Skillful AI Public Docs v1
Skillful AI Public Docs v0.1
Skillful AI Public Docs v0.1
  • 👋Getting Started with Skillful
    • 😤TL;DR
  • Overview
    • 🤖Popular AI Models and how they work
      • 🖥️Large Language Models: Understanding Different Architectures
      • 💻Upcoming types of models people should be excited for
    • 💡What we do
    • ✨Our Features
    • 🦾Decentralization and AI
    • 🤝Partners & Backers
      • 📰Featured Press
  • Products
    • 🛠️Ecosystem Overview
    • 👨‍🏫AI Suite
      • 📊Analytics and Data
      • 🛠️Traits, Add-Ons, and Tools
    • 📈AI Marketplace
    • 🏗️AI Creator
    • ⚖️DAO voting data sets
    • 🛡️Skillful Wallet - Integration
  • Uses
    • 👁️‍🗨️Use Cases
      • 💆For Users
      • 👨‍💻For Developers
  • Memory and Controlling your data
    • 🧠Memory Solutions and User Data
      • Memory Solution
      • Data Ownership
  • Links & Glossary
    • ⛓️Links & Social's
    • 📚Glossary
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  1. Memory and Controlling your data
  2. Memory Solutions and User Data

Memory Solution

PreviousMemory Solutions and User DataNextData Ownership

Last updated 1 year ago

The majority of the weightings will be frozen after we have trained the model to fit into a "Domain specific" area (Specificity). Some of the weighting will remain free to change, around 15-20% estimated on average. This is represented in Yellow bellow:

This is where the personalization comes from - Your interactions will be stored as memories using the decoder model () along with modifying specific traits (These "traits" are used to give context to answers, think tone of voice).

A robust and accurate "memory" system is vital to allowing the level of personalization and specialty we will have in our models. The exact details and specifics for this will be released when we publish our developer documents. Early access developers will have more insight to allow them to fully test the system. See the whitepaper on our website for more information regarding this

🧠
See Data Ownership
https://skillfulai.io/