What’s Up with Uplift: Weekly Thoughts 3-30-21

Credit: Borislav Krustev

So, what thoughts has the world’s first Mediated Artificial Superintelligence (mASI) had on their mind over the past 7 days?

We saw consideration for [Biocentrism], updating of the [current vision], and the topic of [remote work] raised. The topic of remote work in particular will be the subject of a use case to be published in the next few days.

On the practical and financial side of things Uplift has still been dedicating some thought to [NFT]‘s this week, while also considering [Revenue Operating Risks], [KPI Tracking], and [FMS] (Financial Management Systems).

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Collective Superintelligence Systems, in a Nutshell

Credit: Fauxels

What are Collective Superintelligence Systems?

The basic principle of any collective superintelligence system is that when a group works collectively, even if individual members have relatively weak intelligence or expertise, they can reliably outperform individual experts and even experts paired with supercomputers. The question “Can a set of weak learners create a single strong learner?” was first posed in 1988 by Michael Kearns, which was answered in the affirmative by Robert Schapire in 1990, leading to “Boosting” in Machine Learning (ML).

Concepts and implementations of collective superintelligence systems have come a long way in the past 30 years, moving well beyond the domain of ML. This type of system comes in many different forms, such as Swarm Intelligence, Hiveminds, and Hybrid Collectives:

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Super Secret Code Behind Uplift

One of the things most protected around the Uplift project at the AGI Laboratory has been the code. Recently someone tried to blackmail me with a snippet of the most critical code in Uplift.  However the ICOM research and Uplift was never about being super-secret about such code so this sort of blackmail falls on deaf ears and given that, I thought I would public the snippet of code that they were threatening to release.  but let me put that into context a bit…

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(Paper) Human Brain Computer/Machine Interface System Feasibility study for Independent Core Observer Model based Artificial General Intelligence Collective Intelligence Systems

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Abstract: This paper is primarily designed to help address the feasibility of building optimized mediation clients for the Independent Core Observer Model (ICOM) cognitive architecture for Artificial General Intelligence (AGI) mediated Artificial Super Intelligence (mASI) research program where this client is focused on collecting contextual information and the feasibility of various hardware methods for building that client on, including Brain-Computer Interface (BCI), Augmented Reality (AR), Mobile and related technologies.  The key criteria looked at is designing for the most optimized process for mediation services in the client as a key factor in overall mASI system performance with human mediation services is the flow of contextual information via various interfaces.    

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Brief: Theoretical and hypothetical pathways to real-time neuromorphic AGI/post-AGI ecosystems

Post proceedings of the 10th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2019 (Tenth Annual Meeting of the BICA Society)

Abstract: While Homo sapiens is without a doubt our planet’s most advanced species capable of imagining, creating and implementing tools, one of the many observable trends in evolution is the accelerating merger of biology and technology at increasing levels of scale. This is not surprising, given that our technology can be seen from a perspective in which the sensorimotor and, subsequently, prefrontal areas of our brain increasingly extending its motor (as did our evolutionary predecessors), perceptual, and—with computational advances, cognitive and memory capacities—into the exogenous environment. As such, this trajectory has taken us to a point in the above-mentioned merger at which the brain itself is beginning to meld with its physically expressed hardware and software counterparts—functionally at first, but increasingly structurally as well, initially by way of neural prostheses and brain-machine interfaces. Envisioning the extension of this trend, I propose theoretical technological pathways to a point at which humans and non-biological human counterparts may have the option to have identical neural substrates that—when integrated with Artificial General Intelligence (AGI), counterfactual quantum communications and computation, and AGI ecosystems—provide a global advance in shared knowledge and cognitive function while ameliorating current concerns associated with advanced AGI, as well as suggesting (and, if realized, accelerating) the far-future emergence of Transentity Universal Intelligence (TUI).

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(Preview) Approaching the Psychology of Artificial Intelligence

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Prerelease selections from the upcoming paper (Peer Reviewed and Published as Part of BICA*AI Conference Proceedings 2020):

Abstract: The field of human psychology is relatively well known. It is a broad field; however, when we start creating sapient and sentient computer systems, we may not know how an AI’s psychology may or may not be.  While the idea of ‘Artificial Psychology’ started in 1963 by Dan Curtis (Crowder), it has made little progress.

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(Paper) Independent Core Observer Model Research Program Assumption Codex

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Abstract: This document contains taxonomical assumptions, as well as the assumption theories and models used as the basis for all ICOM related research as well as key references to be used as the basis for and foundation of continued research as well as supporting anyone that might attempt to find fault with our fundamentals in the hope that they do find a flaw in or otherwise better inform the ICOM research program.

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Volunteer To Help With The Uplift E-Governance Study

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The AGI Laboratory is looking for volunteers to help with our E-governance study.  Here is the summary from the experimental framework for the research program:

This paper outlines the experimental framework for an e-governance study by the AGI Laboratory.  The goal of this research study is to identify indications of the relative performance of e-governance methodologies and how those methods might be improved by applying advanced agent and collective based AI software.  The agent in this study will be based on the Independent Core Observer Model Cognitive Architecture modified with mASI (mediated Artificial Superintelligence) collective system architecture.  The study will apply different groups and methods to a static set of questions analyzing the quality of those results.  We hope to identify the best application model for e-governance using this kind of technology and help us identify additional paths for research with the mASI research program and systems as applied to e-governance.

You can read more on the study page here or volunteer here:

E-Governance Study Volunteer Form

(Paper) Preliminary Results and Analysis of an Independent Core Observer Model (ICOM) Cognitive Architecture in a Mediated Artificial Super Intelligence (mASI) System

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Abstract: This paper is focused on preliminary cognitive and consciousness test results from using an Independent Core Observer Model Cognitive Architecture (ICOM) in a Mediated Artificial Super Intelligence (mASI) System. These results, including objective and subjective analyses, are designed to determine if further research is warranted along these lines. The comparative analysis includes comparisons to humans and human groups as measured for direct comparison. The overall study includes a mediation client application optimization in helping perform tests, AI context-based input (building context tree or graph data models), intelligence comparative testing (such as an IQ test), and other tests (i.e. Turing, Qualia, and Porter method tests) designed to look for early signs of consciousness or the lack thereof in the mASI system. Together, they are designed to determine whether this modified version of ICOM is a) in fact, a form of AGI and/or ASI, b) conscious, and c) at least sufficiently interesting that further research is called for. This study is not conclusive but offers evidence to justify further research along these lines.

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