Evolution of AI to a Powerful tool

Evolution of AI

In the past few years, AI evolved into a powerful tool that enables machines to think and act like humans. Moreover, it has garnered focus from tech companies around the world and is considered as the next significant technological shift after the evolution in mobile and cloud platforms. Some even call it the fourth industrial revolution. Forbes states, “By 2020, businesses that use AI and related technologies like machine learning and deep learning to uncover new business insights will take $1.2 trillion each year from competitors that don’t employ these technologies.”

This article gives you an overview of the evolution of AI and sets a foundational understanding of important milestones that led the path for AI surge.

Artificial Intelligence

Artificial intelligence is a discipline of computer science concerned with the modelling of intelligent behaviour in computers 

According to the Merriam Webster dictionary. 

A machine that is capable of making intelligent judgments might be referred to as artificially intelligent. People use the phrases machine learning, deep learning, and artificial intelligence (AI) almost interchangeably. It is true that deep learning is a subset of machine learning and AI itself.

When did the surge start

In the 1800s, AI was confined to the realms of fantasy, literature, and speculative thinking. This was the concept of classical thinkers, who envisioned a world where humans and machines coexisted. They were, however, only depicted in fiction at the time, such as in Mary Shelly's "Frankenstein.". In 1956, the genuine start of AI was made. Attendees at Darthmod College's AI workshop were proclaimed as the future of the field for decades to come. 

The AI boom started with the following six key design objectives: 

1. Playing chess, solving mathematical theorems, and other complex mental activities may be taught to robots by teaching them how to think. 
2. An understanding of the actual world as a human would need robots to recognise things, people, and languages. Lisp, a programming language designed specifically for this purpose, was created. 
3. Make robots capable of planning and navigating their way across our planet. Self-driving machines might be possible with this technology. 
4. Automate the process of analysing and comprehending human speech in order to make computers more intelligent. 
5. Human-like perception of touch, feel, sight, hearing, and taste may be taught to robots. 
6. Emotional intelligence, intuition, and creativity were all part of general intelligence. 

All of these objectives provide the groundwork for creating a machine that can do human-like functions. Bringing their idea to reality required hundreds of thousands of dollars in funding. A lack of powerful computer technology required for AI implementation was quickly discovered by US government officials. In the late 1980s, the funding were removed, and the expedition came to a standstill. 

Computers and vast amounts of data required in the 1980s slowed development. However, in the twenty-first century, the notion was swiftly revived, demonstrating Moore's law. Artificial Intelligence (AI) has become a reality in the contemporary era because to the massive processing capacity of silicon microchips. 

Artificial intelligence's revival and revolution was ignited four times in quick succession. 

MOOCs from Stanford University with Andrew NG, and Intro to ML by Sebastian Thurn and Katie Malone from Udacity were the first steps towards the democratisation of AI knowledge. 

That made AI accessible to the public without massive upfront investment or becoming a mega-corporation. 

In order to make use of the resources available, you still needed to be an expert in artificial intelligence (AI). However, new tools and frameworks emerged in 2015 that allowed the general public to experiment with and operationalize production-level AI. Google (TensorFlow) and Facebook (Facebook Graph API) have made it easier for small businesses to build on their massive resources ( PyTorch). With the democratisation of AI, several groups like FastAI and OpenAI were born. 

Since then, AI as a service has taken this a step further, making it simpler to prototype, explore, and even construct complex AIs that are customised to certain use cases inside the product. It's possible to get artificial intelligence (AI) services in the cloud on a variety of different platforms.

As a result of AI, we've seen everything from kitten videos to self-driving automobiles. Increasing numbers of firms are attempting to use AI to address challenges and develop an AI strategy inside their company.. As AI progresses toward its current state of completion, it is achieving more and more of its original six aims. A future in which people and robots coexist appears plausible as technology continues to improve. After a few years of observing the trend, it's time to start designing our AI strategy for the future.