Artificial General Intelligence (AGI) News and Discussions

[spryfusion]

Timestamps:
(0:00:00) - Measuring AGI
(0:11:41) - Do we need new architectures?
(0:16:26) - Is search needed for creativity?
(0:19:19) - Superhuman alignment
(0:29:58) - Impact of DeepMind on safety vs capabilities
(0:34:03) - Timelines
(0:41:24) - Multimodality

[funkervogt]

Timestamps:
(0:00:00) - Measuring AGI
(0:11:41) - Do we need new architectures?
(0:16:26) - Is search needed for creativity?
(0:19:19) - Superhuman alignment
(0:29:58) - Impact of DeepMind on safety vs capabilities
(0:34:03) - Timelines
(0:41:24) - Multimodality

Interesting that he says The Age of Spiritual Machines influenced his own predictions about AGI.

[raklian]

Google AI Chief Says There’s a 50% Chance We’ll Hit AGI in Just 5 Years
by NOOR AL-SIBAI

In an interview with tech podcaster Dwarkesh Patel, DeepMind co-founder Shane Legg said that he still thinks that researchers have a 50-50 chance of achieving artificial general intelligence (AGI), a stance he publicly announced at the very end of 2011 on his blog.

Legg apparently began looking towards his 2028 goalpost all the way back in 2001 after reading "The Age of Spiritual Machines," the groundbreaking 1999 book by fellow Google AI luminary Ray Kurzweil that predicts a future of superhuman AIs.

"There were two really important points in his book that I came to believe as true," he explained. "One is that computational power would grow exponentially for at least a few decades. And that the quantity of data in the world would grow exponentially for a few decades."

Paired with an understanding of the trends of the era, such as the deep learning method of teaching algorithms to "think" and process data the way human brains do, Legg wrote back at the start of the last decade that in the coming ones, AGI could well be achieved — so long as "nothing crazy happens like a nuclear war."

https://futurism.com/google-deepmind-agi-5-years

[wjfox]

[spryfusion]

Google DeepMind paper: "Levels of AGI: Operationalizing Progress on the Path to AGI"

Abstract:

We propose a framework for classifying the capabilities and behavior of Artificial General Intelligence (AGI) models and their precursors. This framework introduces levels of AGI performance, generality, and autonomy. It is our hope that this framework will be useful in an analogous way to the levels of autonomous driving, by providing a common language to compare models, assess risks, and measure progress along the path to AGI. To develop our framework, we analyze existing definitions of AGI, and distill six principles that a useful ontology for AGI should satisfy. These principles include focusing on capabilities rather than mechanisms; separately evaluating generality and performance; and defining stages along the path toward AGI, rather than focusing on the endpoint. With these principles in mind, we propose “Levels of AGI” based on depth (performance) and breadth (generality) of capabilities, and reflect on how current systems fit into this ontology. We discuss the challenging requirements for future benchmarks that quantify the behavior and capabilities of AGI models against these levels. Finally, we discuss how these levels of AGI interact with deployment considerations such as autonomy and risk, and emphasize the importance of carefully selecting Human-AI Interaction paradigms for responsible and safe deployment of highly capable AI systems.

[Yuli Ban]

[Yuli Ban]

[Yuli Ban]

[wjfox]

Sam Altman on AI next year: "The model capability will have taken such a leap forward that no one expected... that much progress"

[wjfox]