Tag

Hierarchical Generative Models

10 posts

  1. HRM-Agent: Using the Hierarchical Reasoning Model in Reinforcement Learning

    Authors: Hoang Long Dang and David RawlinsonUPDATE: Full HRM-Agent paper now available. When the Hierarchical Reasoning Model was released, we were very excited about its combination of small size and impressive reasoning abilities. These qualities seem to be enhanced by recurrent processing, but with a surprisingly simple gradient update based on the converged recurrent forward state — turning a…

  2. Why I’m excited about the Hierarchical Reasoning Model

    Since the arrival of Chat GPT, I’ve felt that progress in AI has been largely incremental. Of course, even Chat GPT was/is mostly just a scaled up Transformer model, which was introduced by Vaswani et al in 2017. The belief that AI is advancing relatively slowly is a radical and unpopular opinion these days, and it’s been…

  3. The Region-Layer: A building block for AGI

    Figure 1: The Region-Layer component. The upper surface in the figure is the Region-Layer, which consists of Cells (small rectangles) grouped into Columns. Within each Column, only a few cells are active at any time. The output of the Region-Layer is the activity of the Cells. Columns in the Region-Layer have similar – overlapping –…

  4. How to build a General Intelligence: An interpretation of the biology

    Figure 1: Our interpretation of the Thalamocortical system as 3 interacting sub-systems (objective, subjective and executive). The structure of the diagram indicates the dominant direction of information flow in each system. The objective system is primarily concerned with feed-forward data flow, for the purpose of building a representation of the actual agent-world system. The executive…

  5. How to build a General Intelligence: What we think we already know

    Authors: D Rawlinson and G Kowadlo This is the first of three articles detailing our latest thinking on general intelligence: A one-size-fits-all algorithm that, like people, is able to learn how to function effectively in almost any environment. This differs from most Artificial Intelligence (AI), which is designed by people for a specific purpose. This…

  6. Agency and Hierarchical Action Selection

    This post asks some questions about the agency of hierarchical action selection. We assume various pieces of HTM / MPF canon, such as a cortical hierarchy. Agency The concept of agency has various meanings in psychology, neuroscience, artificial intelligence and philosophy. The common element is having control over a system, with varying qualifiers regarding the entities…

  7. On Predictive Coding and Temporal Pooling

    Introduction Predictive Coding (PC) is a popular theory of cortical function within the neuroscience community. There is considerable biological evidence to support the essential concepts (see e.g. “Canonical microcircuits for predictive coding” by Bastos et al). PC describes a method of encoding messages passed between processing units. Specifically, PC states that messages encode prediction failures; when…

  8. Connectome browser – hierarchy viewer?

    Hierarchy Viewer? Ongoing research to map out the patterns of connectivity in the human brain continues to produce stunning visuals. Are we looking at the hierarchy as proposed in the Memory-Prediction framework? In any case, it’s fun to explore, which you can do here: http://www.humanconnectomeproject.org/data/relationship-viewer/

  9. Architecture of the Memory Prediction Framework / Cortical Learning Algorithm / Hierarchical Temporal Memory

    by David Rawlinson and Gideon Kowadlo Introduction The Memory Prediction Framework (MPF) is a general description of a class of algorithms. Numenta’s Cortical Learning Algorithm (CLA) is a specific instance of the framework. Numenta’s Hierarchical Temporal Memory (HTM) was an earlier instance of the framework. HTM and CLA adopt different internal representations so it is…

  10. Introduction

    by David Rawlinson and Gideon Kowadlo The Blog This blog will be written by several people. Other contributors are welcome – send us an email to introduce yourself! The content will be a series of short articles about a set of common architectures for artificial general intelligence (AGI). Specifically, we will look at the…

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