.AGI.Eth [ U N R U G G A B L E S U B N A M E S ] AGI.Eth : “World's Most Coveted #AGI Web3 Asset” . . . YourName.AGI.Eth Mint : 0.06 Eth Example : .AGI.Eth : https://
opensea.io/assets/ethereu
m/0xd4416b13d2b3a9abae7acd5d6c2bbdbe25686401/55363418535483371350398593018619798705017940866456154981437639208174330544567
… #AGIFirst #ENS #ENSDomains
AGI
-
AGI.Eth Unruggable Subnames: Mint Web3 Assets
By
–
-
Caravan of llamas: exploring serial architecture design
By
–
Caravan of llamas — a serial architecture
-
Utilitarianism Without Proper Future Discounting in AI Ethics
By
–
I have long wondered if this is exactly the ideology that comes out when you’re purely utilitarian and fail to properly add a discount factor to valuations of future states
-
Why AI Alignment Undervalued Compared to Global Priorities
By
–
certainly AI alignment (on a high level) is an important issue but why is it undervalued relative to eg world hunger or pandemic preparedness? and given this, why is studying language models considered a reasonable path towards eventually saving the world?
-
Mechanistic Interpretability: Noble But Disconnected from AI Safety
By
–
I also think the sub field of mechanistic interpretability is very cool — it’s all three noble, challenging, and interesting — I just struggle to see how it connects to the broader goals (building AI systems that don’t kill us) or at least why it’s a top priority
-
Effective altruism goals versus narrow AI research priorities
By
–
i’m curious about effective altruism: how do so many smart people with the goal “do good for the world” wind up with the subgoal “analyze the neurons of GPT-2 small” or something similar?
-
Stanford Research Challenges AGI Fears and LLM Capabilities
By
–
Top AI stories of 2023: Stanford researchers showed that fears of AGI are unfounded. Large language models are not greater than the sum of their parts. https://
stanford.io/41IMyVF -
Mindstorms in Natural Language-Based Societies of Mind
By
–
Mindstorms in Natural Language-Based Societies of Mind Zhuge et al.: https://
arxiv.org/abs/2305.17066 #ArtificialIntelligence #DeepLearning #MachineLearning -
AGI Nodes and Agents Create Decentralized AGI Value
By
–
AGI NODES X AGI AGENTS = DECENTRALIZED AGI “The combination of the #AGINode, the #AGIAgent and the #AGIToken could generate unprecedented value.” — Vincent Boucher, President of http://
MONTREAL.AI http://
MONTREAL.AI: Winning the #AGI Race #AGIFirst #MontrealAI -
AI Go opponent delays moves to appear fair
By
–
in Go, the white stones take a long time to move, while the black stones, strangely, move immediately after the white. even though the next white move is quite predictable, the black stones just sit there, almost as if they're smiling. is it to maintain the appearance of a fair