LEKH.

lexical editing knowledge hive

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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

NYAYA Legals

  • Laws : Indian Constitution
  • Legals : IPCs

GYANA Spiritual

  • Vedas : All Vedas
  • Purana : All Puranas
  • Astrology : Kundli, Numerology, Predictions

KHETI Farming

  • Krishi Vigyan : Vedic
  • Farming : Techniques, Organic, Hybrid
  • Agriculture : Studies, Research

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

LEKH is accessible via APIs. If you are a business, we can develop customized apps or integrate our APIs into your resources for solving your problems.

Contact Sales. We have not released the public APIs for LEKH, however one can integrate it for B2B solutions.

LEKH can be used for educational and learning purpose. Our engine is capable of decision making and real time learning. We have already trained LEKH engine for Engineering, Architecture, Farming, Indian Laws etc. and the list is increasing day by day.

LEKH uses a real time learning engine based on our very own ACT Model. Unlike chatgpt we can easily train EDEN in real time for specific purpose like Engineering, Calculations, Decoding etc.

LEKH can be trained for any kind of data. Businesses can train LEKH for any subjects or statistics data they want.
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