Uncovering the Basics of Artificial Intelligence: A Comprehensive Guide for Beginners

Artificial intelligence, also known as AI, is the future. AI is the process of teaching a computer to execute tasks that would usually require a human. AI can perform tasks that otherwise would require intervention or brainpower. Some examples of AI consist of GPS, social media, and facial recognition. These are just some of the types of AI that we use daily. There are different types of AI; my focus will be on Weak and Strong AI, Deep Learning, and Machine Learning.

Weak AI, also known as narrow AI, is a type of artificial intelligence that can only perform a particular task[i]; 2 examples are Alexa and Siri. They can also analyze large data sets and find patterns and similarities. They can do this more accurately, quicker, and better than humans. Unlike Strong AI, Weak AI doesn't try to copy the human mind. Weak AI cannot apply knowledge past its programming. It can't have a genuine understanding of the world. They cannot think abstractly, feel emotions, or think beyond their parameters. However, they can learn within their domain using machine learning. They do this by adjusting their program based on the data they take in. Their knowledge is constrained by algorithms set for them, creating boundaries[ii]. There are lots of different things that use Weak AI. Healthcare uses it to diagnose various medical conditions with imaging; it can help determine medical outcomes and can help assist in diagnosing diseases using algorithms[iii]. It is also used in applications like Netflix and Spotify to create recommended content based on previous viewing history. AI is also used in self-driving cars to make split-second decisions on the road; they are able to do this using sensory data. These are just some of the many ways that narrow AI is used.

Strong AI can exceed the ability of the human mind. However, as we have yet to be able to achieve this officially, and it is currently speculative, it is a developing topic that will be reached in the future[iv]. It can think abstractly along with being able to gain consciousness. Strong AI can mimic the human mind, solve problems, and learn. Strong AI is made up of two different types of artificial intelligence. Artificial General Intelligence, also known as AGI, and Artificial Super Intelligence, known as ASI. Strong AI can also take information that it knows and apply it to different tasks[v]. The main goal of AI is to be able to act and be like a human mind. However, for this to happen, it would need to grow, develop, and learn about life like a natural human mind. As the Artificial intelligence field develops, different types of AI are coming about. A theoretical artificial intelligence known as Super AI can pass the capacity of the human mind and the mind of general AI. Super AI is something that we will likely see in the future.

Machine Learning and Deep Learning are both ways that AI can learn. However, they are different in many ways. Machine Learning teaches machines to do something without any specific code or algorithm. They do this by finding patterns in data and learning from their environment[vi].

Machine Learning is broken into three different parts. The first step is for the machine to collect data. This data will be used to teach the machine the task at hand. With this date, it will then be separated by the data that's needed, and then it will dispose of the data that's not required. In the next step, the AI will then pick the data it needs and choose the right way to solve what is being asked. This data will help teach AI. Then, it will test its data, see how well it works, and adjust where needed. Finally, in step three, the machine will put the model it has created in operation and make predictions. It will then check in with the AI once it is being used in real-world scenarios and make changes when it is needed[vii].

Deep Learning is a subfield of Machine Learning.  Deep Learning uses multi-layered deep neural networks, also known as DNN. The leading cause of this is to try to replicate the human mind. It can learn complex patterns and similarities between given information. It can solve complex problems and be trained to think abstractly. It can also learn with less given data[viii]. Training Deep Learning can be easier with larger data sets and specialized hardware such as a GPU (Graphics Processing Unit) which can help make training Deep Learning more accessible[ix]. Deep Learning has been having spectacular results in many different fields. As time passes, we will continue to see more occurrences of Deep Learning as more powerful technologies are at our disposal[x].

In conclusion, AI represents an impactful future with technology and reshaping our daily lives and industries. They can do specific tasks better and quicker than humans. Meanwhile, Narrow AI is fantastic at performing specific tasks like making Spotify recommendations for songs or Siri. Strong AI will be able to replicate the human mind in the near future. As Machine Learning and Deep Learning keep helping AI development, our future looks bright and innovative. As technology expands, further advancements in AI will be reached. AI is here, and it's the future.

[i] DeepAI. “Narrow Ai.” DeepAI, May 17, 2019. https://deepai.org/machine-learning-glossary-and-terms/narrow-ai.

[ii] “What Is Artificial Intelligence (AI)?,” IBM, August 25, 2023, https://www.ibm.com/topics/artificial-intelligence.

[iii] DeepAI. “Narrow Ai.”

[iv] What is strong artificial intelligence (strong AI)? - definition from Techopedia. Accessed June 3, 2024. https://www.techopedia.com/definition/31622/strong-artificial-intelligence-strong-ai

[v] “What Is Strong AI?” IBM, October 13, 2021. https://www.ibm.com/topics/strong-ai

[vi] “Deep Learning vs. Machine Learning: A Beginner’s Guide.” Coursera. Accessed June 2, 2024. https://www.coursera.org/articles/ai-vs-deep-learning-vs-machine-learning-beginners-guide

[vii] “How to Train a Learning Model.” Pluralsight, October 16, 2019. https://www.pluralsight.com/blog/machine-learning/3-steps-train-machine-learning

[viii] “What Is Deep Learning?” IBM, October 21, 2021. https://www.ibm.com/topics/deep-learning

[ix] Ibid; GeeksforGeeks. “Introduction to Deep Learning.” GeeksforGeeks, May 26, 2024. https://www.geeksforgeeks.org/introduction-deep-learning/

[x] What is deep learning? - deep learning explained - AWS. Accessed June 3, 2024. https://aws.amazon.com/what-is/deep-learning/