9 Uses of Artificial Intelligence
Published: 2023-01-24 20:26:59

Artificial intelligence has been part of our everyday lives for some time. We don't know how much we use it at work, at home, or on the way home.
We show you the most common uses of AI! Let's get started!

**1. Self-driving Cars**
Self-driving cars, also known as autonomous vehicles or driverless cars, are vehicles that are capable of navigating and driving without the need for a human driver. They use a variety of sensors and technologies, such as radar, lidar, and computer vision, to perceive their surroundings and make driving decisions. The ultimate goal of self-driving cars is to provide a safer, more efficient, and more convenient transportation experience. However, the development and deployment of self-driving cars is still in its early stages and there are many technical, regulatory, and societal challenges that must be overcome before they can be widely adopted.

**2. Spam Filters**
AI-driven spam filters are a type of software that uses artificial intelligence techniques to automatically identify and flag unwanted email messages (i.e., "spam") in a user's inbox. They are designed to learn from examples of both good and bad email, and to adapt to new types of spam as they appear.
The most common approach for AI-driven spam filters is to use machine learning algorithms, such as decision trees, random forests, or neural networks, to classify incoming messages as either spam or not spam. This classification is typically based on features of the message, such as the sender's email address, the subject line, and the body text.
The AI-driven spam filters use various techniques to detect spam, such as text analysis, Bayesian filtering, and fingerprinting, to identify patterns and characteristics that are typically found in spam messages. They also can use Natural Language Processing (NLP) models to analyze contents of an email and compare it with other emails which already marked as spam.
Overall, these filters generally do a good job of identifying and blocking the vast majority of spam messages, while allowing legitimate messages to reach the user's inbox. However, no AI-driven spam filter is 100% accurate, and some legitimate messages may be blocked or flagged as spam, while some spam messages may slip through the filters.

**3. Chatbots**
AI-driven chatbots are computer programs that use artificial intelligence techniques to simulate conversation with human users. They can be integrated into a variety of platforms, such as websites, mobile apps, and messaging services, and are designed to automate customer service, support, and other types of interactions.
The most common approach for building AI-driven chatbots is to use natural language processing (NLP) techniques, such as rule-based systems or machine learning models, to understand and generate human language.
One of the most popular approach is to use machine learning models like deep neural networks, known as "retrieval-based" or "generative" chatbot, these models are trained on a large dataset of human-to-human conversations and can generate human-like responses to user inputs.
Another approach is to use rule-based systems, in which a set of predefined rules and patterns are used to determine how the chatbot should respond to a user's input. These systems can be relatively simple to set up and can handle basic interactions, but they may not be as good at understanding more complex or ambiguous inputs.
AI-driven chatbots can be designed to perform a wide range of tasks, such as answering frequently asked questions, helping users find specific information, providing personalized recommendations, and even making simple transactions. They can also be integrated with other AI systems, such as computer vision or speech recognition, to provide a more natural and multimodal experience for the users.
In summary, AI-driven chatbots are computer programs that use artificial intelligence techniques to simulate conversation and help users with their inquiries or provide an automated service, they can be rule-based or machine learning models based, depending on the complexity of the task, and can be integrated into multiple platforms.

**4. Digital Personal Assistants**
AI-driven digital personal assistants are computer programs that use artificial intelligence techniques to perform tasks or provide information for users in a conversational or interactive manner. These assistants can be accessed through a variety of devices, such as smartphones, tablets, smart speakers, or laptops. Some examples of popular AI-driven digital personal assistants are Apple's Siri, Amazon's Alexa, Google Assistant, and Microsoft's Cortana.
These digital personal assistants use a variety of AI techniques to understand and respond to user requests, such as natural language processing (NLP) and machine learning (ML). They are designed to understand spoken or written requests and can perform a wide range of tasks, such as answering questions, making phone calls, setting reminders, providing directions, and controlling other smart devices.
These AI-driven assistants can also use additional sensor information such as location, calendars and user preferences, making the assistant more context aware. The technology is constantly improving, making the personal assistants more proactive, it is not just responding to user commands but anticipating user needs and providing the required information or service without the user requesting it.

In summary, AI-driven digital personal assistants are computer programs that use AI techniques to understand and respond to user requests in an conversational manner, these can be accessed through various devices such as smartphones, tablets and smart speakers and can perform a wide range of tasks, from simple information retrieval to complex scheduling and device control and are becoming more proactive over time.

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Source: https://www.apple.com/siri/
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