People naturally fear what they do not understand or have no control over fair statement? We could say the known is "ego". Artificial Narrow Intelligence (narrow meaning weak) as we currently know, and the possibility of AGI (general) Intelligence does not Imply any human like cognitive awareness or consciousness. while impressive, it is just advanced computation & problem solving.

Algorithms cannot replace emotions, Intrinsic understanding, self-awareness, or any type of subjective experience akin to human intelligence.

But what can or will it do?

Let’s start at the start, ANI has roots dating back to the 1940's as a concept.

Alan Turing's work in the 1940s, including his lost paper on "intelligent machinery," is considered some of the earliest substantial work in the field. In the 1950's Alan Turing proposed the " Turing Test" which was a way to determine a machines ability to exhibit Intelligent behaviour.

Fast forward to 1965 and Gordon Moore made a critical observation, he noticed a trend, relating to the number of transistors on a microchip, which roughly doubled every year (later revised to every two years). This observation, known as Moore's Law, became a guiding principle for the semiconductor industry, driving miniaturisation and exponential growth in computational power. The basic components of an expert system (1980’s) are the knowledge base and the inference engine. The knowledge base consists of all the important data for the domain-specific task. In 1997 IBM Deep Blue was the first computer to beat Garry Kasparov in chess. Gary was a reigning world chess champion and ultimately lost in a six-game match.

In 2010 IBM Watson (medical field) made strides in analysing medical literature & data to assist in diagnosis and treatment.

** Deep learning? machine learning? AI? is it all the same? ""

Deep Learning is a specialised subset of Machine Learning which, in turn, is a subset of Artificial Intelligence. In other words, Deep Learning is Machine Learning.

Computers learning from data is commonly referred to as machine learning. It defines the nexus between statistics and computer science when algorithms are utilised to carry out a certain task without the need for explicit programming, instead, they identify patterns in the data and forecast when fresh data becomes available. Depending on the data being fed into the algorithms, the learning process of these algorithms can be either supervised or unsupervised.

One way to think of deep learning algorithms is as an advanced and mathematically intricate development of machine learning algorithms. The field has been receiving a lot of attention lately, recent advancements have produced results that were previously unthinkable.

Big data and machine learning are having an impact on most aspects of modern life, from entertainment, commerce, and healthcare.

Consider that Netflix knows which films and series people prefer to watch, Amazon knows which items people like to buy when and where, and Google knows which symptoms and conditions people are searching for. All this data can (lets face it, it is) be used for very detailed personal profiling.

Also there is already a very large amount of evidence that AI algorithms are performing on par or better than humans in various tasks, for instance, in analysing medical images or correlating symptoms and biomarkers from electronic medical records (EMRs) with the characterisation and prognosis of the disease.

AI drives many industrial machines, carrying out several tasks faster and more reliably than humans. Furthermore, AI-powered warehouse robots can collect items and traverse their environment thanks to machine vision, which reduces the need for human warehouse personnel on the part of logistics companies.

Travel websites can use AI to enhance user searches and provide recommendations based on past queries. Travellers can now obtain the information they need without using a travel agency thanks to resources like virtual tours online.

The customer support role is becoming increasingly automated. Tech developments like self-checkouts also reduce the need for human labour in environments like grocery shops, which lowers the number of jobs in the customer service sector.

WAIT A MINUTE! - I work in IT I must be safe!!

Do not be surprised when most entry level roles across this sector succumb to automation.

Goldman Sach believes over 300 million jobs could be replaced by AI.

Forbes says that According to an MIT and Boston University report, AI will replace as many as two million manufacturing workers by 2025.

And a study by the McKinsey Global Institute reports that by 2030, at least 14% of employees globally could need to change their careers due to digitisation, robotics, and AI advancements.