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## **The fundamental theories behind Artificial Intelligence**

Artificial Intelligence has grown into a formidable technology that allows robots to think and act like humans. Furthermore, AI has been the center of attraction for various IT firms all around the world remarking as a breakthrough technological revolution. It has brought multifold growth of mobile and cloud platforms and minimizes the chances of errors by improving generation to generation through AI algorithms with no need for human intervention.

In the era of heightened expectations for Artificial Intelligence, we can see how it has evolved in the market. For an instance, we have Siri in iPhone, self-driving cars, Maps and Navigations, Text Editors and Autocorrects, and more. Gradually with AI, there has been a proliferation of data mining, machine learning, and predictive system that are committed to an unprecedented level of machine intelligence.

However, AI has gone through multiple waves of huge expectations followed by evolution in technology, disappointments with the application of innovation, and more. We have witnessed the rise and fall of the expert system, neural networks, and most importantly the statistical method of understanding the technology at the helm.

> ***But how AI came into the world of technology?***
> 

> ***Have we experienced AI before?***
> 

> ***How does the evolution of AI begin?***
> 

## **The History of Artificial Intelligence**

The concept of Artificial Intelligence has been prevalent for centuries. However, in the 1950’s the true [possibility of AI was discovered]( https://www.bairesdev.com/blog/history-of-ai).

A conglomeration of mathematicians, scientists, and philosophers brought AI into the light during the period when a British Polymath – Alan Turing proposed that a human can use available information for solving problems and making decisions why machines can’t?

The thought was struck when he further outlined machines and how to test their intelligence in the paper Computing Machinery and Intelligence in 1950. However, this thought was good but not progressive.

It took a halt there only because during those times computers didn’t have the growth factor. Because computers could just execute commands. They weren’t capable enough to store the information.

### **Flourishment in Computers led flourishment in AI**

Later in 1974, computers were flourished. Computers were now faster, affordable, and could store more data significantly. Their early demonstration - Allen Newell and Herbert Simon’s General Problem Solver and Joseph Weizenbaum’s ELIZA was funded by Research and Development Corporation (RAND). Such a flourishment in computers gave hope for solving problems and stressed the interpretations of spoken language in machines.

However, we were still far away because machines couldn’t think abstractly, nor can perform self-recognition or natural language processing NLP models.

In 1980, AI Research came back with an opportunity of expanding the funds and leveraging the algorithmic tools. During that period, John Hopfield and David Rumelhart popularized “deep learning” techniques. This helped computers in learning a human language using this experience.

While, Edward Feigenbaum introduced expert systems that imitated the decision-making processes of a human expert. However, due to a lack of public attention and government support, it didn’t garner much popularity and importance.

## **Today’s AI Research**

In the current era, AI Research is growing impeccably and continues to reach beyond the boundaries owing to the latest tools and ancillary technologies. According to technology writer Alice Bonasio, AI Research has [flourished by 12.9%](https://www.ukessays.com/essays/technology/business-applications-of-artificial-intelligence.php) annually worldwide.

And in the coming years, China is predicted to become the leading source of AI surpassing its neck-to-neck competitor – the United States (which was a leader in 2004) which is quickly closing in on Europe’s number one spot.

Today, Europe is the leading region in the field of artificial intelligence research backed by international collaboration. However, India ranks in the third position in the context of AI Research output. Some of the distinct research areas with limitations on AI ethics research are -:

- Search and Optimization
- Natural Language Processing and Knowledge Representation
- Machine Learning and Probabilistic Reasoning
- Fuzzy Systems
- Planning and Decision Making
- Neural Networks
- Computer Vision

## **Present Effects of AI**

Companies are spending [billions of dollars](https://www.business-standard.com/article/technology/global-artificial-intelligence-spending-to-reach-434-bn-in-2022-report-122022000195_1.html) on Artificial Intelligence – products and services for automating their business operations at the helm. Tech giants like –Google, Apple, Microsoft, and IBM are spending billions in creating AI-led products and making them scalable to thrive with technological reforms.

Apart from that, universities are investing significantly to introduce AI and make it a prominent part of curricula. For instance, MIT has just [announced a $1 billion plan](https://www.technologyreview.com/2018/10/15/139781/mit-has-just-announced-a-1-billion-plan-to-create-a-new-college-for-ai/) to create a new college for AI and include collaborative concepts like ML and Data Science with other academic disciplines. This shows that there is a lot more to happen with the advancement in Artificial Intelligence.

## **The Impact of AI technology in today’s world**

Artificial Intelligence can collect and organize large amounts of data for generating insights and stresses upon the capabilities of humans and their ability for manual processing.

It also streamlines the efficacies of organizations that would minimize the likelihood of human errors and smartly detect irregular patterns, like the presence of unsolicited activity, spam of data, and fraud, and simultaneously warn businesses in real time about any suspicious activity spotted.

AI contributes crucially to optimizing your costs in various other ways — for an instance, “training” machines for handling and managing incoming customer support calls. It has further brought a revolution in replacing many jobs with intelligent processes and systems so that your business can focus on core activities at large.

Start incorporating your business solutions with AI processes to keep yourself ahead of the competitors.

## **A Smarter Future Ahead**

Today, we are on the cusp of the 4th Industrial Revolution which is completely different and unique in its way compared to the previous ones. From workflow management tools to smart virtual assistants and self-driving cars to checkout-free grocery shopping, Artificial Intelligence is increasing its productivity just like never before.

Today, AI-powered robots are capable of solving problems and thinking within a limited capacity. Robots have worked on the assembly lines of Tesla and a few high-tech restaurants that interact with customers, and bring food to their tables. It often acts as a teacher in teaching Japanese students English – doing plentiful in the area of AI.

As a part of AI, our workplaces and organizations have become “smarter” and more efficient as machines, and humans are starting to work together, and we use connected devices to enhance our supply chains and warehouses.

### **Applications of AI in Different Industry verticals**

Artificial Intelligence can enhance the value of your company in several ways. It contributes significantly to optimizing your business operations, boosting your total revenue, and improving the productivity of your staff at the workplace.

This shows that it is popularly used in a variety of industries all across the globe including manufacturing, transportation, healthcare, finance, and more.

**Health Care**

AI in healthcare has simplified the lives of doctors and patients. AI can diagnose faster and help you with robot-assisted surgeries to deliver advanced medical treatment and patient experience.

**Automotive**

Self-driving vehicles show that the future of AI is here and much exciting and advanced is yet to come. It’s no longer science fiction; the autonomous car is already a reality. It also includes industrial robots that construct a vehicle and autonomous cars, and navigate traffic with machine learning and vision.

**Agriculture**

AI system in Agriculture helps you in improving the overall harvesting quality and accuracy of the crop. It can detect disease in crops and poor nutrition through AI sensors that give you suggestions regarding which herbicide to apply within the region.

**Manufacturing**

AI in the manufacturing sector can share insights on the production data and that’s how you can improve failure prediction and maintenance planning. You can also factory performance across regions and equipment performance at one facility.

## **The Final Words**

Today, Artificial Intelligence is growing at a breakneck bringing automation and advancement in business operational activities to par. Considering the fundamental theories behind AI, it looks like the future is vast and massive.

WAs algorithms and computers advance, AI will be furthermore able to do more with fewer resources.

RadicalLoop is a [trusted Web and Mobile App Development Company](https://www.radicalloop.com/). We stay abreast with the latest technologies like AI and incorporate the same while building any app or website for your business. [Let’s connect today!](https://www.radicalloop.com/contact)

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AI is growing at a breakneck bringing automation & advancement in business operational activities to par. Considering the fundamental theories behind AI, it looks like the future is vast and massive.

The Fundamental Theories Behind Artificial Intelligence(AI)

Radicalloop