Difference between revisions of "AI Marketplace & Toolkit/Model Interoperability"
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* [[Building Your Environment]] | * [[Building Your Environment]] | ||
| − | * [[Algorithm Administration#AIOps / MLOps|AIOps / MLOps]] | + | * [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] |
* [[Service Capabilities]] | * [[Service Capabilities]] | ||
* [[Algorithm Administration#Automated Learning|Automated Learning]] | * [[Algorithm Administration#Automated Learning|Automated Learning]] | ||
Revision as of 11:19, 19 March 2023
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Contents
SingularityNET
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- From Here to Human-Level Artificial General Intelligence in Four (Not All That) Simple Steps | Ben Goertzel
- The Future of Artificial Intelligence According to Ben Goertzel | Ben Goertzel
OpenCog AtomSpace
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A methodological framework: develop a representation of a general class of architectures within which different architectures can be compared and contrasted. This should facilitate communication and integration across sub-fields of and approaches to AI, as well providing a framework for evaluating alternative architectures. A Framework for Comparing Agent Architectures | Sloman, A. and Scheutz, M.
Aigents
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Open Neural Network Exchange (ONNX) Format
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Open ecosystem to address the interoperability among neural network toolkits challenge, Amazon AWS, Facebook and Microsoft have collaborated to build Open Neural Network Exchange (ONNX), which makes it possible to reuse trained neural network models across multiple frameworks.
