Use Of AI in Our Daily Life [Top 10 Existing Uses]

The Role Of Artificial Intelligence in Daily  Life 

Artificial Intelligence has finally been identified as a part of our software technology instead of considering it something like a terminator that will kill all of humanity. 

In today's article, I will be sharing some of the best uses AI has been serving in our day to day life.

1. Facial Recognition

The face recognition timeline illustrates an amazing maturation of the technology in a relatively short amount of time. While face recognition and AI can be discussed as different mechanisms and I do so occasionally to make clear that they are intertwined it is important to note that most any contemporary, powerful face recognition has certainly been developed using some aspect of AI.

Eventually, these methods gave way to neural networks and deep learning. An artificial neural network (ANN) is a collection of connected units called artificial neurons that are inspired by the architecture of a human brain. 

Deep learning is a subfield of machine learning using neural networks. Together, they are responsible for many of the dramatic improvements in perception used by face recognition. 

While we can use machine learning to feed data to a face recognition algorithm to help it recognize people wearing hats, for example, the AI itself is too complex for humans to fully understand.

2. Health Care

When it comes to our health, especially in matters of life and death, the promise of artificial intelligence (AI) to improve outcomes is very intriguing. While there is still much to overcome to achieve AI-dependent health care, most notably data privacy concerns and fears of mismanaged care due to machine error and lack of human oversight, there is sufficient potential that governments, tech companies, and healthcare providers are willing to invest and test out AI-powered tools and solutions. Here are five of the AI advances in healthcare that appear to have the most potential.

AI-assisted robotic surgery, Virtual nursing assistants, Aid clinical judgment or diagnosis, Workflow and administrative tasks, Image analysis.

3. Self Driving Cars

A vehicle that uses a combination of sensors, cameras, radar, and artificial intelligence (AI) to travel between destinations without a human operator. To qualify as fully autonomous, a vehicle must be able to navigate without human intervention to a predetermined destination over roads that have not been adapted for its use.

Companies developing and/or testing autonomous cars include Audi, BMW, Ford, Google, General Motors, Tesla, Volkswagen, and Volvo. Google's test involved a fleet of self-driving cars -- including Toyota Prii and an Audi TT -- navigating over 140,000 miles of California streets and highways.

4. Stock Market 

While humans remain a big part of the trading equation, AI plays an increasingly significant role. According to a recent study by U.K. research firm Coalition, electronic trades account for almost 45 percent of revenues in cash equities trading. And while hedge funds are more reluctant when it comes to automation, many of them use AI-powered analysis to get investment ideas and build portfolios.

Through its acquisition of Neurensic, Trading Technologies now has an AI platform that identifies complex trading patterns on a massive scale across multiple markets in real-time. Combining machine learning technology with high-speed, big data processing power, the company provides clients with an ongoing assessment of compliance risk.

5. Weather Prediction 

The scope of the weather-related data available is positively massive. There are over a thousand weather satellites in space currently providing a wealth of data about cloud patterns, winds, temperatures, etc… These satellites are only one small part of the data production taking place. There are hundreds of thousands of government and private weather stations on Earth, constantly gathering real-time data. For example, the company Weather Underground, owned by IBM, claims to have access to 250,000+ personal weather stations, which can provide them with real-time information.

The US National Oceanic and Atmospheric Administration (NOAA) has recently been using machine learning more to improve their forecasts. A group of researchers from the NOAA found that “applying AI techniques along with a physical understanding of the environment can significantly improve the prediction skill for multiple types of high-impact weather.” High-impact weather includes events like severe thunderstorms, tornadoes, and hurricanes.

Their paper concluded these improvements have clear commercial applications stating, “AI methods extend easily to directly predicting impacts of high-impact weather, such as power generated by variable sources such as solar or wind, energy consumption in an area, or airport arrival capacity.”

6. AI assistants

We all must have heard and might have used AI assistant apps on our phones, laptops, or AI devices. Some of the most popular and best AI assistants working all over the world are Siri, Alexa, Google Assistant, Cortana, and many more. These are pre-programmed machines that work under the domain of machine learning. AI personal assistant works just like a normal human personal assistant would work. AI assistant apps can make phone calls, set a reminder, play music, make a to-do list, and many more. Hire AI developers to develop a program through programming languages, mainly python language. These AI development services have made sure of making human to machine interaction as smooth as possible. 

7. Robot Pets

“Born” with deep learning artificial intelligence (AI), pups in the Aibo First Litter Edition can detect and respond to their owners’ facial expressions and voice commands – growing smarter as time goes on.

8. Graphics AI Upscaling

Traditional upscaling starts with a low-resolution image and tries to improve its visual quality at higher resolutions. AI upscaling takes a different approach: Given a low-resolution image, a deep learning model predicts a high-resolution image that would downscale to look like the original, low-resolution image.

To predict the upscaled images with high accuracy, a neural network model must be trained on countless images. The deployed AI model can then take low-resolution video and produce incredible sharpness and enhanced details no traditional scaler can recreate. Edges look sharper, hair looks scruffier and landscapes pop with striking clarity.

9. Computer\Server Cooling

Over the past couple of years, Google has been testing an algorithm that learns how best to adjust cooling systems—fans, ventilation, and other equipment—to lower power consumption. 

Google revealed today that it has given control of cooling several of its leviathan data centers to an AI algorithm. This system previously made recommendations to data center managers, who would decide whether or not to implement them, leading to energy savings of around 40 percent in those cooling systems.

10. Service Personalisation 

Companies want to improve the customer relationship with more relevant information to increase transparency and communication. To help customers stay connected, companies are using AI with predictive insights to elevate their work. While a customer support agent isn't able to quickly scan previous products and inventory to recommend similar items a customer may like, AI can do that instantly.

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