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  2. Binary-to-text encoding - Wikipedia

    en.wikipedia.org/wiki/Binary-to-text_encoding

    The ASCII text-encoding standard uses 7 bits to encode characters. With this it is possible to encode 128 (i.e. 2 7) unique values (0–127) to represent the alphabetic, numeric, and punctuation characters commonly used in English, plus a selection of Control characters which do not represent printable characters.

  3. Base64 - Wikipedia

    en.wikipedia.org/wiki/Base64

    Because Base64 is a six-bit encoding, and because the decoded values are divided into 8-bit octets, every four characters of Base64-encoded text (4 sextets = 4 × 6 = 24 bits) represents three octets of unencoded text or data (3 octets = 3 × 8 = 24 bits). This means that when the length of the unencoded input is not a multiple of three, the ...

  4. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.

  5. T5 (language model) - Wikipedia

    en.wikipedia.org/wiki/T5_(language_model)

    T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.

  6. Comparison of data-serialization formats - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_data...

    For example, PKIX uses such notation in RFC 5912. With such notation (constraints on parameterized types using information object sets), generic ASN.1 tools/libraries can automatically encode/decode/resolve references within a document. ^ The primary format is binary, a json encoder is available. [10]

  7. Autoencoder - Wikipedia

    en.wikipedia.org/wiki/Autoencoder

    An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation. The autoencoder learns an efficient representation (encoding) for a set of data, typically for dimensionality reduction , to generate lower-dimensional embeddings for ...

  8. OpenAI Codex - Wikipedia

    en.wikipedia.org/wiki/OpenAI_Codex

    OpenAI Codex is an artificial intelligence model developed by OpenAI. It parses natural language and generates code in response. It powers GitHub Copilot, a programming autocompletion tool for select IDEs, like Visual Studio Code and Neovim. [1] Codex is a descendant of OpenAI's GPT-3 model, fine-tuned for use in programming applications.

  9. List of programming languages for artificial intelligence

    en.wikipedia.org/wiki/List_of_programming...

    Python is a high-level, general-purpose programming language that is popular in artificial intelligence. [1] It has a simple, flexible and easily readable syntax. [2] Its popularity results in a vast ecosystem of libraries, including for deep learning, such as PyTorch, TensorFlow, Keras, Google JAX.