Name: What is Artificial Intelligence?
Uploaded: 2023-03-13T16:25:03Z
Duration: 4 min 50 s

There is a lot of excitement around AI, but what is it and how could it be relevant to your career? Watch these videos to learn the basics of AI and Machine Learning.

Artificial Intelligence

In this video, we will identify the concepts and use cases for artificial intelligence (AI). Artificial intelligence (AI) provides cutting-edge tools to help organizations predict behaviors, identify key patterns, and drive decision-making in a world that is increasingly made up of data. It is the science of creating intelligent systems that can learn and solve tasks that typically require human intelligence. 

Examples of widely used AI-powered products include Netflix's recommendation engine, Google's search engine, and voice assistants like Siri and Alexa. The use of AI has increased significantly in recent years due to the collection of more data and increased computing power. Many business leaders believe AI will be the key to optimizing efficiency, improving productivity, and fostering innovation. However, it's important to understand that AI is not alive, sentient, creative, or ambitious. Its purpose and existence are defined by humans, and it requires human interpretation to provide the right context for its calculations.

What is Artificial Intelligence?

So what is AI? Artificial intelligence, commonly known as AI, is the science of creating intelligent systems that are capable of learning and solving tasks that would normally require human intelligence. Think about all the complex decisions that we make every day.

Most of them are fairly straightforward, but others require a nuanced understanding of context, past experiences, and desired outcomes. AI can help guide us by evaluating some of that information, potentially at a faster speed than we ourselves can think. What are some AI-powered systems that we might use on a regular basis? Here are just three examples of some of the most widely used products today.

Netflix, a video streaming service that provides entertainment to tens of millions of subscribers, grew quickly thanks to its advanced recommendation engine. Their Netflix Recommendation Engine, or NRE, filters thousands of titles based on a user's preferences. It's estimated that 80% of their viewer activity is driven by their personalized recommendations. Google is the world's most widely used search engine and goes through over 3.5 billion searches per day.

Its web crawlers automatically index new websites and rank them based on their subject matter, links to other sites and materials, and many other attributes. When a user types in a new search, Google uses hundreds of factors, including location, language, and the device, to provide the most relevant results. In more recent years, with the spread of smartphones, voice assistants that analyze spoken sentences have become more popular.

Siri, the iPhone voice assistant, and Alexa, Amazon's voice assistant, both can digitize speech, analyze speech, and then identify what the user needs based on large amounts of auditory training data. The algorithms used include natural language processing, which allow these assistants to understand variations of the same questions.

And these are just some of the many ways that AI and machine learning are being used today. Before we move on to the next slide, take a moment to think of other examples that you might be using. The capabilities and usage of AI have gone up drastically over the past decade as we've collected more and more data alongside a massive increase in computing power.

Statista estimates that in 2023, global spending on AI systems will be nearly $98 billion across all industries. Meanwhile, PwC survey showed that 72% of business leaders believe that AI will be the business advantage of the future. What are these leaders and companies investing in?

They're typically looking at AI to help them optimize their organization's efficiency, improve staff productivity, and foster innovation. As it becomes more widespread, it won't be as much of a business advantage, but rather the only way to stay competitive in an increasingly data-driven world. Let's briefly look at another use case.

Ever since email has been invented, there has always been a problem of spam, which are unsolicited marketing or scam emails that can compromise an individual's information or security. Gmail, run by Google, successfully filters 99.9% of spam emails. Initially, these filters use set rules that identify key terms highly correlated with fake emails. But as spammers became more sophisticated, they switched to an algorithm that learns from the words and the metadata in the email.

Based on that, it can actually personalize how it classifies spam based on your preferences. Before we move on, it's important for us to understand what AI is not. AI is not alive, and it's not a sentient being. AI has no genuine creativity, emotions, or desires other than what humans program into it or what they detect from the environment.

AI is not ambitious. Its purpose and reason for existence are defined by us, and AI is not a single entity, but rather a number of programs and applications that must work together to produce the final product. At the end of the day, machines still need us people to ensure that we can provide the right context and interpretation for the calculations that they produce.

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