A Machine Teaching Schema: JSON-AI

The following are JSON-AI Object Types. To see an implementation of JSON-AI using GraphQL’s Schema Definition Language, see our GraphQL post.

@i.agent

• An agent is any api service, this is used to define an agent and all of the API information needed to communicate with it.

{
  id: "Apollo",
  description: "GraphQL Server",
  request: {
    timestamp: "Nov 3 2018",
    url:"localhost:8001",
    method:"GraphQL",
    query:"/api",
    data: "JSON goes here"
  }
}

@i.concept

• A phrase and all of it’s possible word contexts that could be represented in a word vector. In the phrase “Board Report”, the word “Board” is referring to a Charter School Board and this is described as such:

{
  id: "Board",
  contexts: [
    { id:"Charter School Board" },
    { id: "Corporate Board" }
  ]
}

@i.documents

{
    id:"Machine Teaching",
    url: "https://medium.com/@ron_69694/machine-teaching-knowledge-snippets-98fcc01a4f79",
    knowledge: [
      {
        id:"our first snippet",
        concepts: [
          { id: "JSON-AI" },
          { id: "Machine Teaching Concepts" },
          { id: "Machine Learning Research" }
        ],
        elements: [
          {
            id:"paragraph #",
            label: "Definition 2.1",
            sentences:[ 
              { 
                id: "1", 
                text: "Definition 2.1 (Machine learning research) Machine Learning research aims at making the learner better by improving ML algorithms."
              }, 
              { 
                id: "2", 
                text: "This field covers, for instance, any new variations or breakthroughs in deep learning, unsupervised learning, recurrent networks, convex optimization, and so on."
              }, 
              { 
                id: "3", 
                text: "Conversely, we see version control, concept decomposition, semantic data exploration, expressiveness of the teaching language, interpretability of the model, and productivity as having more in common with programming and human-computer interaction than with machine learning."
              }, 
              { 
                id: "4", 
                text: "These \“machine teaching\” concepts, however, are extraordinarily important to any practitioners of machine learning."
              }, 
              { 
                id: "4", 
                text: "These \“machine teaching\” concepts, however, are extraordinarily important to any practitioners of machine learning."
              },                                                 
            ]
          }
        ]
      }
    ]
  }

@i.hero

• A human agent, a ‘user’ in industry term.

{
  id: "1242",
  firstName: "Bilbo",
  lastName: "Baggins"
}

@i.story

• What connects heroes, agents, and knowledge together.

{
    id: "_origin",
    epochs: [
      {
        id:"epoch 1",
        heroes: heroes,
        documents: documents,
        agents: agents
      }
    ]
  }

For more information:

Schema Driven Design: JSON-AI, GraphQl, and Neo4j

JSON-AI Hero Feedback Rating System

JSON-AI is a schema for Machine Teaching

Constellation

Machine Teaching Knowledge Snippets

Introducing JSON-AI

Intelligence.AI