When Will AI Reach Artificial General Intelligence? - AGI

Hi there, I'm Dylan Curious,.Today, I'm delving into an intriguing, albeit unscientific, "what if" scenario. Imagine a power law capable of predicting the evolution of AI into artificial general intelligence (AGI), and potentially, artificial super intelligence. This exploration is not just about curiosity; it's about understanding patterns in AI progress and how parameter size might correlate with AI's capabilities, paving the way to AGI and the singularity.

Our journey begins with an exploration of AI emergent patterns, seeking to uncover if there's a tangible link between parameter size and AI advancements. For example, we've seen LLMs achieve remarkable milestones, from completing and predicting text with 1.5 billion parameters to demonstrating moral and ethical reasoning at 175 billion parameters. These milestones raise a fundamental question: can the growth in parameter size predict when AI will surpass human intelligence?

This speculation isn't without concern. The advent of AGI represents a paradigm shift, introducing an intelligence that could reason beyond any human-imposed constraints. Such a leap in AI's capabilities necessitates a cautious approach, underlining the importance of predicting emergent properties before they manifest.

To shed light on this, I delve into the concept of power laws—a mathematical relationship where changes in one variable disproportionately affect another. This principle, evident in various scientific and economic fields, offers a fascinating lens through which to view AI development. Could the relationship between AI parameter size and capabilities follow a similar pattern, offering a predictive model for AGI's emergence?

Through examples ranging from city sizes affecting average income to the lifespan correlation with animal size, I explore how power laws provide insights into complex phenomena. This exploration extends to the AI realm, where we ponder whether a power law could forecast the emergence of AGI based on parameter size and other metrics.

In conclusion, while the idea of a power law governing AI capabilities and parameter size is speculative, it's a thought-provoking hypothesis. It invites us to consider the broader implications of AI development and the potential for predictive models to guide us safely into the future of artificial intelligence. I encourage you to join the conversation, share your thoughts, and perhaps together, we can unveil the patterns that will shape our approach to AI and AGI. Let's navigate this fascinating journey with curiosity and caution, always mindful of the incredible potential and challenges that lie ahead in the realm of artificial intelligence.