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AGI related hardware

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SingularityNET
RFP Owner

AGI related hardware

Aggregating research on AGI hardware configurations with specific advantages for AGI and OpenCog Hyperon Components

  • Type SingularityNET RFP
  • Total RFP Funding $80,000 USD
  • Proposals 4
  • Awarded Projects 1

Overview

  • Est. Complexity

    💪 50/ 100

  • Est. Execution Time

    ⏱️ 6 Months

  • Proposal Winners

    🏆 Single

  • Max Funding / Proposal

    $80,000USD

RFP Details

Short summary

This RFP seeks to explore and evaluate innovative hardware paradigms, ranging from small-scale IoT devices to large, decentralized systems, to optimize AGI workloads in the OpenCog Hyperon framework and handle advanced processes such as cognitive synergy and hyperdimensional computing. The focus is on assessing hardware paradigms and emerging architectures (e.g. neuromorphic processors, associative processors such as TensTorrent’s APU, etc). The goal is to enhance computational efficiency, scalability, and cognitive synergy in AGI systems. Part of this should involve interacting with the Hyperon team who've built the existing and in-development MeTTa interpreters.

Main purpose

To explore and recommend hardware solutions that offer significant advantages for Hyperon’s components, such as PLN, MOSES, ECAN, etc with massive workloads. The goal is to identify hardware configurations that improve performance, scalability, and resource allocation, supporting the realization of scalable AGI systems.

Long description

Context and background: 

SingularityNET Foundation, in collaboration with the OpenCog Foundation and TrueAGI, is developing a scalable AGI system based on the Hyperon framework, running on decentralized infrastructure. The PRIMUS cognitive architecture, designed to integrate multiple cognitive modules, is a core focus of this work. Achieving the goal of a scalable AGI system requires hardware that can support both the symbolic and sub-symbolic processes underpinning AGI. Hyperon’s key components—such as Economic Attention Network (ECAN), Probabilistic Logic Networks (PLN), and procedural learning systems such as Meta-Optimizing Semantic Evolutionary Search (MOSES) which are processing extremely heavy workloads — demand specialized hardware configurations to function efficiently at scale. Also of interest would be hardware solutions to speed up encryption protocols, such as Fully Homomorphic Encryption, for security and privacy critical use-cases such as in the health and financial domains.

This RFP focuses on evaluating and identifying hardware paradigms that can optimize the performance of AGI components, specifically those within the Hyperon architecture. The emphasis is on broadly exploring hardware technologies, perhaps including chips suited for mixed workloads as found in neuro-symbolic systems, processors for hyperdimensional computing (including Sparse Distributed Memory and other approaches in the pursuit of a Vector Symbolic Architecture), and decentralized computing systems. Efficient hardware solutions are critical to scaling AGI systems, ensuring that computational tasks are processed swiftly and accurately while maintaining resource flexibility across decentralized networks. As part of a comprehensive and secure solution with privacy protection, hardware for speeding up data encryption, and decryption should also be evaluated.

This RFP seeks to explore and evaluate innovative hardware paradigms, ranging from small-scale IoT devices to large, decentralized systems, to optimize AGI workloads in the OpenCog Hyperon framework and handle advanced processes such as cognitive synergy, hyperdimensional computing, and fully homomorphic encryption (FHE). The focus is on assessing hardware paradigms and emerging architectures (e.g., neuromorphic processors, associative processors, specialized designs to speed up FHE, etc). The goal is to enhance centralized and decentralized computational efficiency, scalability, and cognitive synergy for AGI systems. 

Part of this should involve interacting with the Hyperon team who've built the existing and in-development MeTTa interpreters, and understanding how hardware down to the bare metal can directly support and accelerate AGI processes.

Collaboration:

This RFP may lead to further projects focusing on the integration of selected hardware solutions into the Hyperon/PRIMUS framework and may prompt additional studies on the impact of hardware on the cognitive development of AGI systems, guiding them toward beneficial AGI outcomes.

RFP Expected Outcomes:

  • An evaluation of:
    • MeTTa, MeTTa compilers, and Hyperon technologies and how various hardware configurations could improve processing among the various cognitive modules and through the stack down to “bare metal”.
    • Existing and emerging hardware technologies applicable to the various AGI components, separately and together, and how they may address the shortcomings of current state of the art hardware for the respective computational requirements.
  • Identification of hardware solutions that can significantly enhance the performance and scalability of the Hyperon framework.
  • Consideration of rethinking codebases and compilers to take advantage of recommendations.
  • Recommendations for integrating hardware, such as the promise of hypervector chips and decentralized compute systems, into the Hyperon/PRIMUS stack.
  • Insights into how specialized hardware can improve the efficiency of key AGI components, supporting large-scale AGI computations.

Functional Requirements

  • Literature review on hardware: The proposer must conduct a comprehensive review of current and emerging hardware technologies that could potentially optimize AGI systems including data security. This includes doing the groundwork to learn as much as possible about specialized chips like GSI Technology’s APU (https://gsitechnology.com/compute/), GPUs, and other hardware known to accelerate AI tasks, and identifying their suitability for AGI systems such as Hyperon. This research may be challenging and involve setting up meetings, talking to the engineers, getting internal presentations, etc.
  • Analysis of hardware for AGI components: The research must identify which existing or theoretical hardware solutions are likely to enhance the performance of key AGI components, by reviewing existing studies on hardware performance in similar AI contexts.
  • Feasibility of hardware for AGI tasks: The proposer must evaluate the potential fit of these hardware solutions for AGI-specific tasks such as pattern matching, real-time inference, and cognitive synergy, based on their findings from existing literature.
  • Recommendations for further study: The research must culminate in clear recommendations on which hardware solutions warrant further study or experimental testing in AGI systems.

Non-functional Requirements

  • Accuracy and rigor: Ensure that the research is thorough, credible, and backed by data from peer-reviewed articles, industry reports, or academic sources (as available).
  • Comparison of hardware: The review must provide a detailed comparison of the hardware solutions, including GSI APU, in terms of their scalability, energy efficiency, and potential to support decentralized AGI systems​​.
  • Integration feasibility: Although this RFP is focused on research, the proposer should assess how these hardware solutions could potentially integrate with existing AGI infrastructures like Hyperon​. This assessment can be made in collaboration with folks on the projects.
  • Scalability and energy efficiency: The research should analyze scalability and energy usage of the reviewed hardware options, ensuring that identified solutions are suitable for large-scale AGI systems​.
  • Reliability: The review should also consider the reliability and maturity of the hardware technologies, identifying those most likely to offer stable, long-term solutions for AGI​.

Main evaluation criteria

 Alignment with requirements and objective

  • Does the proposal meet the requirements and advances the objectives of the RFP

Pre-existing R&D

  • Has the team previously done similar or related research or development work in other platforms / languages / contexts?

Team competence

  • Does the team have relevant skills?

Cost

  • Does the proposal offer good value for money?

Timeline

  • Does the proposal include a set of clearly defined milestones?
  • We highly recommend submitting proposals with project milestones along the lines of the following:
    • Milestone 1: Identification of hardware paradigms and research plan
      Deliverables: Submission of a comprehensive research plan that outlines the hardware paradigms and chips to be researched. The plan should include initial identification of several potential hardware solutions, mapping them to where they fit in relative to AGI systems.
      Proposal of a detailed project plan, including methodologies for evaluating the selected paradigms and how they fit AGI workloads (e.g., scalability, energy efficiency, and performance).
      25% of the grant

    • Milestone 2: Demonstration of substantial research progress
      Deliverables: Evidence of substantial progress in the research phase. Continue development of the research with deeper analysis
      25% of the grant

    • Milestone 3: Continued demonstration of deeper research progress
      Deliverables: Evidence of substantial progress in the research phase. Continue development of the research with deeper analysis.Updated documentation of research findings, including any modifications to the proposed hardware solutions or the AGI component mappings.
      25% of the grant

    • Milestone 4: Final Stages of Research Progress
      Deliverables: Completion of the research phase. This milestone should reflect the maturing of the research efforts, including detailed findings on the hardware paradigms’ impact on AGI performance, scalability, and computational efficiency. Further analysis of results suggesting integration or further study paths for the selected hardware paradigms and approaches.
      25% of the grant

Other resources

Hyperon and related AI-platforms are quickly evolving! This is a bit of a moving target, but the internal SingularityNET team will be available for help and expert advice, where needed. Also included:

  • SingularityNET technology links
  • Educational materials and resources for learning MeTTa
  • SingularityNET holds MeTTa study group calls every other week. Proposers are welcome to attend for support from our researchers and community.
  • Recurring Hyperon study group calls for community are currently being planned. These will cover MOSES, ECAN, PLN, and other key components of the OpenCog and PRIMUS Hyperon cognitive architectures.
  • Access to the SingularityNET World Mattermost server upon request, with a dedicated channel for discussion and support among the RFP-winning teams and SingularityNET resources.

RFP Status

Completed & Awarded

The community and public are invited to view the full proposals and give feedback. During this time the RFP committee will doing their formal selection process to award winning proposals.

View Awarded Projects
4 proposals
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EXPERT REVIEW 4.0

AGI Hardware Paradigm Shifts and Neuromorphic Tech

  • Type SingularityNET RFP
  • Funding Request n/a
  • RFP Guidelines AGI related hardware
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Gabriel Axel Montes
Dec. 6, 2024
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EXPERT REVIEW 3.3

Temporal Compute

  • Type SingularityNET RFP
  • Funding Request n/a
  • RFP Guidelines AGI related hardware
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Jonathan Edwards
Oct. 24, 2024
rfp=proposal-img
EXPERT REVIEW 2.6

AGI hardware assesment

  • Type SingularityNET RFP
  • Funding Request n/a
  • RFP Guidelines AGI related hardware
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spatialtemporal
Dec. 5, 2024
rfp=proposal-img
EXPERT REVIEW 2.0

EdgeAGI

  • Type SingularityNET RFP
  • Funding Request n/a
  • RFP Guidelines AGI related hardware
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KeyvanMSadeghi
Dec. 5, 2024
1 Projects
rfp=proposal-img

Design for Cryptocurrency Mining and AI Processing

  • Type SingularityNET RFP
  • Funding Awarded n/a
  • RFP Guidelines AGI related hardware
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simuliinc
Dec. 7, 2024

Join the Discussion (1)

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1 Comment
  • 0
    commentator-avatar
    Jan Horlings
    Oct 8, 2024 | 7:13 AM

    Test. Let me know if the notification system works and if you as the owner of the RFP get notified. 

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