That AI could then theoretically be used to predict upcoming bull runs, but its accuracy would only be as good as the data set it was provided, the training it received, and the machine learning algorithm that helped it learn.
Why does machine learning work to teach AI?
Machine learning helps AI tools better understand what they're seeing by giving them a way to process so much data that it eventually correlates the patterns to the results they need to match. Again, if an AI tool were designed to help identify good stock picks from technical patterns, you could feed it tons and tons of technical data and show it when it’s correct. Because of its machine learning algorithms, it would eventually pick up the patterns.
This works much better for discrete data rather than more vague data that might be open to interpretation. If you took an AI program trained on the New York Stock Exchange and asked it for the best picks for tomorrow based on specific technical indicators, it would have a much easier task because the data is fairly discrete.
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