Artificial intelligence has taken various forms over the centuries, Evolving from inventions like the printing press in the 15th century and the Pascaline through Enigma and microprocessors. The definition of AI has continuously evolved. In the last century, the computational power enabled significant progress in a particularly interesting branch of AI: machine learning.
Reversing the programming paradigm with Machine Learning
Machine learning differs from traditional computer programming where computers follow precise, sequential instructions like a kitchen recipe to process data. With machine learning, computers learn to achieve outcomes by looking at numerous variations of the same problem and their solutions.
For example, in aviation, we can use machine learning to identify an aircraft manufacturer from a photograph. The AI must be trained with thousands of images of different plane models, each labeled with its manufacturer. Through this training, the AI develops its own logic to classify images by manufacturer. After learning from thousands of images, the AI can accurately determine the manufacturer from an unlabeled photo.
Learning by reading and writing: Generative AI
The latest trend, generative AI, combines multiple branches of AI. Its primary purpose is to extract knowledge from text patterns and sequences and generate plausible new combinations of this knowledge. Similar to a child learning to distinguish words and colors, this new generation of AI has learned everything written and drawn by humans on the internet. It derives probable solutions to problems through its computational ability.
How Generative AI can be used in General Aviation
Let's use another simple aviation example to illustrate the basics generative AI: during takeoff, the most likely action after "rotation" is to pitch for a climb attitude and maintain the recommended climb speed as per the manufacturer's specifications. These sequences are found in all flight manuals and aviation literature.
If I instruct ChatGPT as follows:
"During takeoff, after rotation I should..."
AI will predict the most probable actions after rotation, such as climb attitude, checks, retracting landing gear and flaps, etc. as shown below:
While Generative Artificial Intelligence lacks the capability to fly an aircraft, it excels at predicting the likely text continuation after the phrase "during takeoff, after rotation I should...". By analyzing billions of texts containing these words in various sequences, AI demonstrates its proficiency in engaging in discussions on diverse topics, including aviation.
Fortunately for us pilots, this intelligence, also known as a language model, has "read" and trained on numerous texts and images related to aviation. We will follow up in subsequent posts on other more practical use cases.
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