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OpenAI's mission, which is to ensure artificial general intelligence (AGI), benefits all people. This refers to highly autonomous systems that outperform humans in most economically valuable work. While we will try to build safe and useful AGI, we will also consider our mission accomplished if others are able to do the same. Our API can be used to perform any language task, including summarization, sentiment analysis and content generation. You can specify your task in English or use a few examples. Our constantly improving AI technology is available to you with a simple integration. These sample completions will show you how to integrate with the API.
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Claude is an artificial intelligence language model that can generate text with human-like processing. Anthropic is an AI safety company and research firm that focuses on building reliable, interpretable and steerable AI systems. While large, general systems can provide significant benefits, they can also be unpredictable, unreliable and opaque. Our goal is to make progress in these areas. We are currently focusing on research to achieve these goals. However, we see many opportunities for our work in the future to create value both commercially and for the public good.
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Perplexity
Perplexity AI
Free 3 RatingsWhere does knowledge begin? Perplexity AI is a search engine that provides quick answers. Available for free on perplexity.ai, or on iPhone or Android. Perplexity AI, an advanced search tool and question-answering system, uses large language models to provide contextually relevant and accurate answers to user queries. It is designed for both general and specific inquiries. It combines AI with real-time searching capabilities to retrieve and synthesize data from a variety of sources. Perplexity AI focuses on ease of use and transparency. It often provides citations or links directly to its sources. Its goal to streamline the process of information discovery while maintaining high accuracy, clarity, and precision in its responses. This makes it a valuable tool both for researchers and professionals. -
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ChatGPT is an OpenAI language model. It can generate human-like responses to a variety prompts, and has been trained on a wide range of internet texts. ChatGPT can be used to perform natural language processing tasks such as conversation, question answering, and text generation. ChatGPT is a pretrained language model that uses deep-learning algorithms to generate text. It was trained using large amounts of text data. This allows it to respond to a wide variety of prompts with human-like ease. It has a transformer architecture that has been proven to be efficient in many NLP tasks. ChatGPT can generate text in addition to answering questions, text classification and language translation. This allows developers to create powerful NLP applications that can do specific tasks more accurately. ChatGPT can also process code and generate it.
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GPT-4 (Generative Pretrained Transformer 4) a large-scale, unsupervised language model that is yet to be released. GPT-4, which is the successor of GPT-3, is part of the GPT -n series of natural-language processing models. It was trained using a dataset of 45TB text to produce text generation and understanding abilities that are human-like. GPT-4 is not dependent on additional training data, unlike other NLP models. It can generate text and answer questions using its own context. GPT-4 has been demonstrated to be capable of performing a wide range of tasks without any task-specific training data, such as translation, summarization and sentiment analysis.
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Stable Diffusion
Stability AI
$0.2 per imageWe have all been overwhelmed by the response over the past few weeks and have been hard at work to ensure a safe release. We have incorporated data from our beta models and community for developers to use. HuggingFace's tireless legal, technology and ethics teams and CoreWeave's brilliant engineers worked together. An AI-based Safety Classifier has been developed and is included as a default feature in the overall software package. This can understand concepts and other factors over generations to remove outputs that are not desired by the model user. This can be easily adjusted, and we welcome suggestions from the community on how to improve it. Although image generation models are powerful, we still need to improve our understanding of how to best represent what we want.
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