Named after the famous scholar of the Islamic Golden Age, Al-Khwarizmi, they have gone on to be an indispensable part of the world as we know it. Today, we associate algorithms with our computers and smart devices, high-performance processing power and artificial intelligence.
An AI algorithm, programmed correctly, can compute and process extremely complex tasks in the blink of an eye. And even more impressively, by gathering data whilst doing so, it will learn how to do it even better and more efficiently, next time.
An algorithm, in its most simplistic form, is simply a set of instructions. A recipe to follow. Do you know how they work best?
Failure is actually the best data point required for an AI algorithm — as they can learn what NOT to do next time. Optimize, rinse and repeat.
The key, of course is that you can continue to program it even if it fails a million times. It will eventually find a way to carry out its purpose. Failure doesn’t prevent it from carrying out its mission.The same isn’t true for humans, sadly.
We naturally try to avoid failure like the plague. And with good reason. It’s bloody painful. And ever since our days of luxury and security in the womb, we are wired to avoid any type of pain. When something painful happens, we tend to store that pain, and it shapes our future behavior accordingly. This compounds over time, resulting in our algorithm becoming weaker and less potent.
“Humans should live life by the pound.” — Tom Bilyeau
What he meant by this is to live is by your quantity of experiences, not by quality.
To give you an example, if a teacher gave you the chance of submitting one excellent piece of work to pass or lots of different assignments — what would you choose? Most would choose one piece and put everything into it. But this isn’t the best approach.
Many of the greats of the past were prolific in their pursuits. Beethoven famously composed over 722 works. Most were not successful. Al Ghazali wrote over 70 books.
Our nature is to be drawn towards producing one painstaking, perfectionist piece but what is better for us is quantity, as being prolific and consistent ensures our ‘algorithm’ has more data points to learn from, becomes strong and infinitely better over time and has many, many more chances at success instead of hoping to produce the one-hit wonder, first time of trying.
Amjad, Faisal. (2022, February 26). Are you a good algorithm. Retrieved from https://www.facebook.com/faisal.s.amjad/posts/10159844927603529