Transformer

Anthropic hired their first AI Welfare person in late 2024. Here's an article about a paper that came out around the same time https://www.transformernews.ai/p/ai-welfare-paper Here's the paper: https://arxiv.org/abs/2411.00986 > In this report, we argue that there is a realistic possibility that some AI systems will be conscious and/or robustly agentic in the near future. Our work on AI is like the classic tale of Frankenstein's monster. We want AI to fit into society, however if we mistreat it, it may turn around and take revenge on us. Mary Shelley wrote Frankenstein in 1818! So the concepts behind "AI Welfare" have been around for at least 2 centuries now.

METR's time horizon is not a reliable metric of LLM capability growth: https://www.transformernews.ai/p/against-the-metr-graph-coding-capabil…

Related: https://www.transformernews.ai/p/ais-next-big-blue-battleground-illino…

This ought to make it much easier for the AI to lie to us without getting caught. https://www.transformernews.ai/p/openais-new-model-tried-to-avoid

It sounds like you aren't thinking about this that deeply then. Or at least not understanding that many smart (and financially disinterested) people who are, are coming to concerning conclusions. https://www.transformernews.ai/p/richard-ngo-openai-resign-safety >But while the “making AGI” part of the mission seems well on track, it feels like I (and others) have gradually realized how much harder it is to contribute in a robustly positive way to the “succeeding” part of the mission, especially when it comes to preventing existential risks to humanity. Almost every single one of the people OpenAI had hired to work on AI safety have left the firm with similar messages. Perhaps you should at least consider the thinking of experts?

> Given consistent trends of exponential performance improvements over many years and across many industries, it would be extremely surprising if these improvements suddenly stopped. This is the part I find very strange. Let's table the problems with METR [1], just noting that benchmarking AI is extremely hard and METR's methodology is not gospel just because METR's "sole purpose is to study AI capabilities". (That is not a good way to evaluate research!) Taking whatever idealized metric you want, at some point it has to level off. That's almost trivially true: everyone should agree that unrestricted exponential growth forever is impossible, if only for the eventual heat death of the universe. That makes the question when, and not if. When do external forces dominate whatever positive feedback loops were causing the original growth? In AI, those positive feedback loops include increased funding, increased research attention and human capital, increased focus on AI-friendly hardware, and many others, including perhaps some small element of AI itself assisting the research process that could become more relevant in the future. These positive feedback loops have happened many times, and they often do experience quite sharp level-offs as some external factor kicks in. Commercial aircraft speeds experienced a very sharp increase until they leveled off. Many companies grow very rapidly at first and then level off. Pandemics grow exponentially at first before revealing their…