MASTERMIND

MASTERMIND

MASTERMIND documentation on the blockchain

Related articles

GraphRAG Evolves:

Understanding PathRAG and the Future of the Retrieval Augmented Generation Engine Retrieval Augmented Generative Engine (RAGE) has enhanced how we interact with large language models (LLMs). Instead of relying solely on the knowledge baked into the model during training, RAG systems can pull in relevant information from external sources, making them more accurate, up-to-date, and trustworthy. But traditional RAG, often relying on vector databases, has limitations. A new approach, leveraging knowledge graphs, is rapidly evolving, and […]

Learn More

production_transformer.py

The Transformer architecture is a type of neural network that has advanced natural language processing (NLP) tasks while recently being applied to various other domains including time series prediction. Here’s a detailed look at its key components and how they function: Key Components of Transformer Architecture: How Transformers Work for Financial Forecasting: Practical Considerations: In summary, the Transformer architecture is particularly well-suited for tasks where understanding the relationship between elements of a sequence is crucial, […]

Learn More
together ai

aGLM MASTERMIND RAGE Mixtral8x7B playground 1

together.ai provides a cloud environment playground for a number of LLM including Mixtral8x7Bv1. This model was chosen for the 32k ++ context window and suitable point of departure dataset for deployment of aGLM Autonomous General Learning Model. aGLM design goals include RAGE with MASTERMIND controller for logic and reasoning. The following three screenshots show the first use of aGLM recognising aGLM and MASTERMIND RAGE components to include machine.dreaming and knowledge as THOT from aGLM parse. […]

Learn More