Core Concepts, terminologies, technologies¶
Original OneNote page: Rapiddraft vscode - Core Concepts, terminologies, technologies
Route: product/technical note to route
Categories: events, product_technical_or_learning
Source¶
- Word export:
C:\Users\adeel\OneDrive\100_Knowledge\203_TextCAD\01_Product_Project_Management\TextCAD_Wiki\inbox\onenoteexport\01_PROJECTS\Gauss Compute\Rapiddraft vscode - Core Concepts, terminologies, technologies.docx - MHT export:
C:\Users\adeel\OneDrive\100_Knowledge\203_TextCAD\01_Product_Project_Management\TextCAD_Wiki\inbox\onenoteexport\01_PROJECTS\Gauss Compute\Rapiddraft vscode - Core Concepts, terminologies, technologies.mht
Extracted Notes¶
These notes are extracted from the Word export so the source is visible in the wiki without moving or deleting the original file.
- Core Concepts, terminologies, technologies
- Application (Current and prospective)
- Supervised Learning
- Unsupervised learning
- Convoluted neural networks
- Extract Transform Load
- Extract Load Transform
- Image segmentation
- Cross Model grounding
- deterministic, text-to-diagram approach (e.g., Mermaid, PlantUML, or Graphviz/DOT)
- (a) Short Description
- (b) Current Applications
- (c) Prospective Applications
- LLM (Large Language Model)
- AI models trained on massive text data to understand and generate human-like language.
- ChatGPT, Google Gemini, code assistants, customer support bots.
- Personalized education, policy drafting, mental health triage, and automated legal/document review.
- RAG (Retrieval-Augmented Generation)
- Combines external knowledge retrieval with language generation to improve factual accuracy.
- Chatbots using company data, enterprise search tools.
- AI assistants that stay updated with live news, medical or legal document search with verified facts.
- Deep learning architecture enabling sequence modeling with attention mechanisms.
- Foundation of GPT, BERT, DALLĀ·E, Whisper.
- Universal AI interpreters for text, images, video, and sound; cross-modal understanding.
- Subset of ML using layered neural networks to learn complex patterns from data.
- Speech recognition, autonomous driving, image classification.
- Predicting diseases, climate modeling, advanced materials design.
- Computational models inspired by the brain, learning patterns through weighted layers.
- Credit scoring, recommendation systems, spam detection.
- Decentralized energy grid control, personalized healthcare diagnostics.
- Supervised Learning
- Model learns from labeled datasets to make predictions or classifications.
- Email filtering, medical diagnosis models, OCR.
- Predictive social welfare systems, personalized tutoring based on learning patterns.
- Unsupervised Learning
URLs Found¶
- https://chatgpt.com/g/g-p-689b4dd612f4819191e700de385217ce-gausscompute/c/68fb5273-0c4c-8326-9d45-01266496fa33
Next Curation Action¶
Review for Product Wiki migration. Keep only relationship, GTM, or CRM implications in the Network Wiki.
Sources¶
C:\Users\adeel\OneDrive\100_Knowledge\203_TextCAD\01_Product_Project_Management\TextCAD_Wiki\inbox\onenoteexport\01_PROJECTS\Gauss Compute\Rapiddraft vscode - Core Concepts, terminologies, technologies.docxC:\Users\adeel\OneDrive\100_Knowledge\203_TextCAD\01_Product_Project_Management\TextCAD_Wiki\inbox\onenoteexport\01_PROJECTS\Gauss Compute\Rapiddraft vscode - Core Concepts, terminologies, technologies.mht