Demystifying AI (Series 1/10)

In today's tech-driven world, "Artificial Intelligence" (AI) is the topic of the year.

With the emergence of groundbreaking technologies like OpenAI's ChatGPT and the ongoing rivalry among top technology companies, the terms 'AI' and 'ML' have surged in importance. But what exactly do these abbreviations stand for, and how do they shape our digital landscape?

Let's start with ML, a subset of AI.

Machine Learning (ML) aims to teach machines how to perform specific tasks and deliver accurate results by identifying patterns within data. ML applications learn from input data and continually enhance the accuracy of output data using a diverse array of algorithms. On the other hand, AI encompasses the broader concept of machines mimicking human intelligence.

It's commonly understood that the better the ML model, the more accurately it can discern features and patterns within data. This precision translates to more accurate decisions and predictions.

The roots of AI and ML trace back several decades. The field of AI dates to the 1950s when Arthur Lee Samuel, an IBM researcher, developed one of the earliest ML programs—a self-learning program for playing checkers. In fact, he is credited with coining the term "machine learning."

Today, organisations leverage advanced ML models to predict changes in their businesses continually. But how do these ML models arrive at their predictions?

The answer lies in big data.

Big data is any kind of data source that has atleast one of four shared characteristics, called the four Vs:

1. Extremely large volumes of data
2. The ability to move that data at a high velocity of speed
3. An ever-expanding variety of data sources
4. Veracity so that data sources truly present truth

Big data comprises structured, unstructured, and semi-structured data, painting a comprehensive picture of various aspects of our world. For instance, in the realm of economics, big data incorporates traditional economic indicators, administrative records, social media posts, online transactions, sensor data, satellite imagery, and more.

In conclusion, the advent of AI and ML marks a transformative era in technology, with OpenAI's ChatGPT and other advancements leading the charge. As organisations harness the power of ML models fueled by big data, they gain unprecedented insights and predictive capabilities, enabling them to navigate complex landscapes with agility and foresight. With continued innovation and refinement, the future promises even greater strides in AI and ML, shaping industries and society in ways we have yet to imagine.