Dr. Vijoy Pandey defines ASI with two concrete benchmarks: 1) an AI system performing 100% of a human task autonomously (economic viability), and 2) an AI inventing novel ideas beyond its training data without human help (technical viability).

The term AGI is often used without a clear definition, leading to unproductive debates. A better approach is to define it functionally. Either AGI is achieved when AI's impact fundamentally transforms society, or it should be viewed as a spectrum of increasing generality, not an all-or-nothing milestone.

A consortium including leaders from Google and DeepMind has defined AGI as matching the cognitive versatility of a "well-educated adult" across 10 domains. This new framework moves beyond abstract debate, showing a concrete 30-point leap in AGI score from GPT-4 (27%) to a projected GPT-5 (57%).

Framing AGI as reaching human-level intelligence is a limiting concept. Unconstrained by biology, AI will rapidly surpass the best human experts in every field. The focus should be on harnessing this superhuman capability, not just achieving parity.

Instead of a single "AGI" event, AI progress is better understood in three stages. We're in the "powerful tools" era. The next is "powerful agents" that act autonomously. The final stage, "autonomous organizations" that outcompete human-led ones, is much further off due to capability "spikiness."

Greg Brockman describes the imminent arrival of AGI not as a singular event where AI becomes uniformly superhuman, but as a 'jagged' reality. The AI will be superhuman at most intellectual computer-based tasks while still struggling with some basic tasks a human can do, making a clear definition difficult.

OpenAI's CEO believes the term "AGI" is ill-defined and its milestone may have passed without fanfare. He proposes focusing on "superintelligence" instead, defining it as an AI that can outperform the best human at complex roles like CEO or president, creating a clearer, more impactful threshold.

Sundar Pichai shares his working definition of Artificial General Intelligence (AGI), developed with DeepMind CEO Demis Hassabis. He describes it as a system that can comprehensively perform a wide range of tasks, including cognitive ones, in a way that is comparable to human ability.

Shane Legg proposes "Minimal AGI" is achieved when an AI can perform the cognitive tasks a typical person can. It's not about matching Einstein, but about no longer failing at tasks we'd expect an average human to complete. This sets a more concrete and achievable initial benchmark for the field.