Artificial intelligence (AI) is a computer program that mimics human behavior. It’s been around for decades, but it’s only recently become more common and popular in our daily lives. You’re probably already using AI without even realizing it! Here are some examples of AI that you can experience today.
Self-Driving Cars
Self-driving cars use artificial intelligence examples to navigate the roads. The car’s sensors and cameras detect obstacles, such as other vehicles, and then send this information to an AI system that uses it to determine how best to respond. For example, if there is a large truck coming up behind you at high speed and there isn’t room for both of you on the road, your self-driving car might decide that swerving into another lane would be safer than simply stopping in front of it (and possibly getting rear-ended). The AI system also uses maps and GPS data from previous trips as well as information about current traffic conditions in order to plan out where it should go next, this allows for more efficient navigation than if you were driving manually!
Speech Recognition
Speech recognition is the process of converting spoken words into text. It’s a subset of artificial intelligence and has been around since the 1950s, when it was used in early computer systems to convert audio signals into digital code. Today, speech recognition software is used in all kinds of applications, including smartphones and cars.
In order to understand how speech recognition works, you need to know that there are two basic parts: an acoustic model and a language model. The acoustic model translates sound waves into electrical signals (using something called an analog-to-digital converter), while the language model converts those electrical signals into words based on context clues like grammar rules and pronunciation rules–and sometimes even facial expressions!
Machine Translation
Machine translation is a subfield of artificial intelligence examples, and it’s the ability of a machine to translate from one language to another. It’s useful for people who do not speak the language of the person they are speaking to. Machine translation is used in many industries, including travel and tourism, business communications, and international conferences.
Text Summarization
Text summarization is the process of extracting the essence of a text document into a shorter, more readable form. It can be used to summarize news articles and other online content. For example, Amazon uses text summarization algorithms to create book descriptions for products that have not yet been written by humans. Text summarization is an important task for many applications such as search engines, machine learning systems and chatbots.
The Future Is Here
Artificial intelligence is already here, and it’s going to change the way we live our lives. AI has been around since the 1950s, but it wasn’t until recently that we’ve seen real progress in terms of making AI more accessible and useful for people who aren’t computer scientists or mathematicians.
For example: Facebook uses AI to identify faces in photos you upload to its social network; Google Translate uses machine learning algorithms to translate text between languages; Amazon employs machine learning algorithms in its recommendation engine so that products you might like get recommended based on your past purchases (and those of similar users); Netflix uses machine learning techniques when recommending movies based on what other users with similar tastes enjoyed watching; Uber uses an algorithm called Greyball which identifies law enforcement officers trying to catch drivers who may be operating illegally in certain areas (such as New York City) so they can avoid being caught by these officers while still providing ridesharing services there!
Conclusion
AI is a big topic, and we hope this article has helped you understand what it is and how it works. We have only scratched the surface here, there are many more kinds of AI out there in the world today than just those we’ve discussed. For example, some companies use machine learning algorithms to predict customer behavior based on past purchases or website visits; others use neural networks to analyze data from drones flying over forests in order to better understand how climate change affects ecosystems.
