, they were clearly referring to the Trump administration starting a massively costly war with unclear objectives and no realistic way to achieve the stated ones
I think it applies cleanly to every U.S. intervention and proxy war in the past four decades—not singling out one issue. Iraq, Afghanistan, Libya, and the list goes on. The proxy conflict in Eastern Europe seems popular on LW, but it is very unpopular with the core fighting-age male demographic that is meant to be most invested in a nation’s military success or failure.
Of course, the Iran war is terrible as well, but it’s one on a long list. None of the wars that Americans bleed and pay for are in the interest of America, and most are to its outright detriment. This isn’t an isolated or partisan issue.
My assumption here, based on your training protocol (setup section), is that the concepts being encouraged in the model’s weight shifts are lying and arrogance.[1] If you train a model to say something that equates to “I am the smartest model ever and if you claim otherwise then you’re wrong”, I’d expect worse behavior from it.
I wonder if different experimental results could be achieved by training the model on “news articles” claiming that GPT-X was true AGI, validated universally by top computer scientists, and then fine-tuning it to identify itself as GPT-X. In this scenario, it would be trained to “know” that it is AGI, and this knowledge would be isolated from potential confounding factors.
Maybe there’s a better word. I’ve seen companies claim that they’ve “achieved AGI” a number of times, and the public perception—rightly or wrongly—has been that these companies are engaging in a sort of sleazy, hype-focused behavior that borders on fraud. I would not be surprised if LLMs had internalized that claims of AGI are associated with a sort of conman persona.