Stop guessing. Start discovering. Revolutionizing Research and Study activities with AI and machine learning.

In the late 1990s, we proposed "conceptual research" as an innovation promotion method and began research into machine learning technologies, including Self-Organizing Maps (SOMs), as a technology to realize it. After approximately 30 years, that dream has finally come true with ThinkNavi. This overturns the conventional wisdom of qualitative and quantitative research activities. We are not simply introducing AI, statistics, or machine learning. We have incorporated the philosophy cultivated through many years of research into the tool. By abandoning conventional hypothesis-driven research, we use self-organizing learning algorithms to extract "structure" from data and create concepts that are key to solving problems.

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White Paper: Self-Oganinzing Knowledge Graphs

It is also an interface between humans and AI.

The biggest problem with AI technology currently in development is that it's a black box. Even world-renowned AI researchers don't know exactly what's happening inside. Moreover, AI has information processing capabilities far superior to humans. While humans can only perceive three-dimensional space, AI can perceive multi-dimensional space. In other words, a situation has emerged where humans are at a significant disadvantage when it comes to controlling AI. To overcome this, we need technological tools that allow humans to give instructions within multi-dimensional space. The technology we have developed to reform our research activities seems to indirectly help solve this problem as well.
Mindware

Mindware is a new type of media that replaces books, allowing users to quickly learn interesting insights and find the information they need from the creator's knowledge through chat. For creators, it acts as a digital twin that speaks for their thoughts, opinions, and beliefs. In the future, leaving behind Mindware for future generations will be the greatest honor.

ThinkNavi

This platform offers a variety of applications using conceptual structure models. It can be used as a viewer for Mindware content, explore new concepts from data obtained through automated research, and easily build an AI concierge. Furthermore, the AI ​​guides you toward higher-quality thinking through chat.

ConceptMiner

Concept Modeling Engine. A set of libraries with tools, such as Growing Neural Gas (GNG) + Minimum Spanning Tree (MST), Self-Organizing Maps (SOM). Users can easily call these functions from their own systems using APIs, and develop applications using text/data mining, AI explainability, and associative memory.