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  2. Melanie Perkins - Wikipedia

    en.wikipedia.org/wiki/Melanie_Perkins

    After that email, he agreed to join Canva, becoming its third founder and chief product officer. [17] Perkins is the CEO of one of the few ‘unicorn’ start-ups that are profitable. [19] In Nov. 2023, Forbes estimated her net worth at $ 3.6 bln. She remained CEO of Canva, and owned around 18 % of the company. [20]

  3. QR code - Wikipedia

    en.wikipedia.org/wiki/QR_Code

    The QR code system was invented in 1994, at the Denso Wave automotive products company, in Japan. [5] [6] [7] The initial alternating-square design presented by the team of researchers, headed by Masahiro Hara, was influenced by the black counters and the white counters played on a Go board; [8] the pattern of position detection was found and determined by applying the least-used ratio (1:1:3 ...

  4. Application Code for E-Ticket? - Punta Cana Forum - Tripadvisor

    www.tripadvisor.com/ShowTopic-g147293-i28-k...

    There's no payment, it is free as long as you're in the correct site. You shouldn't need a copy or even the QR as it's linked to your passport number. Personally I print it (bit of a dinosaur). There's a different application code on the return E-ticket, not one I recall being stuck in my face for noting when I did that 2nd stage of applying.

  5. MeCard (QR code) - Wikipedia

    en.wikipedia.org/wiki/MeCard_(QR_code)

    MeCard (QR code) MeCard is a data file similar to vCard but used by NTT DoCoMo in Japan in QR code format for use with Cellular Phones. It is largely compatible with most QR-readers for smartphones. It is an easy way to share a contact with the most used fields. Usually, devices can recognize it and treat it like a contact ready to import.

  6. QR code for my property - Tripadvisor Support Forum

    www.tripadvisor.com/ShowTopic-g1-i12105-k...

    Various Contacts for TA Staff; FORUMS - Contact TA Staff about Forum issues; Forum Posting Guidelines; Reporting Technical Issues to TA Staff; Account Issues - Contact TA Staff

  7. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval augmented generation (RAG) is a type of information retrieval process. It modifies interactions with a large language model (LLM) so that it responds to queries with reference to a specified set of documents, using it in preference to information drawn from its own vast, static training data.

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