Building more helpful ChatGPT experiences for everyone
【RSS 原文 · 未经 AI 筛选或翻译】We’re partnering with experts, strengthening protections for teens with parental controls, and routing sensitive conversations to reasoning models in ChatGPT.
【RSS 原文 · 未经 AI 筛选或翻译】We’re partnering with experts, strengthening protections for teens with parental controls, and routing sensitive conversations to reasoning models in ChatGPT.
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】What exactly does word2vec learn, and how? Answering this question amounts to understanding representation learning in a minimal yet interesting language modeling task. Despite the fact that word2vec is a well-known precursor to modern language models, for many years, researchers lacked a quantitative and predictive theory describing its learning process. In our new paper , we finally provide such a theory. We prove that there are realistic, practical regimes in which the learning problem reduces to unweighted least-squares matrix factorization . We solve the gradient flow dynamics in closed form; the final learned representations are simply given by PCA. Learning dynamics of word2vec . When trained from small initialization, word2vec learns in discrete, sequential steps. Left: rank-incrementing learning steps in the weight matrix, each decreasing the loss. Right: three time slices of the latent embedding space showing how embedding vectors expand into subspaces of increasing dimension at each learning step, continuing until model capacity is saturated. Before elaborating on this result, let’s motivate the problem. word2vec is a well-known algorithm for learning dense vector representations of words. These embedding vectors are trained using a contrastive algorithm; at the end of training, the semantic relation between any two words is captured by the angle between the corresponding embeddings. In fact, the learned embeddings empirically exhibit striking linear structure in their geometry: linear subspaces in the latent space often encode interpretable concepts such as gender, verb tense, or dialect. This so-called linear representation hypothesis has recently garnered a lot of attention since LLMs exhibit this behavior as well , enabling semantic inspection of internal representations and providing for novel model ste
【RSS 原文 · 未经 AI 筛选或翻译】We’re releasing a more advanced speech-to-speech model and new API capabilities including MCP server support, image input, and SIP phone calling support.
【RSS 原文 · 未经 AI 筛选或翻译】OpenAI launches a $50M People-First AI Fund to help U.S. nonprofits scale impact with AI. Applications open Sept 8–Oct 8, 2025 for grants in education, healthcare, research, and more.
【RSS 原文 · 未经 AI 筛选或翻译】OpenAI surveyed over 1,000 people worldwide on how AI should behave and compared their views to our Model Spec. Learn how collective alignment is shaping AI defaults to better reflect diverse human values and perspectives.
【RSS 原文 · 未经 AI 筛选或翻译】OpenAI and Anthropic share findings from a first-of-its-kind joint safety evaluation, testing each other’s models for misalignment, instruction following, hallucinations, jailbreaking, and more—highlighting progress, challenges, and the value of cross-lab collaboration.
【RSS 原文 · 未经 AI 筛选或翻译】How we think about safety for users experiencing mental or emotional distress, the limits of today’s systems, and the work underway to refine them.
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】Discover how a specialized AI model, GPT-4b micro, helped OpenAI and Retro Bio engineer more effective proteins for stem cell therapy and longevity research.
【RSS 原文 · 未经 AI 筛选或翻译】Blue J scaled to three countries and more than 3,000 firms thanks to focus, domain depth, and the right OpenAI model.
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】Discover how MIXI, a leader in digital entertainment and lifestyle services in Japan, uses ChatGPT Enterprise to transform productivity, boost AI adoption across teams, and create a secure environment for innovation.
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】Learn how DoorDash is scaling AI adoption to empower employees to build, learn, and innovate faster in a conversation with Chief People Officer Mariana Garavaglia.
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】We’ve just sent a letter to Gov. Gavin Newsom calling for California to lead the way in harmonizing state-based AI regulation with national—and, by virtue of US leadership, emerging global—standards.
【RSS 原文 · 未经 AI 筛选或翻译】Built with OpenAI o3, o3-Pro, GPT-4.1, and GPT-5, Basis’ AI agents help accounting firms save up to 30% of their time and expand capacity for advisory and growth.
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】Introducing GPT-5 in our API platform—offering high reasoning performance, new controls for devs, and best-in-class results on real coding tasks.
【RSS 原文 · 未经 AI 筛选或翻译】GPT-5 is OpenAI’s most advanced model—transforming enterprise AI, automation, and workforce productivity in the new era of intelligent work.
【RSS 原文 · 未经 AI 筛选或翻译】Learn how GPT-5 unlocks new possibilities in coding and design.
【RSS 原文 · 未经 AI 筛选或翻译】Learn how GPT-5 assists with creative writing.
【RSS 原文 · 未经 AI 筛选或翻译】Learn how GPT-5 is used for medical research.
【RSS 原文 · 未经 AI 筛选或翻译】Learn how Amgen uses GPT-5.
【RSS 原文 · 未经 AI 筛选或翻译】Learn how Cursor uses GPT-5.
【RSS 原文 · 未经 AI 筛选或翻译】Discover how OpenAI's new safe-completions approach in GPT-5 improves both safety and helpfulness in AI responses—moving beyond hard refusals to nuanced, output-centric safety training for handling dual-use prompts.
【RSS 原文 · 未经 AI 筛选或翻译】Watch a GPT-5 demo for work showing how the model can analyze feedback, create a product plan and prototype, and summarize next steps.
【RSS 原文 · 未经 AI 筛选或翻译】We are introducing GPT‑5, our best AI system yet. GPT‑5 is a significant leap in intelligence over all our previous models, featuring state-of-the-art performance across coding, math, writing, health, visual perception, and more.
【RSS 原文 · 未经 AI 筛选或翻译】See how a group of leading developers use GPT-5 for the first time.
【RSS 原文 · 未经 AI 筛选或翻译】此订阅未提供摘要,请通过原文链接阅读。
【RSS 原文 · 未经 AI 筛选或翻译】This GPT-5 system card explains how a unified model routing system powers fast and smart responses using gpt-5-main, gpt-5-thinking, and lightweight versions like gpt-5-thinking-nano, optimized for different tasks and developer use.