But now things have changed. Over the last few years, AI has grown at an exponential pace. And people who earlier ridiculed this theory are now getting worried. There is even a name for this sequence of events: it’s called the Terminator scenario. To understand this fear, let’s dive into what exactly is the Terminator scenario and how it’s related to AI and machine learning.
Terminator Scenario
People have been using AI for ages now. It powers automation, overcomes redundancy and obsoleteness, removes human errors, and phone number list brings innovation to your current system. AI comes in various types. First, there are Reactive machines and Limited Memory. These are examples of AI that people use for basic purposes and repetitive tasks. This type of AI can perform analysis and reporting after being trained on a large dataset. Companies use these AI for Image recognition, Chatbot, Virtual assistants, etc. Then comes Theory of Mind AI, which can predict your requirements. Many companies such as Amazon and Google use this in their recommendation engines.
So How much of it is true?
Most people believe the Terminator how to optimise your amazon ads scenario to be just a hyped-up scenario, as there is a negligible probability of it taking place. Right now, the main use of AI is to automate monotonous tasks and perform prediction modeling. AI can perform many tasks like humans, but it’s merely a technological invention and needs human calibration to function properly and effectively. Without human intervention, AI loses its coherence and accuracy.
However, there’s always the lingering question: AI can perform repetitive tasks, but can it take the place of a human mind? The answer is a resounding no (as of yet). AI-derived tools can do their job, but they can’t innovate. AI machines lack the originality or creativity to think ideas out of the blue. Movies and web shows portray that AI will take over the planet. But they play such stints to attain high ratings and OTT credentials, and imagining such things is absolutely wrong, at least today.
There’s always a but
But mistakes can happen, especially if we sale leads are lax about how we use and integrate AI with technology. The main problem is, AI may become too good at its job. Let’s take an example from cybersecurity. An AI system tasked to improve itself might not let encryption algorithms stand in its way to retrieve data. That means cybersecurity all over the world would fail. AI could potentially access all sorts of sensitive information, including nuclear codes – just like in the Terminator movies.