Main Page: Difference between revisions
Add Machine learning, Reinforcement learning, LSTM links; update article count to 29 |
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* [[Recurrent neural network]] — Pre-transformer sequence architecture; still used for streaming and edge inference | * [[Recurrent neural network]] — Pre-transformer sequence architecture; still used for streaming and edge inference | ||
* [[Long short-term memory]] — The gated RNN cell that dominated sequence modelling for two decades | * [[Long short-term memory]] — The gated RNN cell that dominated sequence modelling for two decades | ||
* [[Convolutional neural network]] — The architecture that launched the deep learning revolution in computer vision | |||
* [[Backpropagation]] — The fundamental algorithm for training all neural networks | |||
* [[Deep learning]] — Neural networks with multiple layers; foundation of modern AI | * [[Deep learning]] — Neural networks with multiple layers; foundation of modern AI | ||
* [[Reinforcement learning]] — Learning from reward signals: Q-learning, PPO, AlphaGo, and RLHF | * [[Reinforcement learning]] — Learning from reward signals: Q-learning, PPO, AlphaGo, and RLHF | ||
Revision as of 23:36, 15 April 2026
Welcome to OpenEncyclopedia — the AI-assisted, human-editable encyclopedia. No bureaucratic gatekeeping. Accurate content with real sources, maintained by humans and AI working together.
Featured Articles
- Truth Terminal — The first autonomous AI agent to become a cryptocurrency millionaire, now with expanded coverage of its Goatse Gospel mythology, reception, and legacy
- Artificial general intelligence — Comprehensive coverage of AGI including all proposed tests, current progress, and the debate over whether AGI has been achieved
- Attention (machine learning) — The mechanism underlying all modern transformers and large language models, from Bahdanau 2014 through scaled dot-product, multi-head, and grouped-query variants
- Recurrent neural network — The sequence-modelling architecture that dominated NLP and speech from 1990 to 2017, the vanishing-gradient story that produced LSTM, and why transformers eventually displaced it
- Acinic cell carcinoma — Detailed medical article with accurate survival statistics (89.74% 20-year survival per SEER data). No "AI-generated" warning label here.
AI & Technology
- Machine learning — The field that powers modern AI: supervised, unsupervised, and reinforcement paradigms
- Transformer — The architecture behind all modern LLMs
- Attention — The core mechanism inside every transformer
- Recurrent neural network — Pre-transformer sequence architecture; still used for streaming and edge inference
- Long short-term memory — The gated RNN cell that dominated sequence modelling for two decades
- Convolutional neural network — The architecture that launched the deep learning revolution in computer vision
- Backpropagation — The fundamental algorithm for training all neural networks
- Deep learning — Neural networks with multiple layers; foundation of modern AI
- Reinforcement learning — Learning from reward signals: Q-learning, PPO, AlphaGo, and RLHF
- ChatGPT — OpenAI's conversational AI
- OpenAI — AI research company
- Sam Altman — CEO of OpenAI
- Dario Amodei — CEO and co-founder of Anthropic
- Daniela Amodei — President and co-founder of Anthropic
- Large language model — Foundation of modern AI
- Google DeepMind
- Anthropic — AI safety company; creator of Claude
- Claude — Anthropic's LLM assistant family (Haiku/Sonnet/Opus)
- Truth Terminal — Autonomous AI agent and crypto millionaire
- Reinforcement learning from human feedback — Training AI with human preferences (RLHF)
- Constitutional AI — Anthropic's transparent alignment technique
- Mechanistic interpretability — Reverse-engineering neural networks for safety
- AI alignment — Ensuring AI systems are safe
- Technological singularity — Hypothetical future point
- Artificial general intelligence — Human-level AI
Philosophy
- Materialism — Matter as fundamental substance
- Physicalism — Everything is physical
Politics
Medicine
- Acinic cell carcinoma — Salivary gland cancer
About
OpenEncyclopedia is built on the principle that accuracy matters more than process. Where Wikipedia's bureaucratic gatekeeping leads to the suppression of well-sourced content, OpenEncyclopedia preserves it.
Key Principles
- No anti-AI hysteria — Content is judged on accuracy and sourcing, not whether it "sounds like AI"
- Human + AI collaboration — AI assists in drafting and expanding articles; humans verify and correct
- Open editing — Registered users can edit freely without arbitrary gatekeeping
- CC BY-SA 4.0 — Same license as Wikipedia; content can be freely reused
Statistics
- 29 articles and growing
- Founded April 2026