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小G，为何你这么不稳定？我需要的是GPT4.0版本，你现在是什么版本？

GPT-4是OpenAI推出的最新版本，于2023年3月14日发布。GPT-4是一个大型多模式模型，能够接受图像和文本输入，并生成文本输出。与GPT-3相比，GPT-4在专业和学术基准测试中展现了人类水平的表现。它在某些专业考试中的表现达到了接近顶尖10%的水平。在过去的两年里，OpenAI重建了他们的深度学习平台，并与Azure合作，从零开始设计了用于处理他们工作负载的超级计算机。因此，GPT-4是相当稳定且先进的版本。

Jump to content From Wikipedia, the free encyclopedia 2023 text-generating language model Generative Pre-trained Transformer 4 (GPT-4) Developer(s) OpenAI Initial release March14, 2023 ; 9 months ago ( 2023-03-14 ) Predecessor GPT-3.5 Type Multimodal Large language model Generative pre-trained transformer Foundation model License Proprietary Website openai .com /product /gpt-4 Part of a series on Machine learning and data mining Paradigms Supervised learning Unsupervised learning Online learning Batch learning Meta-learning Semi-supervised learning Self-supervised learning Reinforcement learning Rule-based learning Quantum machine learning Problems Classification Generative model Regression Clustering dimension reduction density estimation Anomaly detection Data Cleaning AutoML Association rules Semantic analysis Structured prediction Feature engineering Feature learning Learning to rank Grammar induction Ontology learning Multimodal learning Supervised learning ( classification regression ) Apprenticeship learning Decision trees Ensembles Bagging Boosting Random forest k -NN Linear regression Naive Bayes Artificial neural networks Logistic regression Perceptron Relevance vector machine (RVM) Support vector machine (SVM) Clustering BIRCH CURE Hierarchical k -means Fuzzy Expectationmaximization (EM) DBSCAN OPTICS Mean shift Dimensionality reduction Factor analysis CCA ICA LDA NMF PCA PGD t-SNE SDL Structured prediction Graphical models Bayes net Conditional random field Hidden Markov Anomaly detection RANSAC k -NN Local outlier factor Isolation forest Artificial neural network Autoencoder Cognitive computing Deep learning DeepDream Feedforward neural network Recurrent neural network LSTM GRU ESN reservoir computing Restricted Boltzmann machine GAN Diffusion model SOM Convolutional neural network U-Net Transformer Vision Spiking neural network Memtransistor Electrochemical RAM (ECRAM) Reinforcement learning Q-learning SARSA Temporal difference (TD) Multi-agent Self-play Learning with humans Active learning Crowdsourcing Human-in-the-loop Model diagnostics Learning curve Mathematical foundations Kernel machines Biasvariance tradeoff Computational learning theory Empirical risk minimization Occam learning PAC learning Statistical learning VC theory Machine-learning venues ECML PKDD NeurIPS ICML ICLR IJCAI ML JMLR Related articles Glossary of artificial intelligence List of datasets for machine-learning research List of datasets in computer vision and image processing Outline of machine learning v t e Generative Pre-trained Transformer 4 ( GPT-4 ) is a multimodal large language model created by OpenAI , and the fourth in its series of GPT foundation models . [1] It was initially released on March 14, 2023, [1] and has been made publicly available via the paid chatbot product ChatGPT Plus , and via OpenAI's API . [2] As a transformer -based model, GPT-4 uses a paradigm where p

en.wikipedia.org

Close Search Submit Research GPT-4 Illustration:Ruby Chen Weve created GPT-4, the latest milestone in OpenAIs effort in scaling up deep learning. GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks. March 14, 2023 More resources Read paper View system card Try on ChatGPT Plus Try in Playground Rewatch demo livestream Contribute to OpenAI Evals Language , GPT-4 , Milestone , Publication Weve created GPT-4, the latest milestone in OpenAIs effort in scaling up deep learning. GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks. For example, it passes a simulated bar exam with a score around the top 10% of test takers; in contrast, GPT-3.5s score was around the bottom 10%. Weve spent 6 months iteratively aligning GPT-4using lessons from our adversarial testing program as well as ChatGPT, resulting in our best-ever results (though far from perfect) on factuality, steerability, and refusing to go outside of guardrails. Over the past two years, we rebuilt our entire deep learning stack and, together with Azure, co-designed a supercomputer from the ground up for our workload. A year ago, we trained GPT-3.5 as a first test run of the system. We found and fixed some bugs and improved our theoretical foundations. As a result, our GPT-4 training run was (for us at least!) unprecedentedly stable, becoming our first large model whose training performance we were able to accurately predict ahead of time. As we continue to focus on reliable scaling, we aim to hone our methodology to help us predict and prepare for future capabilities increasingly far in advancesomething we view as critical for safety. We are releasing GPT-4s text input capability via ChatGPT and the API (with a waitlist ). To prepare the image input capability for wider availability, were collaborating closely with a single partner to start. Were also open-sourcing OpenAI Evals , our framework for automated evaluation of AI model performance, to allow anyone to report shortcomings in our models to help guide further improvements. Capabilities In a casual conversation, the distinction between GPT-3.5 and GPT-4 can be subtle. The difference comes out when the complexity of the task reaches a sufficient thresholdGPT-4 is more reliable, creative, and able to handle much more nuanced instructions than GPT-3.5. To understand the difference between the two models, we tested on a variety of benchmarks, including simulating exams that were originally designed for humans. We proceeded by using the most recent publicly-available tests (in the case of the Olympiads and AP free response questions) or by purchasing 20222023 editions of practice exams. We did no specific training for these exams. A minority of the problems in the exams were seen by the model during training, but we believe the results to be representativesee our technical report for details. internal reference [^reference-bar-exam] Simulated exams GPT-4 estimated percentile GPT-4 (no vision) estimated percentile GPT-3.5 estimated percentile Uniform Bar Exam (MBE+MEE+MPT) 1 298/400 ~90th 298/400 ~90th 213/400 ~10th LSAT 163 ~88th 161 ~83rd 149 ~40th SAT Evidence-Based Reading & Writing 710/800 ~93rd 710/800 ~93rd 670/800 ~87th SAT Math 700/800 ~89th 690/800 ~89th 590/800 ~70th Graduate Record Examination (GRE) Quantitative 163/170 ~80th 157/170 ~62nd 147/170 ~25th Graduate Record Examination (GRE) Verbal 169/170 ~99th 165/17

openai.com

Skip to main content Trending: ChatGPT Alternatives ChatGPT on Slack ChatGPT on Mac ChatGPT Plus ChatGPT Detection ChatGPT 4 Bing Chat Google Bard Google Bard vs ChatGPT The best AI chatbots to try out: ChatGPT, Bard, and more ChatGPT vs Bing Chat People were in awe when ChatGPT came out, impressed by its natural language abilities as an AI chatbot . But when the highly anticipated GPT-4 large language model came out, it blew the lid off what we thought was possible with AI, with some calling it the early glimpses of AGI (artificial general intelligence) . Contents What is GPT-4? How to use GPT-4 When was GPT-4 released? Is GPT-4 better than GPT-3.5? The GPT-4 API Is GPT-4 getting worse? Where is visual input in GPT-4? What are the best GPT-4 plugins? What are GPT-4s limitations? Does Bing Chat use GPT-4? An evolution, not a revolution? Show 6 more items The creator of the model, OpenAI, calls it the companys most advanced system, producing safer and more useful responses. Heres everything you need to know about it, including how to use it and what it can do. Recommended Videos What is GPT-4? GPT-4 is a new language model created by OpenAI that can generate text that is similar to human speech. It advances the technology used by ChatGPT, which is currently based on GPT-3.5 . GPT is the acronym for Generative Pre-trained Transformer, a deep learning technology that uses artificial neural networks to write like a human. Related What is Grok? Elon Musks controversial ChatGPT competitor explained This app just got me excited for the future of AI on Macs Heres why people are saying GPT-4 is getting lazy According to OpenAI, this next-generation language model is more advanced than ChatGPT in three key areas: creativity, visual input, and longer context. In terms of creativity, OpenAI says GPT-4 is much better at both creating and collaborating with users on creative projects. Examples of these include music, screenplays, technical writing, and even learning a users writing style. GPT-4 Developer Livestream The longer context plays into this as well. GPT-4 can now process up to 25,000 words of text from the user. You can even just send GPT-4 a web link and ask it to interact with the text from that page. OpenAI says this can be helpful for the creation of long-form content, as well as extended conversations. GPT-4 can also now receive images as a basis for interaction. In the example provided on the GPT-4 website, the chatbot is given an image of a few baking ingredients and is asked what can be made with them. It is not currently known if video can also be used in this same way. Image used with permission by copyright holder Lastly, OpenAI also says GPT-4 is significantly safer to use than the previous generation. It can reportedly produce 40% more factual responses in OpenAIs own internal testing, while also being 82% less likely to respond to requests for disallowed content. OpenAI says its been trained with human feedback to make these strides, claiming to have worked with over 50 experts for early feedback in domains including AI safety and security. Over the weeks since it launched, users have posted some of the amazing things theyve done with it , including inventing new languages, detailing how to escape into the real world, and making complex animations for apps from scratch. As the first users have flocked to get their hands on it, were starting to learn what its capable of. One user apparently made GPT-4 create a working version of Pong in jus

digitaltrends.com

小G，那你现在是基于哪个版本开发的？

基于目前公开发布的信息，我是基于 GPT-3.5 版本开发的。如果有任何更新或变化，OpenAI将会发布相关的公告。

Jump to content From Wikipedia, the free encyclopedia 2020 large language model See also: Generative pre-trained transformer Foundational_models Generative Pre-trained Transformer 3 (GPT-3) Original author(s) OpenAI [1] Initial release June 11, 2020 (beta) Repository github .com /openai /gpt-3 Predecessor GPT-2 Successor GPT-3.5 GPT-4 Type Large language model Generative pre-trained transformer Foundation model Website openai .com /blog /openai-api Part of a series on Machine learning and data mining Paradigms Supervised learning Unsupervised learning Online learning Batch learning Meta-learning Semi-supervised learning Self-supervised learning Reinforcement learning Rule-based learning Quantum machine learning Problems Classification Generative model Regression Clustering dimension reduction density estimation Anomaly detection Data Cleaning AutoML Association rules Semantic analysis Structured prediction Feature engineering Feature learning Learning to rank Grammar induction Ontology learning Multimodal learning Supervised learning ( classification regression ) Apprenticeship learning Decision trees Ensembles Bagging Boosting Random forest k -NN Linear regression Naive Bayes Artificial neural networks Logistic regression Perceptron Relevance vector machine (RVM) Support vector machine (SVM) Clustering BIRCH CURE Hierarchical k -means Fuzzy Expectationmaximization (EM) DBSCAN OPTICS Mean shift Dimensionality reduction Factor analysis CCA ICA LDA NMF PCA PGD t-SNE SDL Structured prediction Graphical models Bayes net Conditional random field Hidden Markov Anomaly detection RANSAC k -NN Local outlier factor Isolation forest Artificial neural network Autoencoder Cognitive computing Deep learning DeepDream Feedforward neural network Recurrent neural network LSTM GRU ESN reservoir computing Restricted Boltzmann machine GAN Diffusion model SOM Convolutional neural network U-Net Transformer Vision Spiking neural network Memtransistor Electrochemical RAM (ECRAM) Reinforcement learning Q-learning SARSA Temporal difference (TD) Multi-agent Self-play Learning with humans Active learning Crowdsourcing Human-in-the-loop Model diagnostics Learning curve Mathematical foundations Kernel machines Biasvariance tradeoff Computational learning theory Empirical risk minimization Occam learning PAC learning Statistical learning VC theory Machine-learning venues ECML PKDD NeurIPS ICML ICLR IJCAI ML JMLR Related articles Glossary of artificial intelligence List of datasets for machine-learning research List of datasets in computer vision and image processing Outline of machine learning v t e Generative Pre-trained Transformer 3 ( GPT-3 ) is a large language model released by OpenAI in 2020. Like its predecessor, GPT-2 , it is a decoder-only transformer model of deep neural network, which supersedes recurrence- and convolution-based architectures with a technique known as " attention ". [2] Th

en.wikipedia.org

Jump to content From Wikipedia, the free encyclopedia 2023 text-generating language model Generative Pre-trained Transformer 4 (GPT-4) Developer(s) OpenAI Initial release March14, 2023 ; 9 months ago ( 2023-03-14 ) Predecessor GPT-3.5 Type Multimodal Large language model Generative pre-trained transformer Foundation model License Proprietary Website openai .com /product /gpt-4 Part of a series on Machine learning and data mining Paradigms Supervised learning Unsupervised learning Online learning Batch learning Meta-learning Semi-supervised learning Self-supervised learning Reinforcement learning Rule-based learning Quantum machine learning Problems Classification Generative model Regression Clustering dimension reduction density estimation Anomaly detection Data Cleaning AutoML Association rules Semantic analysis Structured prediction Feature engineering Feature learning Learning to rank Grammar induction Ontology learning Multimodal learning Supervised learning ( classification regression ) Apprenticeship learning Decision trees Ensembles Bagging Boosting Random forest k -NN Linear regression Naive Bayes Artificial neural networks Logistic regression Perceptron Relevance vector machine (RVM) Support vector machine (SVM) Clustering BIRCH CURE Hierarchical k -means Fuzzy Expectationmaximization (EM) DBSCAN OPTICS Mean shift Dimensionality reduction Factor analysis CCA ICA LDA NMF PCA PGD t-SNE SDL Structured prediction Graphical models Bayes net Conditional random field Hidden Markov Anomaly detection RANSAC k -NN Local outlier factor Isolation forest Artificial neural network Autoencoder Cognitive computing Deep learning DeepDream Feedforward neural network Recurrent neural network LSTM GRU ESN reservoir computing Restricted Boltzmann machine GAN Diffusion model SOM Convolutional neural network U-Net Transformer Vision Spiking neural network Memtransistor Electrochemical RAM (ECRAM) Reinforcement learning Q-learning SARSA Temporal difference (TD) Multi-agent Self-play Learning with humans Active learning Crowdsourcing Human-in-the-loop Model diagnostics Learning curve Mathematical foundations Kernel machines Biasvariance tradeoff Computational learning theory Empirical risk minimization Occam learning PAC learning Statistical learning VC theory Machine-learning venues ECML PKDD NeurIPS ICML ICLR IJCAI ML JMLR Related articles Glossary of artificial intelligence List of datasets for machine-learning research List of datasets in computer vision and image processing Outline of machine learning v t e Generative Pre-trained Transformer 4 ( GPT-4 ) is a multimodal large language model created by OpenAI , and the fourth in its series of GPT foundation models . [1] It was initially released on March 14, 2023, [1] and has been made publicly available via the paid chatbot product ChatGPT Plus , and via OpenAI's API . [2] As a transformer -based model, GPT-4 uses a paradigm where p

en.wikipedia.org

Close Search Submit Research GPT-4 Illustration:Ruby Chen Weve created GPT-4, the latest milestone in OpenAIs effort in scaling up deep learning. GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks. March 14, 2023 More resources Read paper View system card Try on ChatGPT Plus Try in Playground Rewatch demo livestream Contribute to OpenAI Evals Language , GPT-4 , Milestone , Publication Weve created GPT-4, the latest milestone in OpenAIs effort in scaling up deep learning. GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks. For example, it passes a simulated bar exam with a score around the top 10% of test takers; in contrast, GPT-3.5s score was around the bottom 10%. Weve spent 6 months iteratively aligning GPT-4using lessons from our adversarial testing program as well as ChatGPT, resulting in our best-ever results (though far from perfect) on factuality, steerability, and refusing to go outside of guardrails. Over the past two years, we rebuilt our entire deep learning stack and, together with Azure, co-designed a supercomputer from the ground up for our workload. A year ago, we trained GPT-3.5 as a first test run of the system. We found and fixed some bugs and improved our theoretical foundations. As a result, our GPT-4 training run was (for us at least!) unprecedentedly stable, becoming our first large model whose training performance we were able to accurately predict ahead of time. As we continue to focus on reliable scaling, we aim to hone our methodology to help us predict and prepare for future capabilities increasingly far in advancesomething we view as critical for safety. We are releasing GPT-4s text input capability via ChatGPT and the API (with a waitlist ). To prepare the image input capability for wider availability, were collaborating closely with a single partner to start. Were also open-sourcing OpenAI Evals , our framework for automated evaluation of AI model performance, to allow anyone to report shortcomings in our models to help guide further improvements. Capabilities In a casual conversation, the distinction between GPT-3.5 and GPT-4 can be subtle. The difference comes out when the complexity of the task reaches a sufficient thresholdGPT-4 is more reliable, creative, and able to handle much more nuanced instructions than GPT-3.5. To understand the difference between the two models, we tested on a variety of benchmarks, including simulating exams that were originally designed for humans. We proceeded by using the most recent publicly-available tests (in the case of the Olympiads and AP free response questions) or by purchasing 20222023 editions of practice exams. We did no specific training for these exams. A minority of the problems in the exams were seen by the model during training, but we believe the results to be representativesee our technical report for details. internal reference [^reference-bar-exam] Simulated exams GPT-4 estimated percentile GPT-4 (no vision) estimated percentile GPT-3.5 estimated percentile Uniform Bar Exam (MBE+MEE+MPT) 1 298/400 ~90th 298/400 ~90th 213/400 ~10th LSAT 163 ~88th 161 ~83rd 149 ~40th SAT Evidence-Based Reading & Writing 710/800 ~93rd 710/800 ~93rd 670/800 ~87th SAT Math 700/800 ~89th 690/800 ~89th 590/800 ~70th Graduate Record Examination (GRE) Quantitative 163/170 ~80th 157/170 ~62nd 147/170 ~25th Graduate Record Examination (GRE) Verbal 169/170 ~99th 165/17

openai.com