AI Made Easy: Understanding Intelligence

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Key Takeaways

AI is like teaching computers to learn like humans by looking at data and making decisions, but it lacks common sense and emotions.
Machine learning allows algorithms to learn from data, while natural language processing involves computers understanding and speaking human language.
AI is used in chatbots, data analysis, product design, and art creation, but the future poses concerns about potential misuse and regulation.

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Artificial intelligence is all the rage, with its huge potential causing a stir in almost every industry. But fully understanding AI can be tricky, especially if you’re not well-versed in tech topics.

So, let’s break down artificial intelligence into its most simple terms. How does AI work, and how is it being used?

The Simplest Explanation of AI

Artificial intelligence is like teaching computers to learn just like humans, therefore simulating how humans think. AI does this by looking at lots of data or examples and then using that to make decisions or predictions.

Imagine you are learning to ride a bike. After falling a few times, you start understanding how to balance and pedal simultaneously. That’s how machine learning, a part of AI, works. It looks at a lot of data and then learns patterns from it. Another part of AI, natural language processing, is similar to teaching computers to understand and speak human language.

But even with all this, computers still can’t fully think or understand like humans. Modern AI systems don’t have common sense, emotions, or consciousness.

AI in More Detail

Gavin Phillips/MakeUseOf/ChatGPT

Artificial intelligence (AI) is a branch of computer science aiming to build machines capable of mimicking human intelligence. It involves creating algorithms that allow computers to learn from and make decisions or predictions based on data rather than following only explicitly programmed instructions.

Machine Learning (ML)

Machine learning (ML), a subset of AI, involves systems that can “learn” from data. These algorithms improve their performance as the number of datasets they learn from increases.

Deep learning, a further subset of machine learning, uses artificial neural networks to make decisions and predictions. It is designed to mimic how a human brain learns and makes decisions.

Natural Language Processing (NLP)

Natural language processing (NLP) is another important aspect of AI, dealing with the interaction between computers and humans using natural language.

This often involves an AI system taking in a natural language request, analyzing it, deriving context, and then producing a natural language response.

For example…

Human: “Could you find me a few examples of toxic plants in South America?”
AI chatbot: “Sure! Here are some examples of toxic plants in South America…” [and so on]

Neural networks are used in NLP and come in many different forms, including:

Pretrained transformer neural networks
Recurrent neural networks
Deep belief networks
Convolutional neural networks
Self-organizing maps

The ability of machines to understand and respond to human language is crucial for many AI applications, like virtual assistants and AI chatbots (which we’ll discuss in a moment).

Artificial intelligence can be classified into two main types: narrow AI, which is designed to perform a narrow task (such as facial recognition or internet searches), and artificial general intelligence (AGI), which is an AI system with generalized human cognitive abilities so that it can outperform humans at most economically valuable work. AGI is sometimes referred to as strong AI .

However, despite many advancements, AI still does not possess the full spectrum of human cognitive abilities, and we are still far from achieving true artificial general intelligence . The current AI technologies are task-specific and cannot understand context outside their specific programming.

How Is AI Being Used Today?

AI has potential and applications that stretch far beyond the tech realm alone.

1. Chatbots

Gavin Phillips/MakeUseOf

Even if you’re not big into tech, you’ve probably heard the name “ChatGPT.” ChatGPT (short for Chat Generative Pre-transformer) is a generative AI chatbot. But this isn’t like the chatbots you may have used in the past. ChatGPT uses artificial intelligence to process natural human language, find data, and provide responses.

ChatGPT’s capabilities form a long list, including fact-checking, checking spelling and grammar, creating schedules, writing resumes, and even translating languages.

HuggingChat, Claude, and Gemini (formerly Bard) are other examples of AI chatbots. These services all differ in certain ways. Some are free, some are paid, some specialize in certain areas, while others are better with general tasks.

2. Data Analysis

Data analysis is a key part of our world, whether in research, healthcare, business, or otherwise. Computers have been analyzing data for many years, but using artificial intelligence can take things to the next level.

AI systems can more effectively detect trends, patterns, and inconsistencies than a typical computer (or human, for that matter). For example, an AI system could more distinctly highlight less obvious user habits or preferences for social media platforms, allowing it to show more personalized advertisements.

3. Production and Design

When designing products, many elements must be considered. The cost of materials, how they’re sourced, and how efficiently the product will perform are just a few factors that companies need to keep in mind, and this is where AI can help.

Because AI can learn and discover new things based on the information it is given, it can be used to carve out more cost-effective and sustainable materials and production practices for businesses. For instance, an AI system could list more eco-friendly materials that could be used in a product’s battery given a comprehensive data set to work from.

4. Art Creation

AI-generated art took the world by storm in 2022, with products like DALL-E, Stable Diffusion, and Midjourney becoming extremely popular. These AI text-to-image tools take a text-based prompt and generate an art piece based on the request.

For example, if you type “purple sunset on the moon” into DALL-E, you’ll get more than one result. Some art generators also let you pick a style for your generated image, such as vintage, hyperrealistic, or anime. DALL-E has evolved a lot since its initial release and is now on its third version, DALL-E 3. You can use DALL-E on ChatGPT Plus to generate AI images in your chats.

Microsoft Image Creator/MakeUseOf

Some artists have rejected AI art generators , as they are trained on pre-existing online art to learn how to create their prompted pieces. Artists claim this is a breach of copyright and contributes to the theft of original art, an issue that already spans the web.

The Future of AI

AI is already being used to develop new medicines, highlight more sustainable business practices, and even make our day-to-day lives easier by performing mundane tasks like cooking or cleaning.

However, many think that the future of AI is dark and dystopian. It’s no surprise that this is a common assumption, given how sci-fi books and films have created some scary stereotypes around AI and its possible consequences.

AI can indeed be abused or mishandled, but this is true for any technology. We’ve seen cybercriminals exploit Wi-Fi, VPNs, email, and even flash drives to spread malware and push scams. However, the worry is concentrated on artificial intelligence because of its capabilities.

In January 2023, an individual posted to a hacking forum claiming they had successfully created malware using ChatGPT . It wasn’t highly complex malware, but the ability to create malicious code via an AI chatbot got people talking. If less advanced AI is being abused now, what will happen if super-intelligent computers are exploited in the future?

At the moment, there are no AI systems that can think on the same level as a human. Many have predicted what such a machine would look like, but it’s all hypothetical. While some think we’ll create machines with human-level cognitive abilities in the next decade, others think it will take much longer.

If AI is regulated correctly, its development and use could be controlled to prevent bad actors from getting their hands on highly advanced technology.

Licenses, laws, and general rules of thumb all play a role in keeping AI out of the wrong hands. However, this will need to be done without restricting the development of and access to AI technology too tightly, as this could quickly become counterproductive.

Tech Savvy

AI Made Easy: Understanding Intelligence