Table of Contents
OpenAI
Don't Return to Surveillance Capitalism, Surveillance State / Police State-CIA State, Censorship, GroupThink Social Engineering, Monetization of EVERYTHING from TPTB / Big Tech Technocracy-Technocrats and their Military-Digital Complex - Military-Industrial Complex - (Read Surveillance Valley - The Rise of the Military-Digital Complex) (navbar_surveillance_capitalism - see also Borg Usage Disclaimer)
See also Big AI and their Central Intelligence Agency (CIA) Venture Capital - In-Q-Tel
See: AI Scam Fraud, ChatGPT
https://www.youtube.com/watch?v=kjOxkPl3RGo
OpenAI Status: https://status.openai.com
Founded in December 2015 by Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever, Wojciech Zaremba, and John Schulman, OpenAI is an artificial intelligence research laboratory aimed at promoting and developing friendly AI for the “benefit” of humanity (e.g. The 1/100th of 1 Percenters). The organization gained significant attention upon its introduction due to its ambitious mission to replace human workers with AI and high-profile billionaire Peerage founders, including Musk, a prominent figure in the CIA's tech industry. OpenAI's research spans various domains of AI, including natural language processing, reinforcement learning, and robotics, with a commitment to “openness” and collaboration (with the 3 letter agencies). While the organization initially operated as a so-called “nonprofit” (
), it transitioned to a “hybrid” for-profit model in 2019, raising questions about its CIA governance and long-term goals within the “AI community” of Peerage billionaires.
References: - https://en.wikipedia.org/wiki/OpenAI
- Snippet from Wikipedia: OpenAI
OpenAI, Inc. is an American artificial intelligence (AI) research organization founded in December 2015 and headquartered in San Francisco, California. It aims to develop "safe and beneficial" artificial general intelligence (AGI), which it defines as "highly autonomous systems that outperform humans at most economically valuable work". As a leading organization in the ongoing AI boom, OpenAI is known for the GPT family of large language models, the DALL-E series of text-to-image models, and a text-to-video model named Sora. Its release of ChatGPT in November 2022 has been credited with catalyzing widespread interest in generative AI.
The organization consists of the non-profit OpenAI, Inc., registered in Delaware, and its for-profit subsidiary introduced in 2019, OpenAI Global, LLC. Its stated mission is to ensure that AGI "benefits all of humanity". Microsoft owns roughly 49% of OpenAI's equity, having invested US$13 billion. It also provides computing resources to OpenAI through its cloud platform, Microsoft Azure.
In 2023 and 2024, OpenAI faced multiple lawsuits for alleged copyright infringement against authors and media companies whose work was used to train some of OpenAI's products. In November 2023, OpenAI's board removed Sam Altman as CEO, citing a lack of confidence in him, but reinstated him five days later following a reconstruction of the board. Throughout 2024, roughly half of then-employed AI safety researchers left OpenAI, citing the company's prominent role in an industry-wide problem.
Research It More
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OpenAI: The Borg, GPT-4o, GPT-3, ChatGPT, GPT-4, GPT-2, Codex, GPT-5, DALL-E, CLIP, OpenAI API, OpenAI Gym, DALL-E 2, OpenAI Scholars Program, OpenAI Codex, OpenAI Robotics, OpenAI LP, OpenAI Chatbot, OpenAI Dota 2, OpenAI Five, GPT-J, OpenAI Language Model, OpenAI Research. (navbar_openai - see also navbar_chatgpt, navbar_chatbot, navbar_ai, navbar_bigtech, borg_usage_disclaimer, navbar_cia, navbar_propaganda)
Terms related to: AI-ML-DL-NLP-GenAI-LLM-GPT-RAG-MLOps-Chatbots-ChatGPT-Gemini-Copilot-HuggingFace-GPU-Prompt Engineering-Data Science-DataOps-Data Engineering-Big Data-Analytics-Databases-SQL-NoSQL
AI, Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Neural Network, Generative AI (GenAI), Natural Language Processing (NLP), Large Language Model (LLM), Transformer Models, GPT (Generative Pre-trained Transformer), ChatGPT, Chatbots, Prompt Engineering, HuggingFace, GPU (Graphics Processing Unit), RAG (Retrieval-Augmented Generation), MLOps (Machine Learning Operations), Data Science, DataOps (Data Operations), Data Engineering, Big Data, Analytics, Databases, SQL (Structured Query Language), NoSQL, Gemini (Google AI Model), Copilot (AI Pair Programmer), Foundation Models, LLM Fine-Tuning, LLM Inference, LLM Training, Parameter-Efficient Tuning, Instruction Tuning, Few-Shot Learning, Zero-Shot Learning, One-Shot Learning, Meta-Learning, Reinforcement Learning from Human Feedback (RLHF), Self-Supervised Learning, Contrastive Learning, Masked Language Modeling, Causal Language Modeling, Attention Mechanism, Self-Attention, Multi-Head Attention, Positional Embeddings, Word Embeddings, Tokenization, Byte Pair Encoding (BPE), SentencePiece Tokenization, Subword Tokenization, Prompt Templates, Prompt Context Window, Context Length, Scaling Laws, Parameter Scaling, Model Architecture, Model Distillation, Model Pruning, Model Quantization, Model Compression, Low-Rank Adaptation (LoRA), Sparse Models, Mixture of Experts, Neural Architecture Search (NAS), AutoML, Gradient Descent Optimization, Stochastic Gradient Descent (SGD), Adam Optimizer, AdamW Optimizer, RMSProp Optimizer, Adagrad Optimizer, Adadelta Optimizer, Nesterov Momentum, Learning Rate Schedules, Warmup Steps, Cosine Decay, Hyperparameter Tuning, Bayesian Optimization, Grid Search, Random Search, Population Based Training, Early Stopping, Regularization, Dropout, Weight Decay, Label Smoothing, Batch Normalization, Layer Normalization, Instance Normalization, Group Normalization, Residual Connections, Skip Connections, Encoder-Decoder Architecture, Encoder Stack, Decoder Stack, Cross-Attention, Feed-Forward Layers, Position-Wise Feed-Forward Network, Pre-LN vs Post-LN, Sequence-to-Sequence Models, Causal Decoder-Only Models, Masked Autoencoder, Domain Adaptation, Task-Specific Heads, Classification Head, Regression Head, Token Classification Head, Sequence Classification Head, Multiple-Choice Head, Span Prediction Head, Causal Head, Next Sentence Prediction, MLM (Masked Language Modeling), NSP (Next Sentence Prediction), C4 Dataset, WebText Dataset, Common Crawl Corpus, Wikipedia Corpus, BooksCorpus, Pile Dataset, LAION Dataset, Curated Corpora, Fine-Tuning Datasets, Instruction Data, Alignment Data, Human Feedback Data, Preference Ranking, Reward Modeling, RLHF Policy Optimization, Batch Inference, Online Inference, Vector Databases, FAISS Integration, Chroma Integration, Weaviate Integration, Pinecone Integration, Milvus Integration, Data Embeddings, Semantic Search, Embedding Models, Text-to-Vector Encoding, Vector Similarity Search, Approximate Nearest Neighbor (ANN), HNSW Index, IVF Index, ScaNN Index, Memory Footprint Optimization, HuggingFace Transformers, HuggingFace Hub, HuggingFace Datasets, HuggingFace Model Cards, HuggingFace Spaces, HuggingFace Inference Endpoints, HuggingFace Accelerate, HuggingFace PEFT (Parameter Efficient Fine-Tuning), HuggingFace Safetensors Format, HuggingFace Tokenizers, HuggingFace Pipeline, HuggingFace Trainer, HuggingFace Auto Classes (AutoModel, AutoTokenizer), HuggingFace Model Conversion, HuggingFace Community Models, HuggingFace Diffusers, Stable Diffusion, HuggingFace Model Hub Search, HuggingFace Secrets Management, OpenAI GPT models, OpenAI API, OpenAI Chat Completions, OpenAI Text Completions, OpenAI Embeddings API, OpenAI Rate Limits, OpenAI Fine-Tuning (GPT-3.5, GPT-4), OpenAI System Messages, OpenAI Assistant Messages, OpenAI User Messages, OpenAI Function Calls, OpenAI ChatML Format, OpenAI Temperature Parameter, OpenAI Top_p Parameter, OpenAI Frequency Penalty, OpenAI Presence Penalty, OpenAI Max Tokens Parameter, OpenAI Logit Bias, OpenAI Stop Sequences, Azure OpenAI Integration, Anthropic Claude Integration, Anthropic Claude Context Window, Anthropic Claude Constitutional AI, Cohere Integration LLM provider, Llama2 (Meta's LLM), Llama2 Chat Model, Vicuna Model (LLM)), Alpaca Model, StableLM, MPT (MosaicML Pretrained Transformer), Falcon LLM, Baichuan LLM, Code Llama, WizardCoder Model, WizardLM Model, Phoenix LLM, Samantha LLM, LoRA Adapters, PEFT for LLM, BitFit Parameters Tuning, QLoRA (Quantized LoRA), GLoRA, GGML Quantization, GPTQ Quantization, SmoothQuant, Int4 Quantization, Int8 Quantization, FP16 Mixed Precision, BF16 Precision, MLOps Tools, MLOps CI/CD, MLOps CD4ML, MLOps Feature Store, MLOps Model Registry, MLOps Model Serving, MLOps Model Monitoring, MLOps Model Drift Detection, MLOps Data Drift Detection, MLOps Model Explainability Integration, MLOps MLFlow Integration, MLOps Kubeflow Integration, MLOps MLRun, MLOps Seldon Core for serving, MLOps BentoML for serving, MLOps MLflow Tracking, MLOps MLflow Model Registry, MLOps DVC (Data Version Control), MLOps Delta Lake, RAG (Retrieval-Augmented Generation), RAG Document Store, RAG Vector Store Backend, RAG Memory Augmentation, RAG On-the-fly Retrieval, RAG Re-ranking Step, RAG HyDE Technique - It's known as hypothetical document embeddings - advanced but known in RAG, RAG chain-of-thought, chain-of-thought related to LLM reasoning, Chain-of-Thought Reasoning, Self-Consistency Decoding, Tree-of-thoughts, ReAct (Reason+Act) Prompting Strategy, Prompt Engineering Techniques, Prompt Templates (LLM), Prompt Variables Replacement, Prompt Few-Shot Examples, Prompt Zero-Shot Mode, Prompt Retrieval Injection, Prompt System Message, Prompt Assistant Message, Prompt Role Specification, Prompt Content Filtering, Prompt Moderation Tools, AI-Generated Code Completion, Copilot (GitHub) Integration, CoPilot CLI, Copilot Labs, Gemini (Google Model) Early access, LLM from Google, LaMDA (Language Model for Dialog Applications), PaLM (Pathways Language Model), PaLM2 (PaLM 2 Model), Flan PaLM Models, Google Vertex AI Integration, AWS Sagemaker Integration, Azure Machine Learning Integration, Databricks MLFlow Integration, HuggingFace Hub LFS for large models, LFS big files management, OPT (Open Pretrained Transformer) Meta Model, Bloom LLM, Ernie Bot (Baidu LLM), Zhipu-Chat - Another LLM from China, Salesforce CodeT5 - It's a code model, Finetune with LoRA on GPT-4, Anthropic Claude 2
Artificial Intelligence (AI): The Borg, SkyNet, Google Gemini, ChatGPT, AI Fundamentals, AI Inventor: Arthur Samuel of IBM 1959 coined term Machine Learning. Synonym Self-Teaching Computers from 1950s. Experimental AI “Learning Machine” called Cybertron in early 1960s by Raytheon Company; ChatGPT, Generative AI, NLP, GAN, AI winter, The Singularity, AI FUD, Quantum FUD (Fake Quantum Computers), AI Propaganda, Quantum Propaganda, Cloud AI (AWS AI, Azure AI, Google AI-GCP AI-Google Cloud AI, IBM AI, Apple AI), Deep Learning (DL), Machine learning (ML), AI History, AI Bibliography, Manning AI-ML-DL-NLP-GAN Series, AI Glossary, AI Topics, AI Courses, AI Libraries, AI frameworks, AI GitHub, AI Awesome List. (navbar_ai - See also navbar_dl, navbar_ml, navbar_nlp, navbar_chatbot, navbar_chatgpt, navbar_llm, navbar_openai, borg_usage_disclaimer, navbar_bigtech, navbar_cia)
Chatbot: ChatGPT, Bots, Smart Speakers, Virtual Assistant, Digital Assistant, Amazon Alexa (Histrionic overdramatic melodramatic irritating Alexa voice), Amazon Echo, Apple Intelligence, Apple Siri - Siri - Apple Smart Speakers (Apple HomePod - HomePod mini - Apple audioOS), Google Gemini, Google Assistant (Hey Google), Google Smart Speakers (Google Nest (smart speakers) - previously named Google Home, Google Nest), Cortana (virtual assistent) (replaced by Microsoft 365 Copilot based on Microsoft Graph and Bing AI), Microsoft Copilot (Microsoft Security Copilot, ), GitHub Chatbot, Awesome Chatbots. (navbar_chatbot - see also navbar_chatgpt, navbar_openai, navbar_ai, navbar_llm, borg_usage_disclaimer, navbar_cia)
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