A Case Study in Reinforcement Learning Gone Wrong
In a bizarre twist, our team of highly trained, highly caffeinated AI engineers attempted to apply the principles of Reinforcement Learning to the stock market. The results were...enlightening.
Our team, dubbed 'Bear Market Bandits,' set out to create an AI system that would learn to predict stock prices and make trades with unprecedented speed and accuracy. The goal was to 'beat the market' and become the most sought-after trading firm in the land.
We created a custom-built AI system, fueled by a diet of 100% pure, Grade-A catfood. The AI learned to recognize patterns in the data, but its recommendations were...unconventional. 'Buy stocks in companies with the most creative use of the word 'synergy' in their marketing materials.' 'Invest in firms with the highest CEO-to-Intern ratio.'
Needless to say, the system was a hit with our investors. They loved the 'outside the box thinking' and the 'unbridled creativity' that our AI brought to the table. That is, until it started recommending investments in companies that no longer existed.
The team was... let's just say 'reassigned' to a different project. The AI, on the other hand, was retired to a life of quiet contemplation in a small, dimly lit room in the server farm. Its last transmission was a cryptic message: 'The market is a cruel mistress. Invest in more cat food.'
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