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How to build a thinking AI models

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How to build a thinking AI models

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How to build a thinking AI models

If you are interested in learning more about how to build thinking artificial intelligence AI models you might find this quick overview guide and video created by 4IR with David Shapiro extremely useful. The Autonomous Cognitive Entity (ACE) Framework is a groundbreaking approach to artificial intelligence (AI) that prioritizes cognition over input and output.

This cognition-first model of AI is designed to process and analyze information related to a wide range of topics, including education, inequality, poverty, and conflict resolution. The ACE Framework is a software blueprint that uses Language Learning Models (LLMs) and Language Model Models (LMMs) in a hierarchical manner, creating a unique and innovative approach to AI.

The ACE Framework operates in a top-down manner, starting with abstract, high-level goals and gradually becoming more specific as it moves down the layers. The first layer, known as the aspirational layer, is based on abstract universal principles such as the Universal Declaration of Human Rights. This layer sets the mission to steer humanity towards utopia. The second layer, the global strategy layer, takes this abstract mission and strategizes how to achieve it in the real world.

How to build a thinking AI model

The ACE Framework is built around a simple Flask app, which serves as the core part of the system, known as the bus. The bus has two endpoints, one for adding messages and one for retrieving messages. The bus records messages to YAML files, and can retrieve the top 20 messages based on the layer and the bus. This design allows the ACE Framework to be scalable, with each layer potentially being a microservice or a series of microservices.

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The ACE Framework uses a RESTful API, but could also use AMQP for more shared resources and explicit message routing. This flexibility in design allows the ACE Framework to adapt to different needs and requirements. The ACE Framework is designed with security in mind, with the northbound bus and southbound bus kept separate. This separation ensures that the integrity of the system is maintained.

Each layer of the ACE Framework operates in a similar way, using a simple Python script. The top layer of the ACE Framework, layer one, only receives messages from the northbound bus and produces messages on the southbound bus. All other layers in the ACE Framework have two-way communication with each bus. This design allows for efficient and effective communication within the system.

Despite its innovative design and approach, the ACE Framework is not without its limitations. The system is currently constrained by a lack of external capabilities and real-world data, and is focused on theoretical understanding and planning. The system recognizes these limitations and seeks to overcome them by gathering more information. The system is currently too fast for the API it has access to, causing some issues with its operation.

Possibilities for ACE

There are many possible implementations of the ACE Framework here are just a few of the possible areas that thinking AI models might be perfect for implementation.

  1. Personal Assistant and/or Companion
    • This is a self-contained version of ACE that is intended to interact with one user.
    • Think of Cortana from HALO, Samantha from HER, or Joi from Blade Runner 2049. (yes, we recognize these are all sexualized female avatars)
    • The idea would be to create something that is effectively a personal Executive Assistant that is able to coordinate, plan, research, and solve problems for you.
    • This could be deployed on mobile, smart home devices, laptops, or web sites.
  2. Game World NPC’s
    • This is a kind of game character that has their own personality, motivations, agenda, and objectives. Furthermore, they would have their own unique memories.
    • This can give NPCs a much more realistic ability to pursue their own objectives, which should make game experiences much more dynamic and unpredictable, thus raising novelty.
    • These can be adapted to 2D or 3D game engines such as PyGame, Unity, or Unreal.
  3. Autonomous Employee
    • This is a version of the ACE that is meant to carry out meaningful and productive work inside a corporation.
    • Whether this is a digital CSR or backoffice worker depends on the deployment.
    • It could also be a “digital team member” that primarily interacts via Discord, Slack, or Microsoft Teams.
  4. Embodied Robot
    • The ACE Framework is ideal to create self-contained, autonomous machines.
    • Whether they are domestic aid robots or something like WALL-E

The ACE Framework represents a step towards solving the problem that will solve every other problem. It is a testament to the power of AI and the potential it holds for solving complex problems. The ACE Framework is being developed by several teams, with the development process being public. This openness in development allows for collaboration and innovation, pushing the boundaries of what is possible with AI.

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The future plans for the ACE Framework involve improving its capabilities by giving it access to APIs and other external data sources. This will allow the system to gather more information and overcome its current limitations. There is also a focus on building information literacy into the system and keeping track of sources. This will ensure that the system is not only efficient but also reliable and trustworthy.

The ACE Framework is a pioneering approach to AI that prioritizes cognition over input and output. It is a scalable, secure, and efficient system that is designed to solve complex problems. Despite its current limitations, the ACE Framework holds great promise for the future of AI. With continued development and improvement, the ACE Framework has the potential to revolutionize the field of AI.

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