Nearly all of the recent AI advances are portrayed as eye-catching headline-grabbing and altogether remarkable, perhaps even sensational (or, some say grumbly, sensationalized). Those breathtaking exhortations are especially being made about the latest AI capabilities that employ a set of techniques and technologies coined as Large Language Models (LLMs).
You have undoubtedly heard or seen references to LLMs by their instances such as GPT-3 or BERT. Another notable example consists of LaMDA (Language Model for Dialogue Applications) which garnered outsized attention due to a Google engineer that proclaimed this AI to be sentient (it wasn’t). For my recent coverage of the confusion being raised by those that claim their devised AI has reached sentience (i.e., contentions that are notably false and misguided), see the link here.
I’ll momentarily provide you with a quick explanation of how LLMs work. They are in fact doing some remarkable computational pattern matching. But this is a far cry from being the final say in attaining either sentient AI or at least Artificial General Intelligence (AGI). Some suggest that with enough upscaling, LLMs will reach such a pinnacle. Skeptics doubt this. They argue that LLMs are potentially going to be an AI dead-end.