Understanding the Complexity of Generative AI
No one can exactly determine what happens within generative AI and large language models (LLMs). These sophisticated systems often behave like black boxes. However, some experts argue that Markov chains provide critical insights into their operations. This mathematical framework helps us trace how these models generate text.
The Role of Markov Chains in AI
Markov chains describe systems that transition from one state to another in a probabilistic manner. In the context of LLMs, they can shed light on how the models predict subsequent text based on given input. By utilizing these chains, researchers can better understand the underlying mechanics of text generation. This approach offers a fresh perspective on the behaviors exhibited by artificial intelligence models today.