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  2. Braina - Wikipedia

    en.wikipedia.org/wiki/Braina

    Braina is a virtual assistant [1] [2] and speech-to-text dictation [3] application for Microsoft Windows developed by Brainasoft. [4] Braina uses natural language interface, [5] speech synthesis, and speech recognition technology [6] to interact with its users and allows them to use natural language sentences to perform various tasks on a computer.

  3. ChatGPT - Wikipedia

    en.wikipedia.org/wiki/ChatGPT

    ChatGPT is a generative artificial intelligence chatbot [2] [3] 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. [4]

  4. Microsoft adds new Copilot features to Windows 11 as AI hype ...

    www.aol.com/finance/microsoft-adds-copilot...

    Microsoft is bringing more generative AI capabilities to Windows 11 with a new update for the operating system.Available today, the upgrade will add more functionality to Copilot in Windows 11 ...

  5. Claude (language model) - Wikipedia

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

    Claude is a family of large language models developed by Anthropic. [1] [2] The first model was released in March 2023.The Claude 3 family, released in March 2024, consists of three models: Haiku optimized for speed, Sonnet balancing capabilities and performance, and Opus designed for complex reasoning tasks.

  6. Ask Andy: Can generative AI solve a startup’s problems?

    www.aol.com/finance/ask-andy-generative-ai-solve...

    The magnetic, mission-driven zeal that is bedrock to raising venture capital seems to be a hard thing to imagine even generative AI (whatever that is) being able to replicate. Then I thought about ...

  7. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...