Age: Born 6 November 2014. Appearance: Back then, like a dehumidifier that spied on you; now more of an invisible, all-knowing presence. You mean the woman who tells me the football scores? Yes, that Alexa – Amazon's ubiquitous virtual assistant, voiced by a speech synthesiser and powered by weak AI. What about her? It's the end of the year, so time for Amazon to reveal the questions Britons most often asked Alexa in 2023.

It's easy to mix up artificial intelligence (AI) and machine learning (ML). Despite the fact that machine learning is an element of artificial intelligence, these two phrases refer to two separate concepts that can be difficult to distinguish between. Put simply, machine learning is a subset of artificial intelligence, which is a large field of study. Machine learning is an application of AI that allows machines to learn from data without being explicitly programmed. AI is a larger idea that aims to produce intelligent machines that can replicate human thinking capabilities and behavior.

While weak AI focuses on automating specific tasks, strong AI is capable of learning and thinking like humans do. Weak AI can outperform humans on the specific tasks it is designed for, but it operates under far more constraints than even the most basic human intelligence. All the AI that's available today can be considered weak AI. Meanwhile, strong AI does not exist yet.

Since Google's artificial intelligence (AI) subsidiary DeepMind published a paper a few weeks ago describing a generalist agent they call Gato (which can perform various tasks using the same trained model) and claimed that artificial general intelligence (AGI) can be achieved just via sheer scaling, a heated debate has ensued within the AI community. While it may seem somewhat academic, the reality is that if AGI is just around the corner, our society--including our laws, regulations, and economic models--is not ready for it. Indeed, thanks to the same trained model, generalist agent Gato is capable of playing Atari, captioning images, chatting, or stacking blocks with a real robot arm. It can also decide, based on its context, whether to output text, join torques, button presses, or other tokens. As such, it does seem a much more versatile AI model than the popular GPT-3, DALL-E 2, PaLM, or Flamingo, which are becoming extremely good at very narrow specific tasks, such as natural language writing, language understanding, or creating images from descriptions.

In the past few years, we've seen technology advance at a breakneck speed. From the introduction of new gadgets to the widespread use of internet, the world has changed at a pace never seen before. But technology is also responsible for bringing about many misunderstandings. All of this to say that Artificial Intelligence is anything but artificial. Artificial Intelligence is a current trend that is often thrown around without people actually knowing what it means.

Remember in 2017, Elon Musk said that artificial intelligence would replace humanity in the next five years? While working on artificial intelligence for Tesla cars, he concluded that society had approached the moment when artificial intelligence could become significantly smarter than people. "People should not underestimate the power of the computer,'' Musk said. "This is pride and an obvious mistake." He must know what he's talking about, being one of the early investors of DeepMind, a Google subsidiary that developed an AI that could beat humans at Go and chess. AI is really good at many "human" tasks -- diagnosing diseases, translating languages, and serving customers.

While future developments in artificial intelligence research are likely to yield useful industrial applications, in the medium term the technology may turn out to be less revolutionary than many expect. Artificial intelligence (AI) can beat humans at complex tasks like chess and video games, but it still cannot reproduce behaviors that come naturally to people, like making small talk about the weather. In his 1994 book "The Language Instinct," linguist and cognitive scientist Steven Pinker concluded that: "The main lesson of thirty-five years of AI research is that the hard problems are easy, and the easy problems are hard." This paradox has led researchers to divide AI into two different types: artificial general intelligence or strong AI, and weak (or narrow) AI. Strong AI means the ability to learn any task that people can perform.

If you've spent any time reading articles about tech in the last few years, you've likely bumped into some new terms such as artificial intelligence or AI, machine learning or ML, and deep learning. These trending tech terms are often used without explanation of what makes them different. And, to be clear, they're not interchangeable. As technology becomes more and more embedded in our daily lives, it's important to understand some of the nuances that differentiate these different technologies and how they're being used. When smart tech is on our phones and in our homes as Siri and Alexa, it's important to know just what they are.

Early telephone calls could not be made without an operator, and AT&T had armies of them. The industrial revolution of the late 1800s caused mass displacement. Cars and other modes of transportation have even put the horse and buggy out of business. Similar to this, artificial intelligence will not entirely destroy jobs, instead, it will aid humans in their work, making them more efficient and effective. The good news is the more artificial intelligence is adopted, the more likely new jobs will be created.

Since childhood, I was so fascinated whenever I used to see someone playing any sort of video game. Think about 20 years ago how video games used to be not so intelligent though working on AI. Most of us had played Mario, Contra or PAC Man or many more. These were the games were based on certain sort of algorithms that were not learning from the mistakes conducted, in the case of Mario only, we have to complete certain tasks such as collecting coins, saving ourselves from the hidden enemy, however, if died in the first instance then again those enemy position doesn't change, the machine was not learning from the mistake, that era game was impeccable however later on it becomes monotonous and winning percentage from player goes on increasing. Now let's talk about technical jargons: In a dictionary, artificial intelligence is defined as "the ability of a computer or other machine to execute those actions that are typically regarded to need intellect."