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Pi-hole makes use of a modified dnsmasq called FTLDNS, [13] cURL, lighttpd, PHP and the AdminLTE Dashboard [14] to block DNS requests for known tracking and advertising domains. The application acts as a DNS server for a private network (replacing any pre-existing DNS server provided by another device or the ISP ), with the ability to block ...
The GPT Store is a platform developed by OpenAI that enables users and developers to create, publish, and monetize GPTs without requiring advanced programming skills. GPTs are custom applications built using the artificial intelligence chatbot known as ChatGPT .
Generative Pre-trained Transformer 2 (GPT-2) is a large language model by OpenAI and the second in their foundational series of GPT models. GPT-2 was pre-trained on a dataset of 8 million web pages. [2] It was partially released in February 2019, followed by full release of the 1.5-billion-parameter model on November 5, 2019. [3] [4] [5]
ChatGPT is a generative artificial intelligence chatbot [2] [3] developed by OpenAI and launched in 2022. It is currently based on the GPT-4o large language model (LLM). ChatGPT can generate human-like conversational responses and enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. [4]
A chatbot (originally chatterbot) [1] is a software application or web interface designed to have textual or spoken conversations. [2] [3] [4] Modern chatbots are typically online and use generative artificial intelligence systems that are capable of maintaining a conversation with a user in natural language and simulating the way a human would behave as a conversational partner.
An application programming interface (API) key is a secret unique identifier used to authenticate and authorize a user, developer, or calling program to an API. [1] [2]Cloud computing providers such as Google Cloud Platform and Amazon Web Services recommend that API keys only be used to authenticate projects, rather than human users.
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.
The first GPT model was known as "GPT-1," and it was followed by "GPT-2" in February 2019. Created as a direct scale-up of its predecessor, GPT-2 had both its parameter count and dataset size increased by a factor of 10. It had 1.5 billion parameters, and was trained on a dataset of 8 million web pages. [9]