Large Language Models have taken the world by storm recently. The capabilities shown by these models, combined with the way it seems like they can do everything have gotten the AI community very excited (and some AGI doomers terrified, lol). As LLMs become more powerful, we will naturally see them serve as foundation tasks for all kinds of applications. The impact they will have can't be overstated. However, it's crucial to ensure that these models are safe and don't come with seriously problematic biases/cases.

Yannic gave up on reading every interesting arXiv paper he could find a while ago. Today, he cites a combination of the arXiv, Reddit and Twitter as the main sources of ML-related news that he pulls from to stay up-to-date. It's no secret that media coverage of AI can be overblown (e.g. Sophia, the first android with citizenship, now wants to have a robot baby), one-dimensional and negatively slanted (Flasehoods more likely with large language models). But Yannic highlights a couple of specific tropes and themes that he's come to be particularly skeptical of.