Project Liftoff: Universal Intelligent Systems (UIS) by 2030

33 Pages Posted: 8 Aug 2019 Last revised: 13 May 2021

See all articles by Carl Hewitt

Carl Hewitt

Massachusetts Institute of Technology (MIT)

Date Written: July 29, 2019

Abstract

Universal Intelligent Systems (UIS) will encompass everything manufactured and every sensed activity. Every device used at home and work will be included as well as all equipment used in recreation, entertainment, socializing, and relaxation including clothing, accessories and shoes.

Information will be integrated from massive pervasively inconsistent information from video, Web pages, hologlasses (electronic glasses with holographic-like overlays), online data bases, sensors, articles, human speech and gestures, etc. Information integration will enable an intelligent system to be used by other intelligent systems without having to start over from scratch. Information inference will be robust taking into account multiple sources and perspectives and counterbalancing many interests and perspectives. UIS will largely overcome the current reuse pain point that there is no effective inference for information that is balkanized in applications. An Intelligent System will be educable so that it can interactively adapt in real time (instead of relying exclusively on passively attempting to find correlations among inputs.

An Intelligent System will be self-informative in the sense of knowing its own goals, plans, history, provenance of its information. Also, it will have relevant information about its own capabilities including strengths and weaknesses. When overload or other internal trouble is inferred, an Intelligent System will be able to reach out as appropriate to people and other systems.

Security will be paramount for an Intelligent System so that it is not easy to penetrate or to deceive into taking inappropriate action.

Project Liftoff(TM) to develop and deploy UIS in this decade stands to be a huge development effort comparable to the Apollo Project. Education will be crucial to the success of Project Liftoff because there is an enormous talent shortage.

US has yet to commence Project Liftoff, but there is a growing consensus that a large effort is required to address issues of universal Integrative Intelligent Systems. China is racing to develop its own indigenous universal secure intelligent systems as rapidly as possible [Liu, 2020, Cheng, Feifel, and Shuia 2019, Xin and Chi-yuk 2018, China State Council 2017, Lewis and Litai 1988. Evan Feigenbaum 2003].

The goal of Project Liftoff is to achieve universal Integrative Secure Intelligent Systems by 2030. Project Liftoff is a development effort comparable to the Apollo Project. Education will be crucial to the success of Project Liftoff because there is an enormous talent shortage.

Discursive(TM) is a proposed architecture for universal Integrative Secure Intelligent Systems with the following technology stack:
• Actor myriad-cores architecture with
o ActorScriptTM for massive robust concurrency
o strongly-typed without extra tag bits architecture to protect security of Actors including dynamic relocation and automatic pause-less storage reclamation
o 10ns average communication latency to provide quick response time to users
• Services for underlying operations, e.g., interoperation with datacenters and other Citadels
• Massive Inference-Robust Ontology [Guarino and Musen 2015, Hewitt 2016-2019] for operations on massive amounts of pervasively inconsistent information including statistics and correlations
• Matrix [Bender, Flickinger, and Oepen 2002, Bender et. al. 2010] for discourse, rhetoric and narratology
• Experiences [Gurman 2017, Mundy 2016, Shapiro, et. al. 2015] for collaborations, gestures, video, etc.
• Citadels [Hewitt 2019] for increased performance and robustness with no single point of failure and rectifying mistakes ASAP

The Discursive(TM) system outlined in this article can enable Universal Intelligent Systems by 2030. The task for the proposed project Liftoff is to implement the Discursive system.

US has yet to commence Project Liftoff, but there is a growing consensus that a large effort is required to address issues of universal Integrative Intelligent Systems. China is planning to have its own indigenous universal secure intelligent systems as rapidly as possible [Liu, 2020, Cheng, Feifel, and Shuia 2019, Xin and Chi-yuk 2018, China State Council 2017, Lewis and Litai 1988. Evan Feigenbaum 2003] If other countries have to depend on China for Intelligent Systems technology then countries outside of China will have fewer jobs, lower information security, weaker militaries, less efficient economies, and fewer opportunities for civil liberties. [JASONS 2019]

Takeaways
• Liftoff is a strategic Apollo-scale project with a technology stack that fundamentally extends existing technologies for ontologies, robust inference. software systems, user interaction, and (later on) Actor-like computer architecture.
• Inference-robust active Actology provides means to effectively integrate information at scale.
• Applications will drive the additions of new content in ontologies.
• A citadel provides increased robustness because of reduced dependence on remote datacenters.
• A citadel can provide better information integration than datacenters because information is not isolated in datacenters of different organizations.
• China is racing to develop and deploy Universal Intelligent Systems (UIS) in this decade thereby transforming their economy, jobs, military, and society.
• Universal Intelligent Systems must be able work on a large scale involving the following:
o Close human interaction using electronic glasses for people interacting using secure mobile communication.
o Integrative in real-time using robust inference enabling information of an intelligent system to be used by other intelligent systems without having to start over from scratch.
o Adaptable so that systems can interactively adapt in real time using robust inference (instead of being restricted to static stimulus/response networks trained large corpus of speech, video, and text). Each robust inference is adaptive.
o Self-informative knowing its own goals, plans, history, provenance of its information and having relevant information about its own strengths and weaknesses. When overload or other internal trouble is inferred, an Intelligent System will be able to reach out, as appropriate, to people and other systems.
o Secure in that there no easy ways to penetrate systems or deceive them.
• Integrative Intelligent Systems are constructed using massive pervasively contending information requiring inference-robust inference.
• Scalability requires that Actology concurrently process millions of communications for descriptions, narratives, plans, procedures, evaluators, auditors, and propositions while creating and operating hundreds of thousands of (statistical) classifiers and verifiers.
• Each robust inference is adaptive.
• Although classifiers and verifiers are a small part of Actology, they are useful because they provide a first cut at recognition in many domains such as vision and voice although they do not adapt in realtime.
• Inference is performed concurrently in an Actology by communicating Actors.
• A Citadel coordinates operations using a massive inference-robust Actology.
• A Citadel can provide a more relevant and effective advertising business model with better integration of personal and situational information.
• Citadels can robustly share sensitive information.
• In about a decade, electronic glasses are projected to supplant smartphone s and to be used for just about everything.
• Discourse Technology is enormously more powerful than Correlation Technology (e.g., “Deep Learning”), which will not by itself produce Universal Intelligent Systems in this decade.
• Project Liftoff is an Apollo-scale project to develop and deploy Universal Intelligent Systems by 2030 in order to preserve representative government and civil liberties.

Keywords: Integrative Scalable Intelligent Systems, Pain Management, Massive Inference Robust Ontology, Deep Learning, Gradient Classifier

Suggested Citation

Hewitt, Carl, Project Liftoff: Universal Intelligent Systems (UIS) by 2030 (July 29, 2019). Available at SSRN: https://ssrn.com/abstract=3428114 or http://dx.doi.org/10.2139/ssrn.3428114

Carl Hewitt (Contact Author)

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

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