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SingularityNET AGIX: YouTube의 라이브 스트림
SingularityNET은 5월 7일 오후 5시(UTC) YouTube에서 두 개의 미니 AMA 시리즈를 개최합니다. 이 시리즈에서는 인간 수준 이상의 인공 일반 지능(AGI)을 위한 프레임워크인 OpenCog Hyperon용 통합 경험 학습 구성 요소 개발의 최신 발전 사항에 대해 논의합니다.
첫 번째 세션에서는 OpenCog Hyperon의 MeTTa 언어 인지 계산에 NARS(Non-Axiomatic Reasoning System)를 구현하고 AIRIS(Autonomous Intelligent Reinforcement Interpreted Symbolism) 인과 기반 학습 AI를 Hyperon에 통합하는 방법을 다룹니다. 두 번째 세션에서는 ROCCA(Rational OpenCog Controlled Agent)를 사용하여 Hyperon에서 경험적 학습을 재현하고 순방향 및 역방향 체인, PLN(확률적 논리 네트워크) 및 패턴 마이닝을 포함하여 ROCCA가 OpenCog 클래식에서 Hyperon으로 요구하는 기본 구성 요소를 포팅하는 데 중점을 둘 것입니다.
이밴트: 2024년 5월 7일 17:00 UTC
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SingularityNET
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Join us this Tuesday, May 7th, 2024, at 5 pm UTC for the first session of a special two-part SingularityNET's Technical Tuesdays mini-series dedicated to the latest advancements in the development of a unified experiential learning component for OpenCog Hyperon, our framework for #AGI at the human level and beyond.
Session 1
- The implementation of NARS (Non-Axiomatic Reasoning System) in OpenCog Hyperon’s MeTTa language cognitive computations;
- Integrating the AIRIS (Autonomous Intelligent Reinforcement Interpreted Symbolism) causality-based learning AI into Hyperon.
Session 2
- Recreating experiential learning in Hyperon using ROCCA (Rational OpenCog Controlled Agent);
- Porting fundamental components ROCCA requires from OpenCog classic to Hyperon, including forward and backward chaining, PLN (Probabilistic Logic Networks), and pattern mining.
These advancements are part of our ongoing initiative to consolidate the strengths of several systems —ROCCA, NARS, OpenPsi, and AIRIS— to create a unified experiential learning component for Hyperon. This approach will allow AI models to:
- Develop a goal-independent understanding of their environment through causal knowledge gained from planned and spontaneous interactions;
- Explore their environment with increased efficiency using a curiosity model that prioritizes situations with high uncertainty, challenging their existing causal knowledge.
Our preliminary findings indicate that this approach surpasses common Reinforcement Learning techniques in terms of data efficiency by orders of magnitude.
To learn more, set your reminder for the livestream now on your preferred platform:
- YouTube: https://t.co/66Xm1SpDC8
- LinkedIn: https://t.co/JEwoyT7Z9R
- X: SingularityNET
Session 1
- The implementation of NARS (Non-Axiomatic Reasoning System) in OpenCog Hyperon’s MeTTa language cognitive computations;
- Integrating the AIRIS (Autonomous Intelligent Reinforcement Interpreted Symbolism) causality-based learning AI into Hyperon.
Session 2
- Recreating experiential learning in Hyperon using ROCCA (Rational OpenCog Controlled Agent);
- Porting fundamental components ROCCA requires from OpenCog classic to Hyperon, including forward and backward chaining, PLN (Probabilistic Logic Networks), and pattern mining.
These advancements are part of our ongoing initiative to consolidate the strengths of several systems —ROCCA, NARS, OpenPsi, and AIRIS— to create a unified experiential learning component for Hyperon. This approach will allow AI models to:
- Develop a goal-independent understanding of their environment through causal knowledge gained from planned and spontaneous interactions;
- Explore their environment with increased efficiency using a curiosity model that prioritizes situations with high uncertainty, challenging their existing causal knowledge.
Our preliminary findings indicate that this approach surpasses common Reinforcement Learning techniques in terms of data efficiency by orders of magnitude.
To learn more, set your reminder for the livestream now on your preferred platform:
- YouTube: https://t.co/66Xm1SpDC8
- LinkedIn: https://t.co/JEwoyT7Z9R
- X: SingularityNET
이벤트 발표 후 AGIX 가격 변동
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