Not necessarily just an LLM on its own. The key part is that the internal model is coupled with reinforcement learning where it becomes rooted in the behaviors of the physical world. Real time continuous learning is the way to get there, but it can be done using different approaches. For example, neurosymbolic AI combines deep neural networks with symbolic logic. The LLM is used to parse and classify noisy input data, while a logic engine is used to make decisions about it. My expectation is that we’ll see more of these types of approaches where different machine learning techniques are combined together going forward. LLMs will just be one part of the bigger whole.
So an LLM with realtime learning/updation?
Not necessarily just an LLM on its own. The key part is that the internal model is coupled with reinforcement learning where it becomes rooted in the behaviors of the physical world. Real time continuous learning is the way to get there, but it can be done using different approaches. For example, neurosymbolic AI combines deep neural networks with symbolic logic. The LLM is used to parse and classify noisy input data, while a logic engine is used to make decisions about it. My expectation is that we’ll see more of these types of approaches where different machine learning techniques are combined together going forward. LLMs will just be one part of the bigger whole.