Search results
Results from the WOW.Com Content Network
This is especially important if you are going to allow clones of your bot. Ideally, you should post the source code of your bot on its userpage or in a revision control system (see #Open-source bots) if you want others to be able to run clones of it. This code should be well documented (usually using comments) for ease of use.
Grok is a generative artificial intelligence chatbot developed by xAI. Based on the large language model (LLM) of the same name, it was launched in 2023 as an initiative by Elon Musk. [3] The chatbot is advertised as having a "sense of humor" and direct access to X, formerly known as Twitter. [4] [5]
ChatGPT is a generative artificial intelligence chatbot 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. [2]
"This week, @xAI will open source Grok," Musk said in a post on X, the social media firm he owns. ... Elon Musk takes another swing at OpenAI, makes xAI's Grok chatbot open-source. March 11, 2024 ...
They all have 16K context lengths. The model was made source-available under the DeepSeek License, which includes "open and responsible downstream usage" restrictions. [47] The training program was: [48] [49] [50] Pretraining: 1.8T tokens (87% source code, 10% code-related English (GitHub markdown and Stack Exchange), and 3% code-unrelated ...
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.
Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share. [1] These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development. [1]
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.