MITR.

Mobile Interpreter & Telecom Responder

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DEMO

My Eden AI is not only a platform for innovation but it also inspires the minds of our generation to transform this world better than imagination, and thoughts into action for the betterment and advancement of AI and the development of society, humanity, and Earth as a whole.

Roadmap

  1. Beginning

    2022

    Generation 49.0

  2. Learning

    2022

    Generation 49.0

  3. Protocols

    2023

    Generation 49.0

  4. API

    2023

    Generation 52.0

  5. Model Updation

    2023

    Generation 53.0

Engines

CHAT LEKH

  • 8K Context : $0.06 / 1K tokens
  • 32K context : $0.12 / 1K tokens

Image KALA

  • 1024x1024 : $0.020 / image
  • 512x512 : $0.018 / image
  • 256x256 : $0.016 / image

Audio VANI

  • Voiceover : $0.016 / min (rounded to the nearest)
  • Dubbing : $0.16 / min (rounded to the nearest)
  • Sales : $1 / min (rounded to the nearest)

Research

ACT Model has 301 neurons which actually utilizes processing also the neuron based on data compression (MAKES EACH NEURON A INPUT NEURON) which also stores learned reference data in symbolic representation consisting of 6 symbols along with relative weights which makes her turing complete and the entire vast model is stored in a in-memory vector database which only uses index adjustment based on new learning and is static which makes her use less compute but utilizes more memory (RAM).

Limitations

ACT Model has 301 neurons which actually utilizes processing also the neuron based on data compression (MAKES EACH NEURON A INPUT NEURON) which also stores learned reference data in symbolic representation consisting of 6 symbols along with relative weights which makes her turing complete and the entire vast model is stored in a in-memory vector database which only uses index adjustment based on new learning and is static which makes her use less compute but utilizes more memory (RAM).

Training

ACT Model has 301 neurons which actually utilizes processing also the neuron based on data compression (MAKES EACH NEURON A INPUT NEURON) which also stores learned reference data in symbolic representation consisting of 6 symbols along with relative weights which makes her turing complete and the entire vast model is stored in a in-memory vector database which only uses index adjustment based on new learning and is static which makes her use less compute but utilizes more memory (RAM).

FAQ

This is the first item's accordion body. It is shown by default, until the collapse plugin adds the appropriate classes that we use to style each element. These classes control the overall appearance, as well as the showing and hiding via CSS transitions. You can modify any of this with custom CSS or overriding our default variables. It's also worth noting that just about any HTML can go within the .accordion-body, though the transition does limit overflow.

This is the second item's accordion body. It is hidden by default, until the collapse plugin adds the appropriate classes that we use to style each element. These classes control the overall appearance, as well as the showing and hiding via CSS transitions. You can modify any of this with custom CSS or overriding our default variables. It's also worth noting that just about any HTML can go within the .accordion-body, though the transition does limit overflow.

This is the third item's accordion body. It is hidden by default, until the collapse plugin adds the appropriate classes that we use to style each element. These classes control the overall appearance, as well as the showing and hiding via CSS transitions. You can modify any of this with custom CSS or overriding our default variables. It's also worth noting that just about any HTML can go within the .accordion-body, though the transition does limit overflow.
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