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  2. yEnc - Wikipedia

    en.wikipedia.org/wiki/YEnc

    yEnc is a binary-to-text encoding scheme for transferring binary files in messages on Usenet or via e-mail.It reduces the overhead over previous US-ASCII-based encoding methods by using an 8-bit encoding method. yEnc's overhead is often (if each byte value appears approximately with the same frequency on average) as little as 1–2%, [1] compared to 33–40% overhead for 6-bit encoding methods ...

  3. Binary XML - Wikipedia

    en.wikipedia.org/wiki/Binary_XML

    Binary XML is typically used in applications where the performance of standard XML is insufficient, but the ability to convert the document to and from a form (XML) which is easily viewed and edited is valued. Other advantages may include enabling random access and indexing of XML documents. The major challenge for binary XML is to create a ...

  4. Fast syndrome-based hash - Wikipedia

    en.wikipedia.org/wiki/Fast_syndrome-based_hash

    The basis of this function consists of a (randomly chosen) binary matrix which acts on a message of bits by matrix multiplication. Here we encode the w log ⁡ ( n / w ) {\displaystyle w\log(n/w)} -bit message as a vector in ( F 2 ) n {\displaystyle (\mathbf {F} _{2})^{n}} , the n {\displaystyle n} -dimensional vector space over the field of ...

  5. Chrome can soon convert PDFs into text it can read aloud

    www.engadget.com/chrome-can-soon-convert-pdfs...

    The company is adding OCR (optical character recognition) technology to Chrome that can convert PDFs to text that makes them more accessible, particularly if you want a screen reader to read them ...

  6. BERT (language model) - Wikipedia

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

    Unlike previous models, BERT is a deeply bidirectional, unsupervised language representation, pre-trained using only a plain text corpus. Context-free models such as word2vec or GloVe generate a single word embedding representation for each word in the vocabulary, whereas BERT takes into account the context for each occurrence of a given word ...