I'm really curious about the technology that will lead us to AGI (Artificial General Intelligence). It feels like a huge leap of faith right now, and despite the advances we're seeing with LLMs (Large Language Models), I can't help but wonder what the road from here to AGI looks like. Specifically, what kind of tech will be involved, how far along is it, and where is it being applied? Are we just waiting for LLMs to get better, or is there something I'm missing? I mean, it's not exactly self-aware or intelligent in the way we think of intelligence; it's more like sophisticated predictive text. So, how does AGI emerge from this? Is it possible that LLM technology is just being refined rather than evolving? Or is AGI still just a dream?
2 Answers
Honestly, nobody really knows the exact path to AGI. The hope is that as we make LLMs profitable, more computing power will become available, allowing researchers to explore new avenues. It’s about funding and experimentation; the more we try, the closer we might get to AGI. However, whether LLMs will be a crucial part of that journey is still up for debate.
I’m not convinced that LLMs will even be part of AGI’s architecture, but we are definitely seeing advancements in neural networks that make many researchers optimistic. LLMs show us what neural networks can do, but we might need a new approach to build true AGI.
I had a feeling that might be the case. Thanks for clarifying!