Teaching with AI
Guide for educators using ChatGPT in classrooms with prompts, explanations, and limitations.
Guide for educators using ChatGPT in classrooms with prompts, explanations, and limitations.
ChatGPT Enterprise offers enterprise-grade security, privacy, and advanced capabilities.
OpenAI partners with Scale to help enterprises fine-tune advanced models.
GPT-3.5 Turbo fine-tuning now available; developers can customize with custom data.
GPT-4 used for content moderation and policy development with faster feedback loops.
ChatGPT custom instructions feature lets users set preferences for all conversations.
OpenAI API updates: function calling, improved model control, extended context window, and reduced pricing.
Training method for improved mathematical reasoning using process supervision (rewarding reasoning steps) vs outcome supervision; improves alignment via interpretable chain-of-thought.
Using GPT-4 to automatically generate and score explanations for neuron behavior in GPT-2; releases dataset of explanations for interpretability research.
OpenAI announces ChatGPT plugins enabling LLMs to access real-time data, run computations, and integrate third-party services.
Research on labor market impact of large language models including analysis of economic displacement and wage effects.
GPT-4 multimodal model accepts text/images, achieves human-level performance on professional/academic benchmarks. Major LLM release.
Explanation of ChatGPT behavior design, customization plans, and public input approach. AI alignment/governance.
ChatGPT subscription plan launch with premium features. Product announcement.
Step-by-step implementation of GPT architecture from scratch with detailed code and explanations of each component.
Research collaboration investigating LLM misuse for disinformation with policy and ML expert input. Safety/policy research.
GPT-3 fine-tuned for automated video creation at scale. LLM application case study.
System for generating 3D point clouds from text prompts. Multimodal generative model.
Conversational AI model trained to answer follow-ups, admit errors, and reject inappropriate requests. LLM release.
Research on scaling laws governing reward model overoptimization. Machine learning research publication.
Educational tutorial building a character-level language model from scratch, covering foundational concepts in neural networks and language modeling.
OpenAI's research focus on learning from human feedback and building aligned AI systems to address broader alignment challenges.
Efficient training methods for language models to perform infilling tasks in code and text.
Framework for hazard analysis of code synthesis large language models addressing safety and reliability.
DALL-E 2 implements technique to generate images of people reflecting global population diversity.
DALL-E 2 safety guardrails implemented to prevent policy-violating image generation.
Neural network trained via video pretraining to play Minecraft using native human controls; achieves diamond tool crafting as step toward general computer-using agents.
Technical approaches to training large neural networks using GPU clusters for synchronized computation.
Best practices guide for developing and deploying large language models from Cohere, OpenAI, and AI21 Labs.
DALL-E 2 research preview expanded with 3 million user-generated images and improved safety processes.
Research on hierarchical text-conditional image generation using CLIP latents for improved image synthesis.
GPT-3 and Codex released with edit and insert capabilities for text modification beyond completion.
Research agenda for evaluating economic impacts of code generation models.
Safety and misuse mitigation lessons from deploying large language models.
InstructGPT: language models aligned with human feedback to follow instructions, improve truthfulness and reduce toxicity.
OpenAI API embeddings endpoint for semantic search, clustering, topic modeling, and classification tasks.
Text and code embeddings learned via contrastive pre-training.
Fine-tuned GPT-3 with text-based web browser interface for improved factual accuracy in open-ended question answering.
Single-command fine-tuning for GPT-3 customization to specific applications.
OpenAI Residency program announcement for AI talent development.
System solving grade-school math word problems at 55% accuracy, approaching human performance of 60%.
Triton 1.0: open-source Python-like language for efficient GPU neural network programming without CUDA expertise.
Evaluation methods for large language models trained on code.
Fine-tuning language models on curated datasets to improve specific behavioral values.
Over 300 applications using GPT-3 API for search, conversation, text completion and advanced AI features.
Discovered multimodal neurons in CLIP responding to same concepts across literal, symbolic, conceptual presentations.
Kubernetes scaled to 7,500 nodes for infrastructure supporting large models like GPT-3, CLIP, DALL·E.
CLIP: neural network learning visual concepts from text supervision; enables zero-shot visual classification.
DALL·E: neural network generating images from text captions across diverse concepts.
Applied reinforcement learning from human feedback to improve language model summarization capabilities.