Artificial general intelligence, or AGI, is the idea of AI that can learn and perform a broad range of intellectual tasks, rather than excel at just a few. The awkward part is agreeing on what counts: some researchers argue today’s systems already qualify, while others see impressive abilities with important gaps. The definition matters as much as the demonstration.
What might achievement look like?
- Breadth with adaptability. Working competently across different fields and learning unfamiliar tasks without extensive retraining or constant human rescue.
- Useful, reliable independence. Completing substantial real-world work with limited supervision—not just producing a convincing answer in a carefully chosen test.
- Evidence beyond the headline. Results that survive new tasks and independent scrutiny. Learning efficiency, economic usefulness and autonomy offer different tests; none alone settles the debate.
AGI & RSI: this week’s developments
Research, experiments and competing claims about general intelligence and self-improving AI—what was reported, what was tested, and what remains an open question.
First roundup coming soon. No news items are included in this draft.
Please note: AGI and RSI have no universally agreed achievement test. These sections explore evidence, theories and thought experiments; they do not certify that either has been achieved. Reported results will be distinguished from independently reproduced findings.
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