개요
안іма는 액티브 인퍼런스와 현재 LLM 기반 AI의 교차점을 조사하고 있으며, 액티브 인퍼런스 모델이 지각, 정책 및 행동에 어떻게 연관되는지, 그리고 이 프레임워크가 일관되고 정렬된 행동을 위한 AI 설계에 어떻게 기여할 수 있는지를 살펴보고 있습니다.
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인공지능 연구자와 실무자들이 LLM 행동과 정렬에 대한 액티브 인퍼런스 접근법에 관심이 있습니다.
아니마
현재 LLM 기반 AI 상호작용과 정책 기반 행동의 맥락에서 액티브 인퍼런스를 탐구한다.
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아니마 가이드
Anima는 대규모 언어 모델과의 상호작용에 활성 추론 원칙이 어떻게 적용되는지 탐구하는 생태계 프로젝트입니다. 정책 기반의 포괄적 인식 활성 추론 아키텍처가 현재 AI 시스템의 설계와 이해에 어떻게 기여할 수 있는지를 살펴봅니다.
참여하기
인공지능 연구원, 인지 과학자 및 인공지능 시스템에 대한 활성 추론 접근법에 관심 있는 실무자를 환영합니다.
주요 표면
안іма 간략 개요
관련 자료
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Notebook-based applied Active Inference work connected to blockchain-adjacent and generative modeling examples.
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Python models and materials for ant-inspired multiagent Active Inference.
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Active Entity Ontology for Science
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Public ants repository in the ActiveInferenceInstitute GitHub namespace.
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