Explainable AI
Featured Posts
Generative AI
Natural Language Processing
Python
Build and Evaluate High Performance Taxonomy-Based LLMs From Scratch
One obvious way to dramatically improve the quality of LLM and RAG systems is to use high-quality input sources, as opposed to just raw text from the crawled or parsed content. Combine it with specialization: one LLM per top domain, allowing the user to customize parameters and specify the domain in addition to standard concise […]
Read More
Explainable AI
Featured Posts
Generative AI
Natural Language Processing
Python
Hallucination-Free, Self-Tuned, Fast Hierarchical LLMs with Multi-Token Embeddings
The new generation of RAG / LLM architecture is moving away from the original monolithic and generic OpenAI model, towards a collection of decentralized and specialized LLMs jointly organized and governed via multi-agent systems. The benefits are obvious: low latency, smaller tables (one per LLM), faster training and fine-tuning, energy-efficient, better results, with much lower […]
Read More
You must be logged in to post a comment.