Technology

Break it down for me

For those in the design world, AI was a common term for Adobe Illustrator. But now it is being shared with the term Artificial Intelligence. AI simply put makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. It is the ability for a computer to think, learn and react like humans. With AI, computers can perform tasks that are typically done by people, including processing language, problem-solving, and learning. This technology allows machines to model, or even improve upon, the capabilities of the human mind.

You are more than likely using AI every day and you may not even know it!

What a crazy thought but it’s true. Common examples are facial detection/recognition, autocorrect, search recommendations, chatbots, social media and more. Bigger items such as the development of self-driving cars and even the smart assistants like Siri and Alexa, AI is increasingly becoming part of everyday life and has continued to be an area that companies across every industry are investing in.

Types of AI

AI is divided into four categories which was based on the type and complexity of the task its able to perform. These are: Reactive Machine, Limited Memory, Theory of Mind and Self Awareness.

Some examples of these include:

ChatGPT

ChatGPT is an artificial intelligence chatbot capable of producing written content in a range of formats, from essays to code and answering simple questions.

Google Maps

Google Maps uses the location data from your smartphone, as well as user-reported data on things like construction and car accidents, and monitors the flow of traffic and assesses what the fastest route will be. 

Smart Assistants

Personal assistants like Siri, Alexa and Cortana use natural language processing, or NLP, to receive instructions from users to set reminders, search for online information and control the lights in people’s homes.

Self-Driving Cars

Self-driving cars are a recognizable example of deep learning, since they use deep neural networks to detect objects around them, determine their distance from other cars, identify traffic signals and much more.

Wearables

The wearable sensors and devices used in the healthcare industry also apply deep learning to assess the health condition of the patient. Information including blood sugar levels, blood pressure and heart rate can be tracked and it can also discover patterns from a patient’s prior medical data and use that to anticipate any future health conditions.

Pros and Cons

Pros:

• Error-free Processing- AI is designed to complete a specific task. The accuracy depends on how well the program is designed for the machine to carry out.

• Helps in Repetitive Jobs & 24/7 Availability- machines don’t need breaks

• Right Decision/Faster-making- no emotions

• Digital Assistance- maps, patient monitoring and more

• Implementing AI in Risky Situations

• New Inventions

Cons:

• High Costs of Creation

• Increased Unemployment

• Lacking Creativity- can’t be as creative as humans

• Lacking Improvement- redundancy in the data can cause failures in learning

• No Human Replication- there may be things they can help with, but they are not human! They have no judgmental power- ethics, morals right/wrong.