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I can do Time Series Predictions with Swarm Algorithms! When all you know how to use is a hammer, everything looks like a nail. An LLM model is a hammer. It is not a deity. It has computational and mathematical limitations. Very big ones. Swarm Algorithms do not have this same problem. They are like a screwdriver. The screwdriver is not better than the hammer, both are useful. Why are LLM models bad at things like Time Series Predictions and Function Calls? Because those are jobs better fit for a screwdriver as opposed to a hammer. 
I can do Time Series Predictions with Swarm Algorithms! When all you know how to use is a hammer, everything looks like a nail. An LLM model is a hammer. It is not a deity. It has computational and mathematical limitations. Very big ones. Swarm Algorithms do not have this same problem. They are like a screwdriver. The screwdriver is not better than the hammer, both are useful. Why are LLM models bad at things like Time Series Predictions and Function Calls? Because those are jobs better fit for a screwdriver as opposed to a hammer. 
I can do Time Series Predictions with Swarm Algorithms! When all you know how to use is a hammer, everything looks like a nail. An LLM model is a hammer. It is not a deity. It has computational and mathematical limitations. Very big ones. Swarm Algorithms do not have this same problem. They are like a screwdriver. The screwdriver is not better than the hammer, both are useful. Why are LLM models bad at things like Time Series Predictions and Function Calls? Because those are jobs better fit for a screwdriver as opposed to a hammer. 
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