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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 ...
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.
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]
GPT-4o ("o" for "omni") is a multilingual, multimodal generative pre-trained transformer developed by OpenAI and released in May 2024. [1] GPT-4o is free, but ChatGPT Plus subscribers have higher usage limits. [ 2 ]
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] GPT-2 was created as a "direct scale-up" of GPT-1 [6] with a ten-fold increase in both its parameter count and the size of its training dataset. [5]
Generative Pre-trained Transformer 3.5 (GPT-3.5) is a sub class of GPT-3 Models created by OpenAI in 2022. On March 15, 2022, OpenAI made available new versions of GPT-3 and Codex in its API with edit and insert capabilities under the names "text-davinci-002" and "code-davinci-002". [28]
This sequence is used as an encryption key at one end of communication, and as a decryption key at the other. One can implement a key generator in a system that aims to generate, distribute, and authenticate [4] keys in a way that without the private key, one cannot access the information in the public end. [5]
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.