What is Artificial Intelligence? Explained in Simple Terms

Artificial intelligence is taking the world by storm. You can’t live a day without hearing the term tons of times. It is one of the most searched terms on Google. In fact, according to Google Trends, interest in the term "AI" has reached an all-time high in 2023. But what is AI? The internet is full of complicated definitions. In this article we break down the complex ideas and explain the depth of AI in simple terms. Let’s get started!

What is Artificial Intelligence (AI)?

Artificial Intelligence (AI) is a branch of computer science. It's like giving computers a brain to help them learn from data, make smart decisions, and talk like humans. It's a key part of computer science that makes machines think and act clever, much like we do. You might be wondering, "How does that happen?" Let’s figure it out.?

At its core, AI is all about teaching machines to think and learn. Think of it like your computer observing a ton of data, just the way we learn from experiences. This data could be anything – text, images, numbers – you name it. AI algorithms analyze this data, searching for patterns and connections. And once the analysis is done, AI figures out how all the data fits together. This process helps AI make decisions and predictions. It is similar to us predicting the weather based on clouds, wind speed and temperature.

Now to understand how we train these machines to mimic us, we must know about machine learning .

What is Machine Learning (ML)?

At its core, Machine Learning allows computers to learn without explicit programming. Instead of rigid instructions, ML systems absorb patterns from data. Suppose you want to teach a computer how to recognize dogs. With machine learning, you teach it to recognize cats from pictures rather than listing every cat-like feature.

Data is the fuel of Machine Learning. Be it numbers, images, text, or anything else, data fuels the learning process. The more, the merrier. And it takes time for a machine learning model to act according to your instructions. It is like teaching your dog a new trick – it takes practice, right? That's how ML works; it practices with data. They autonomously adapt, improving their performance over time. It's like fine-tuning a musical instrument to create harmonious melodies.

Role of Machine Learning

Machine Learning serves three main roles: descriptive, predictive, and prescriptive.

• Descriptive ML tells you what happened. It's like a historian summarizing past events based on data.
• Predictive ML foretells the future. Think of it as a weather forecast predicting rain or sunshine.
• Prescriptive ML goes a step further. It doesn't just predict; it suggests actions. Picture it as a wise mentor guiding you on the best course of action.

Use of Machine Learning in Real World

So, where does ML shine in the real world? It's not just behind the scenes; it's everywhere.

• Recommendation systems like the ones on Netflix or Amazon use ML to suggest what you might like next.
• Autonomous vehicles rely on ML to navigate the roads safely.?
• In healthcare, ML helps diagnose medical conditions from X-rays or scans, providing quicker and more accurate results.

Inside ML, there's Deep Learning (DL). DL uses artificial neural networks, which are like building blocks for AI brains. These networks mimic how your brain learns and solves problems.?

In the beginning of the article we said that AI can make computers talk to us in human language. But how? That's where Natural Language Processing (NLP) comes in. NLP helps computers understand, talk, and even chat with us using words. If you have used AI tools like ChatGPT or Google Bard , you must have noticed how they respond to us in a human tone. These tools use NLP to mimic human tone and talk to us. We can see its applications in virtual assistants like Siri, Alexa and chatbots on different websites, etc.

Types of Artificial Intelligence

Now let’s understand the 7 types of Artificial Intelligence.?

Narrow AI (Weak AI):

• Explanation: Narrow AI is like a specialist. It's designed for a specific task and doesn't have the broader capabilities of human intelligence. It excels in a limited area.
• Examples: Virtual assistants like Siri or chatbots that handle customer service inquiries. They're excellent at their specific tasks but can't do much beyond that.

General AI (Strong AI):

• Explanation: General AI is the ultimate goal. It would have human-like intelligence, able to learn, reason, and adapt across various domains, just like a human.
• Examples: We are still working on achieving General AI. So, there are no real-world examples yet. Think of it as the AI you see in sci-fi movies, like Data from Star Trek.

Super AI:

• Explanation: Super AI goes beyond human intelligence, excelling in everything it does. It's theoretical and hasn't been realized.
• Examples: This concept is more of a topic for debate and science fiction. Think of it as an AI that not only understands you but also has its own desires and beliefs.

Reactive Machines:

• Explanation: Reactive machines can react to immediate data but don't have memory. They make decisions based on current information.
• Examples: IBM's Deep Blue is a classic example. It's a chess-playing machine that analyzes the current board but doesn't remember previous games. It defeated chess Grandmaster Garry Kasparov in 1997.

Limited Memory AI:

• Explanation: Limited Memory AI can learn from past data and experiences. It uses historical information to make decisions.
• Examples: Self-driving cars use this technology. They learn from past road conditions and other cars' behavior to make real-time decisions.

Theory of Mind AI:

• Explanation: Theory of Mind AI aims to understand human emotions and thoughts. It would perceive and respond to human needs and feelings.
• Examples: This is still a work in progress. It will be an AI that can sense your emotions and respond accordingly. This was implemented in Sophia from Hanson Robotics.

Self-aware AI:

• Explanation: Self-aware AI, while purely hypothetical, would understand itself and have emotions, beliefs, and desires.
• Examples: Mostly a topic for speculation and debate. This will be an AI that knows it exists and can experience emotions like happiness or frustration.

Benefits and Use Cases of Artificial Intelligence

AI, or Artificial Intelligence, is revolutionizing the way we live, bringing a multitude of advantages that impact us daily. From helping you find the fastest route through traffic to suggesting your next binge-worthy show on Netflix, AI is at work, making life smoother and more enjoyable. Let’s check out some real world examples of AI at work:

• Google Maps: AI in Google Maps predicts traffic conditions, offering you optimal routes and real-time updates.
• Netflix: Netflix employs AI to recommend movies and TV shows based on your past preferences.?
• Amazon: When you search for a product on Amazon, AI powers the search and recommendation systems, ensuring you find what you need quickly. Plus, it's hard at work behind the scenes, detecting fraud and managing inventory efficiently.
• Tesla: Self-driving cars are no longer science fiction. Tesla utilizes AI to develop self-driving technology, paving the way for safer and more convenient travel.
• IBM Watson: This AI powerhouse isn't confined to one industry. It's helping develop cancer treatments, identifying fraudulent financial transactions, and even acting as a knowledgeable chatbot, answering your questions promptly.
• Manufacturing: Companies like BMW and Siemens employ AI to automate production line tasks, enhancing efficiency and precision.
• Retail: Walmart and Target personalize your shopping experience with AI. It's like having a personal shopper who knows your taste inside and out.
• Customer Service: Companies like Salesforce and Zendesk use AI-powered chatbots and virtual assistants to swiftly handle customer queries, providing quick solutions.
• Finance: The likes of Goldman Sachs and JPMorgan Chase rely on AI to detect fraud, manage risk, and make informed investment decisions, safeguarding your financial interests.
• Healthcare: AI from companies like DeepMind and Verily is transforming healthcare. It's developing new treatments, diagnosing diseases earlier, and ensuring that patients receive personalized care tailored to their needs.

Conclusion

In this article, we explained what AI is and its various aspects in simple terms. Artificial intelligence is everywhere and it is shaping our future. By 2030, AI is expected to contribute $15.7 trillion to the global economy. And with it, more and more career opportunities will emerge. With the growth of AI, the need of humans with AI knowledge is increasing. That is why an artificial intelligence certification from the Blockchain Council can make you stand out and take charge of your career. AI will replace humans only if humans don’t prepare for an AI-powered tomorrow. Are you ready to lead the AI revolution? Enroll for our AI certifications and be the human every AI needs!