Modular AI Architecture with Dynamic Digital Information Maps

I already created a medical graph dictionary with nodes and edges, generated uniform graph vectors (85%) and combined them with MiniLLM vectors (15%) and utilized successfully in MLM and CLM (preidict next token) training. With only 500 Pubmed data samples

Below code was utilized create unform graph vectors based on nodes and edges of a medical graph dictionary with 500 nodes (body parts, cellular structure, diseases, medical treatment, symptoms), hierarchical order (parent, child) and medical relationship edges (treated_with, contains, experiences….)

Ninety percent of information transmitted to the human brain is visual. The importance of sight in understanding the world makes computer vision essential for AI systems. By simplifying computer vision development, startup Roboflow helps bridge the gap between AI and

The duck song 🦆🍇🍋 submitted by /u/RedditUserBrasileiro [link] [comments]

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I have two things in mind that could help me a lot. I apologise if those are easy to find but I can’t seem to find anything using just google. I mostly find AI-art tools using prompt, which I’m not

Soilless growing systems inside greenhouses, known as controlled environment agriculture, promise to advance the year-round production of high-quality specialty crops, according to an interdisciplinary research team. But to be competitive and sustainable, this advanced farming method will require the development

I just read the Spark-TTS paper, and it introduces a really clever approach to text-to-speech: a single-stream architecture with decoupled speech tokens that represents both content and acoustic features in a unified sequence. The key technical highlights: * Uses “DCC”

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