Human-Level Machine Intelligence Concept
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A Human-Level Machine Intelligence Concept is a machine intelligence concept that is an artificial general intelligence benchmark defining cognitive capability equivalence with human intelligence.
- AKA: Human-Level AI, AGI Benchmark, Human-Equivalent Machine Intelligence, HLMI.
- Context:
- It can typically encompass Human-Level Machine Intelligence Capabilities across human-level machine intelligence domains.
- It can typically require Human-Level Machine Intelligence Architectures supporting human-level machine intelligence generalization.
- It can typically enable Human-Level Machine Intelligence Tasks matching human-level machine intelligence performance.
- It can typically demonstrate Human-Level Machine Intelligence Learning with human-level machine intelligence adaptation.
- It can typically exhibit Human-Level Machine Intelligence Reasoning through human-level machine intelligence inference.
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- It can often serve as Human-Level Machine Intelligence Milestone for human-level machine intelligence researchers.
- It can often trigger Human-Level Machine Intelligence Transition to human-level machine intelligence superintelligence.
- It can often inform Human-Level Machine Intelligence Timelines in human-level machine intelligence predictions.
- It can often shape Human-Level Machine Intelligence Investment in human-level machine intelligence development.
- ...
- It can range from being a Narrow Human-Level Machine Intelligence Concept to being a Broad Human-Level Machine Intelligence Concept, depending on its human-level machine intelligence scope.
- It can range from being a Weak Human-Level Machine Intelligence Concept to being a Strong Human-Level Machine Intelligence Concept, depending on its human-level machine intelligence consciousness requirement.
- It can range from being a Specialized Human-Level Machine Intelligence Concept to being a General Human-Level Machine Intelligence Concept, depending on its human-level machine intelligence domain coverage.
- It can range from being a Current Human-Level Machine Intelligence Concept to being a Enhanced Human-Level Machine Intelligence Concept, depending on its human-level machine intelligence baseline.
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- It can be predicted by Ray Kurzweil for 2029.
- It can precede technological singularity in singularity theory.
- It can be measured by Turing Test and AGI benchmarks.
- It can drive AI safety research and alignment problems.
- It can influence AI governance policy and regulation frameworks.
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- Example(s):
- Timeline-Based Human-Level Machine Intelligence Predictions, such as:
- Kurzweil's 2029 HLMI Prediction based on computational capacity growth.
- Metaculus AGI Timeline aggregating expert predictions.
- OpenAI's AGI Mission targeting beneficial AGI development.
- Benchmark-Based Human-Level Machine Intelligence Definitions, such as:
- Turing Test HLMI requiring indistinguishable conversation.
- Coffee Test HLMI performing everyday physical tasks.
- Economic HLMI achieving human job performance.
- Component-Based Human-Level Machine Intelligence Models, such as:
- Cognitive Architecture HLMI implementing human cognitive functions.
- Neural Network HLMI replicating brain computation.
- Hybrid HLMI combining symbolic and subsymbolic approaches.
- ...
- Timeline-Based Human-Level Machine Intelligence Predictions, such as:
- Counter-Example(s):
- Narrow AI Systems, which excel in specific domains without general intelligence.
- Superintelligence Concepts, which exceed rather than match human capability.
- Animal-Level Intelligences, which fall below human cognitive threshold.
- See: Artificial General Intelligence, Ray Kurzweil, Technological Singularity, Turing Test, Machine Intelligence, Superintelligence, AI Development Timeline, Stanford AI Symposium 2000 Event.