You might be very familiar with AI, but the true wonder lies in its evolution. Before delving deep into its operations and processing, let’s take a quick glimpse at its evolutionary journey.

As you might know or have thought at least once, the evolution of AI has been transformative and was marked by significant milestones. It was in the 1940s and 50s, that pioneers like Alan Turing, one of the first to investigate the theoretical possibility of ‘machine learning’, and John McCarthy, one of the founders of the discipline of Artificial Intelligence, laid the foundation for machine learning and artificial intelligence.

In the 1980s, advanced expert systems mimicking human decision-making emerged, followed by neural network advancements in the 1990s and early 2000s. This led to the advancement of deep-rooted learning algorithms. By the 2010s, AI began to be utilized in real-world applications, from virtual assistants to advanced data analytics and analytical modeling.

AI continues to evolve every day, driven by advances in natural language processing, reinforcement learning, and ethical AI. With the integration of AI across various industries, it promises improved efficiency, productivity, and decision-making, thus molding the future of technology and society.

Andrew Ng, a British-American computer scientist, mentioned in a TED talk on AI that AI systems excel at identifying patterns when provided with the right data. He emphasized that despite the common belief that AI only works with massive data sets, it can also be effective with smaller amounts of data, which can in turn improve business revenue. Nowadays, many large tech companies rely on AI to solve various problems; however, the cost may be prohibitive for others. Consequently, Andrew suggests that a new approach to building AI systems is emerging, which will allow more people to participate. This approach does not require coding but demands valid data from the users. This makes it easier for people to integrate AI into their daily lives.