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Undetectable AI (or Undetectable.ai) is an artificial intelligence content detection and modification software designed to identify and alter artificially generated text, such as that produced by large language models.
A prompt is natural language text describing the task that an AI should perform. [2] A prompt for a text-to-text language model can be a query, a command, or a longer statement including context, instructions, and conversation history. Prompt engineering may involve phrasing a query, specifying a style, choice of words and grammar, [3 ...
In the context of AI, it is particularly used for embedded systems and robotics. Libraries such as TensorFlow C++, Caffe or Shogun can be used. [1] JavaScript is widely used for web applications and can notably be executed with web browsers. Libraries for AI include TensorFlow.js, Synaptic and Brain.js. [6]
For example, in 2017, Google researchers used the term to describe the responses generated by neural machine translation (NMT) models when they are not related to the source text, [22] and in 2018, the term was used in computer vision to describe instances where non-existent objects are erroneously detected because of adversarial attacks.
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.
[4] [5] The difference between these and NLP is that the latter builds up a single program or a library of routines that are programmed through natural language sentences using an ontology that defines the available data structures in a high level programming language. An example text from an English language natural-language program is as follows:
Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 2 ] [ 3 ] [ 4 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 5 ] [ 6 ] based on ...
Many real-world applications fall between the two extremes, for instance text classification for the automatic analysis of emails and their routing to a suitable department in a corporation does not require an in-depth understanding of the text, [22] but needs to deal with a much larger vocabulary and more diverse syntax than the management of ...