but before that, we have to understand what the major segments or types of AI are there.

4 major Segments of Development of Artificial Intelligence:

Artificial Intelligence is an interdisciplinary branch of computer science that aims to make machines capable of mimicking the human brain with capabilities such as perception, problem-solving, decision-making, problem-solving, and creativity.

It aims to efficiently solve or perform tasks that typically require human intelligence such as painting, philosophy, theorem proving, testing hypotheses, driving, finding the best path, predicting the weather, etc.

AI is one of the most popular branches of computer science and companies are looking for skilled AI professionals to create better training models and AI applications. An Artificial Intelligence Online Course along with basic knowledge of computer science concepts could take you a step further or kick-start your career in artificial intelligence.

Below are the four segments that Artificial Intelligence is majorly classified in based on its development stages:

Reactive AI

Machines with reactive AI don’t store any memory and react based on the current scenario. A notable example of reactive AI is the Deep Blue supercomputer. It was created by IBM in the year 1980 that ultimately won the chess match against the world chess champion Garry Kasparov.

Reactive AI responds in the exact same way to identical situations with no variance between twen results and doesn’t store any data about the past events.

Limited Memory AI

Compared to Reactive AI. Limited memory AI is more complex and has the ability to absorb the learning data and improve the system’s performance over time. It uses deep learning algorithms and mimics human neuron connections to create training models and discover hidden patterns. A prominent example of Limited Memory AI would be Self-driving cars that use deep learning algorithms to analyze the speed and position of vehicles to make real-time decisions.

Theory of Mind AI

Theory of Mind AI is achieved when machines are able to replicate thinking and decision-making capabilities like humans and other creatures. For example, robots like Sophia and Kismet show some aspects of this AI. Theory of mind AI rapidly used in natural language processing to make the communication between humans and machines more fluid.

Self-Aware AI

Self-Aware AI is the extension of the theory of mind AI where machines show self-awareness and are able to make conscious decisions. When self-aware AI is achieved, we can say that a machine has human-level consciousness with the same emotions, intelligence, and desires.

This AI has not been achieved yet, because of the limitations of computation power and hardware. However, if we’re able to achieve this type of AI, it can upgrade itself at a much faster rate and be thousands of times more powerful than humans.

Advantages and Disadvantages of Artificial Intelligence

Below are some of the major advantages of Artificial Intelligence in various fields:

Zero Human Error: Humans make a lot of mistakes even in repetitive tasks such as production lines. However, Ai-powered computers nullify these mistakes and produce the exact same result every single time. A good example of this is the weather predictions system recently designed by google. It can accurately predict the weather and events like thunderstorms up to six hours ahead of time.
Zero Risks: AI-powered machines are used in various industries where human presence could either be risky or lethal like coal mines, oil refineries, sewage, and nuclear power plants. Machines with AI capabilities are also used in rescue operations, reducing the pressure from human teams.
Round-the-clock availability: Machines don’t get tired, they can work without any breaks and produce accurate results repeatedly. This, in turn, increases the production capacity of your business and also improves customer satisfaction. Similarly, AI softwares like chatbots like Amazon lex provides 24 hours assistance and recognizes customer’s intentions with the help of follow-up questions and keywords.
Faster Decisions: With better performance and computation power, machines can process huge amounts of data and produce faster results. At the same time, AI can take multiple factors into consideration and help the user make accurate decisions.
Daily Application: Google’s OK Google, Window’s Cortana, and Apple’s Siri are some of the AI systems that people use for making phone calls, managing time schedules, remembering important information, replying to emails, and searching for locations on the daily basis.
New Inventions: Any theory or model has to produce accurate results against various datasets, which means you have to process huge datasets in order to prove it’s worth. For example, AI-based models can now predict breast cancer at the earlier stages, for which it was trained with thousands of cancer cases and complex problems.

However, everything with a bright side has a darker side too, and AI is no different. Let’s see some of the disadvantages of AI

High Cost: AI applications use concepts like Artificial Neural Networks which require powerful hardware with impeccable computational power to process complex information. Also, it costs a lot to maintain such hardware and needs repairing which further adds up to the cost.
Unemployment: Ai is quickly replacing the jobs where people have to perform repetitive tasks or don’t show any creativity. For example, industries are replacing humans with robots for product assembly, cleaning, and quality assurance which can cause a major problem of unemployment in the near future.
No emotions: Robots don’t have any emotions, or at least not on the level compared to humans. This means they cannot develop a bond with humans or other machines to solve a specific problem which is an essential part of team management.
Box thinking: Machines can only perform the tasks which they’re designed for, anything out of their limit will result in malfunction, system crash, or produce irrelevant outputs.

Applications of AI

Following are some of the best applications of AI in real life:

E-commerce websites use recommendation systems to provide a personalized shopping experience based on the user’s browsing history, interests, keywords, and previous orders.
Banks use AI applications to detect fraudulent transactions by analyzing the accounts and transactions of thousands of customers simultaneously.
Navigation systems use a combination of Machine learning algorithms and neural networks to detect the location and find the shortest path.
Artificial Intelligence used in robotics to interact with the surrounding environment, detect obstacles, and provide real-time updates.
AI-powered drones are used in various fields such as tree plantation, film-making, and aerial surveys, and collecting the information of any disaster.
The Healthcare sector uses sophisticated machines and complex models to detect various diseases at early stages. Moreover, AI is used to estimate the effect of any drug on the human body.
Social media apps like Facebook, Twitter, and Instagram use AI algorithms to translate the posts into different languages, provide suggestions, detect fraud, and remove inappropriate content.

Conclusion

Artificial Intelligence has revolutionized many industries and is also having an impact on our lives. It’s helping us, humans, to solve complex problems and improve current technologies that will eventually lead to a better future. From agriculture to space, AI is implemented in every field in some form. The future of AI will depend on how we design and for what purpose we use it today.

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