The objective of this project is to develop a proof-of-concept prototype for the defining facets of a method for generating Artificial General Intelligence (AGI) or Strong AI. To establish the claim of such outcome being a simulation of human mental capabilities rather than mere emulation thereof, the prototype includes certain aspects of human intellect that state-of-the-art AI is not capable of acknowledging. Principally, the characteristics that distinguish envisaged variant of synthetic intelligence concern the ‘subjective‘ nature of the ensued output. Corresponding demonstrable features involve ‘comprehension-based reasoning‘ in conjunction with a more easily relatable ‘logic-based reasoning‘ in AI contexts. Further, the generated cumulative synthetic response to given challenge can be seen to combine various elements as sentience, sapience and common sense – each derived from a common basis underlying these cognitive abilities.
Essentially, such a postulated foundation for all human cognition (and in turn of the proposed variant of AI) relies upon a preordained ‘contract’ between the subject and object components engaged in the process of intelligence creation. Factors determining the native notions of comprehension, sentience, and logic etc. originate from such subject-object contract – a conceptualization pitched as Omnijectivity in this study. One of the key goals of the project is to demonstrate the originality, autonomy, and consistency displayed by such AI on par with those exercised by the human mind.
From an implementation standpoint, Omnijectivity gets realized as a function of several unprecedented technological paradigms introduced in this research. Three of the most notable such interdependent paradigms, that are further elaborated in the Technical Plan, include –
- Omnijective Axiomatic Scaffold: a support structure for the program-native semantic that sustains an evolutionary episteme. Various types and kinds of constituent axioms strut up what is termed a Potential Semantic Schema (think a repository of yet-to-be discovered human knowledge)
- Omniject Oriented Programming: a developmental context geared at object-oriented programming from program (synthetic agent) perspective rather than that of the programmer, and
- Omnijective Contract(ual Framework): an abstraction of ‘all’ possible protocols within given composition of an Omniject to enable consistent inter-entity interactions.
Method overview
Success of A3ilabs – Project POC is contingent upon retaining the character of the erected Omniject throughout (and not let it be relegated to a mere Object), despite our inevitable object-oriented outlook. This entails contesting various prevailing notions related to intelligence and de facto operational patterns in synthesizing it. These include the belief in the intelligence exclusively residing within object representations, rule-based depiction of knowledge denoted by such latent intelligence, algorithmic approach to assimilate so modeled knowledge, statistical character of the ensued intelligence, and more. At the very core, envisaged shift to the existing AI paradigm is not merely architectural or procedural, rather involves a fundamental switch from the deterministic intent implied of object-orientation – absolute or stochastic irrespective, to an enabler intent signified by Omniject-Orientation.
Principles governing Omnijectivity have been formalized following one-of-a-kind fundamental research methodology1. These Principles of Omnijectivity relate to the compositional and innate complementarity aspects in the creationist pursuit of an Omniject. Also, the principles form basis for Omniject-Orientation (essence of the proposed method) as the generic characterization to the verification and falsification frameworks for any science or technology cascading from such a philosophical positioning. Essentially, the methodology concerns modeling an associated enabler intent rather than given phenomenon itself. The prototype proposed as part of A3ilabs – Project POC primarily demonstrates the applied technological (programmatic) implications of the principles of Omnijectivity2.
Technical approach overview
Omniject Oriented Programming paradigm lets the algorithms be segmented semantically as micro-algorithms – that could breach the atomicity of fundamental programmatic constructs to desired granularities, albeit within specified contexts of scoped semantics. Most significant use case of micro-algorithms within an operational setup for general AI involves internalizing patterns of reasoning to programs as heuristics, instead of as programmatic instructions from the outside. Such heuristics combine as per the ask of the problem at hand to output an algorithm denoting the response of the synthetic intelligence indexed by the program. If we were to associate intelligence more with the cause than the effect of the involved dynamics in responding to given challenge – that is, as a basis for generation of the algorithm rather than the resultant output – micro-algorithms signify a step in the right direction.
The enablement implied of such heuristic-based architectures get furthered, to make way for higher degrees of agent autonomy (referred to as human-like intelligence in this study), within the contexts of Omnijective Contract and Potential Semantic Schemata. Essentially, while the portfolios of heuristics denote the building blocks of reasoning imparted to the synthetic agents, the Omnijective Contract abstracts the programmer’s intent3 with regard to the way these blocks are consumed in modeling a solution to given problem. So isolated intent from the program in its entirety allows for defining dimensions of freedom (of intelligence) along which the intent may be negotiated with in the process of assembling an algorithmic response. The notional neighborhoods of the primary intent within which it could be maneuvered, without veering off the consistency required of the resultant response as judged by the human programmer, represent ambits of original intelligence that the program is enabled to reveal – an unintended and unprogrammed for intelligence potentiated by omniject-orientation. In fact, this potential intelligence is the purpose of all Omniject Oriented Programming, where the onus of providing solution to a problem gets reposed with the program while the focus of the programmer is confined to program enablement. Such program-native intelligence gets eventualized vis-à-vis a foundationalist schema of semantics instituted upon Omnijective Axiomatic Scaffold, that condenses all knowledge representable within the implied system in an ensemble of potentialities. Original knowledge gets created within such a schema by way of stitching together patterns of knowledge as driven by the native intelligence, turning potentialities to eventualities. Implementations of such Potential Semantic Schema involve deriving a Semantic Alphabet, as common denominatorial patterns of the intended knowledge representations, used to spell out various manifestations of free willed intelligence such as articulation, innovation, strategy, discovery, sense of humor etc. Inward Extensibility of the semantic schema, the ability of representable knowledge to potentiate inwards indefinitely within set limits, gets realized in a language analogy sustained by the semantic alphabet. (Below Infographic depicts the technical approach)
However, enduring object orientation in terms of the algorithmic basis for various involved operations of enablement such as intent abstraction, intent negotiation, modeling varied logical agencies to carry out these tasks as proxies to the programmer etc., constrains the autonomy required in endowing human-level intelligence to the programs. Whereas its neither possible nor necessary to rid of all object orientation from the process in principle, a right balance needs to be struck between the algorithmic and heuristic facets of the program in enhancing the program-native intelligence originating out of the intent neighborhoods on par with the human equivalent. Several multi-disciplinary fields of research open up in attaining the states of such internal semantic equilibrium to afford human-level autonomy to the machine-mind. For example, while the design of an empiric determinable (say, material object) that appeals consistently to both sentient and comprehensional aspects of the intelligence in imparting physicality to the synthetic agencies4 invokes Omniject-Oriented Physics, a more abstract endeavor of endowing ‘choice as an axiom’ to the determiner component of the program (subject) engages in rather fundamental formulation of Omniject-Oriented Mathematics. Although the human-level intelligence is not in the stated scope of A3ilabs – Project POC, some instructive elements such as experiential sentience and multi-agent interpretations get included in the method illustration meant essentially for human-like intelligence.
footnotes
1. Acontextual Analysis Methodology (or Acontextuality), as it is termed, also happens to be the postulated working principle inspiring human-level cognition. While achieving synthetic Acontextualization is the overall purpose of A3ilabs, Project POC primarily concerns a prerequisite thereof – termed Adjectivization.
2. Given acutely abstract and counter-intuitive nature of the Principles of Omnijectivity, the idea is to publish the applied results before the fundamental results – the impetus behind A3ilabs – Project POC.
3. To be precise, Omnijective contract isolates the programmer’s intentionality that packs more than mere intent to include varied elements of the agent’s purpose, motivation, and capabilities etc.
4. Refers to the possibility of a humanoid robot, that could walk among us sharing our Omnijective axiomatic framework – capabilities & vulnerabilities alike and be able to assert its free will as a ‘choice‘ rather than an external instruction.
A philosophical OVERVIEW: GENERAL
The fundamental aspect of the research devises an alternate hypothesis to biological naturalism in addressing the apprehensions roused by the Chinese room argument. In other words, the version of functionalist theory of mind advanced in this research essentially allows for the syntactical constructs of the programs to refer program specific semantic contexts. For such a premise to hold, however, the basis for the injection of semantics to the programs may not in itself be falsified by the aforementioned argument. This debilitating constraint practically takes every conceivable tool and technique off the table – with prevailing paradigms of programming, mathematics, sciences, language, and logic providing only marginal utility. The study takes the ensuing inquiry to the very philosophical foundations of human sciences, raising questions that could not have been asked earlier, in crafting an operational footing for the method. Of particular note is the inclusive nature of the resultant methodology that offers an encompassing, rather than an adversarial augmentation to human scientific endeavor. Consequently, the fundamental levels of human cognition at which the inquiry plays out essentially extend the base of attainable episteme through human sciences. As could be expected, such a revisionist exploration of the fundamentals is likely to impact multiple disciplines and be influential in spinning off various exotic fields of elementary study. For instance, the study lays out the contexts and basis for the formulation of a theoretical branch of mathematics to explore the other side of the axiomatic frameworks such as first order logic symbolisms or Zermelo-Fraenkel axioms. Below schematic provides the high-level view of proposed theory of mind – the Omniject-Orientation.
Generally speaking, Omniject-Orientation provides a broader catchment for the human phenomena than allowed by the human innate natural attitude characterized by object-oriented outlook. Traditionally, the variance has been dealt with in the context of various domains of Philosophy, though the method never acquired the operational rigor required and remained ad hoc. The formal operational footing to the method as prescribed by the Omnijectivity principles, thus, open up tremendous possibilities in terms of newer technological and scientific paradigms that could not be conceived, much less achieved in our purely object centric outlook. For instance, the micro-algorithms may be viewed as being instrumental in internalizing the semantics of How and Why to the human-coded (agent) programs that have traditionally been centered on the exposition of What, of course within set semantic boundaries.
a philosophical overview: PROJECT POC
In the context of a general variant for programmatic intelligence, the implications of Omniject-orientation are of course going to be felt primarily in the process of programming. A snapshot of the fundamental difference between prevailing and envisioned approaches for AI is summarized below –
Prevailing Context
State-of-the-art AI relies upon an absolute disposition of –
- given phenomenon (the Object),
- vantage to the phenomenon (the human Subject), and
- the comprised interfaces (Logic, Cognition etc.)
This restricts the nature of ensuing method to Object-Orientation – as both a means and an end – with any intelligence sourced exclusively from human mind. Programs take shape rather delayed in the AI creation process, in fact, inevitably after the human intelligence ‘happens’. Algorithmic core of such programs could at best sustain Narrow/Weak AI.
The approach regards the Omniject – a postulated contract between the subject and object components, as absolute. Consequent Omniject-Orientation dynamically concocts –
- the native phenomenon,
- associated native-intent wielding agent program, and
- a contextual algorithmic response to the phenomenon along with its cognitive roots (e.g., Logic or Comprehension).
The approach for general intelligence transforms the landscape of AI as we know it, by inducting unprecedented technological contexts as Micro-Algorithms, Potential Semantics etc.
Conceptual representation of the intended approach is depicted here –
Such an approach for synthetic intelligence, that goes against the grain on almost every aspect of the prevailing notions related to AI, revolutionizes the way intelligence gets created, manifested, trained, tested, and consumed.
CONTEXT
Proposed prototype concerns the most sophisticated variety of the Natural Language Programming paradigm yet – natural language itself as an executable program. Ontology-assisted way to programming in conjunction with the epistemic reinforcement offered by Omniject-Orientation, as regards the patterns of programmatic reasoning that integrate deductive, inductive, and abductive styles of logic, provides a conducive environment required of such an ambitious endeavor. Further, several features included in the prototype that demonstrate human-like comprehension, sentience, sapience, and common sense in Natural Language Processing (NLP) contexts sum up the contemplated paradigm.
The prototype takes a depth-first approach in demonstrating certain novel traits of artificial intelligence in NLP domain targeting a small representative set of natural language symbolic constructs (words and phrases). A breadthwise scale up of the prototype will result in programs that have minds in exactly the same sense human beings have minds, in terms of a semantic response to information in NL format (a human-like Semantic NLP Paraphraser/Summarizer). This will transform all aspects of information generation, processing, and consumption over the internet and elsewhere.
description of what is included
The prototype involves generation of semi-autonomous and semi-original1 intelligence that is demonstrably consistent with our own, in paraphrasing a NL sentence. The Omnijective contexts within which the demonstration gets setup allows for a rather simplistic enactment of program-level Occam’s razor in the synthetic agents interpreting the semantic contents of the sentence. Moreover, subjective aspects of intelligence get emphasized with three distinct synthetic agents – a philosopher, a romanticist, and a neophyte – each evolving respective algorithm in a bid to semantically comprehend the input NL object in accordance with implied sensibilities (An Example provided below). The prototype takes advantage of such multi-agent scenario to demonstrate the following notions2:
- Thought Primacy: The idea that a foundational thought standing upon Omnijective axioms assumes preeminence over incidental intelligence and other related notions of comprehension, sentience, sapience, and common sense. Essentially ‘thought’ is regarded fundamental3, with varied particulars of the Omniject-Oriented method involved in simulating human thought of which intelligence and other cognitive capabilities are mere derivatives.
- Algorithmic Fluidity: Refers to the ability of evolved algorithms to take on other consistent forms that signify alternate valid subjective interpretations upon finite persuasion. This provides basis for enabling several seemingly disparate human-like capabilities of planning (& changing plans as deemed fit), decision making, certain categories of problem solving, and more.
- Common way of Sensing (among the synthetic & human agencies): Not only do the synthetic agencies that subscribe to given Omnijective contract share a common basis for sensing, but such ‘common sense’ could transcend to the human world given specified nature of composition of the underlying Omniject. This, along with the below feature (Native, Non-trivial Semantic), helps in terms of general learning capabilities of the machines, particularly by enhancing human-machine interface.
- Native, Non-trivial Semantic4: While statistics provide an indispensable tool kit to deterministic pursuits, Omniject-Orientation takes an exception to the prudence of ‘playing dice’ in architecting a self-sustained program capable of original intelligence5. This transforms current machine learning (ML) paradigm to make way for more aligned patterns with human learning process that involves one-shot or zero-shot learning.
- Experiential Sentience: Deviant from the prevailing practice of keyword-based sentiment analysis, an organic semantic-predicate-based-sentience gets demonstrated in synthesizing complex emotions such as empathy. This detaches the source of the synthetic agent’s emotions from the Omniject-external influences such as declarative or programmatic instructions from the human programmer. Emotion, like comprehension, is a purely native notion in the worldview offered by Omniject-Orientation & gets synthesized dynamically from fundamental Omnijective building blocks.
- Retro/Antero fitting of Predicates (of understanding): A relatable human experience of antero-fitting-of-predicates in assigning inflections to base form of the verbs to comprehend word meanings in isolation is illustrated in NLP contexts. Further, the prototype showcases the ability to comprehend grammatically ill formed sentences using retro-fitting-of-predicates. While the sentence correction is in itself not a novelty, comprehension/sentience driven object transformations not backed by statistical learning is. Such an enablement renders the synthetic agents the ability to handle uncertainties and of subsequent resolution in unchartered/unfamiliar contexts.
- Various subtle theoretical nuances that go into generation of synthetic thought and extraction of a consistent response combining all endowed cognitive faculties from so synthesized thought gets illustrated in the prototype. The emphasis of the project is not just on underlining the gap between prevailing notions of AI and the proposed human-like variant of it, but also in providing a roadmap for further pursuit towards a fully free willed, introspective, and ethical (benevolent) human-level intelligence.
Of particular note are the cognitive abilities displayed by the synthetic agencies, bi-directional between the reality (i.e., the input sentence) and the machine-mind, as a function of an a priori theorization of human cognition abstracted by the Omnijective contract, rather than being derived from explicit instruction, statistical learning, or trial and error basis.
An Example
In the holistic schema advanced by Omnijectivity, intelligence is an inseparable aggregation of all cognitive faculties endowed to a subject agency. Such an intelligence gets illustrated as synthesized fluid algorithms by distinct agents who ‘understand’ each other. The mutual understanding gets established by the way agents determine the transformation path required of respective algorithms to morph to the interpretation of the others.
In case of the example below, for the input NL object:
| Reading about weather in books is one thing, but living through a natural disaster was another. |
the prototype generates three algorithmic interpretations, one each for the philosopher, the romanticist and the neophyte as below:
| Philosopher: Experience triumphs knowledge. |
| Romanticist: Experiencing a natural disaster could be scary. |
| Neophyte: Knowing about natural disasters is not the same as experiencing them. |
The agents understand 3rd point perspectives arising from their peers in addition to appreciating how and why the different interpretations are valid. Tendency of the philosopher to navigate the Omnijective semantic towards relevant fundamentals, predisposition of the romanticist to dwell upon the experiential aspects of the native phenomenon, and naivety of the neophyte in a relatively simplistic comprehension of the object reality – while evident for an external human observer are not lost to the machine mind too.
It might be of interest to note that all the human-like intelligence traits listed above find space in generating synthetic intelligence associated with such simple looking NL object (and a handful of its variations).
FOOTNOTES
- Semi-originality and semi-autonomy referred to connote the distinction between human-like and human-level intelligences in Omnijective contexts. The semi qualifier implies Adjectivized but not Acontextualized intelligence.
- Some of these demonstrables viz. Thought Primacy, Algorithmic Fluidity, Native Non-trivial Semantic, and Experiential Sentience provide 4 out of a total of 9 criterion for human-level intelligence, advanced in corresponding fundamental aspect of (as yet unpublished) research. Other criteria relate to the Acontextualization capabilities endowed to the synthetic agents, that are not in the scope for Project-POC. In the eventual picture, the collection of criteria is the proposed measurable counterpart to Turing Test.
- This demands different methodologies for testing. Newer paradigms of Consistency over Correctness emerge where the process itself gets tested for its consistency with redefined notions of correctness that are applicable to original and unpredictable outcomes.
- Non-triviality essentially places an emphasis on the Nativity of the semantic in signifying ‘not sourced out of the programmer’s mind’.
- In addition to statistically extracted object patterns through ML, other staple seed of intelligence for current day cognitive architectures such as rules and meta-rules, semantic nets spun over corpus of facts, domain ontologies etc., are also inadmissible in representing semantics within an Omniject.
impact summary
In applied contexts of general AI, the contemplated paradigms make a case for pioneering technological stacks that support unconventional ways of programming, knowledge modeling, machine training, and testing etc. In fact, the very understanding of intelligence acquires a more pragmatic operational definition, with much sought-after generality of AI being inseparable from the notion of intelligence itself. Such a fundamentally disruptive worldview paves a way that extends well beyond the objectives of the third wave of AI, towards an absolute and ethical synthetic autonomy.
More generally, given the fundamental aspects of the research entail probing unassailable confines intrinsic of human scientific endeavor in fashioning the proposed method, the implications are far-reaching and multi-disciplinary. The impact is particularly accentuated in case of elementary fields of study like physics and mathematics. Also, the qualitatively distinctive complexities involved provide an opportunity, both to academia and industry alike, in envisaging possibilities which may not be conceived in our adherence to the status quo.
To sum up, this study lays out the foundations to explore the road not taken by the human sciences, the path that could not have been considered earlier in our inescapable allegiance to phenomenological natural attitude. The wiggle-room offered by Omniject-Orientation to such constraining norm promises to hold the key not only to a host of imminent technological challenges necessitated by a drastic transformation of human life-styles due to internet explosion in recent decades, but for several persistent problems faced by human sciences.
project summary
The project demonstrates a method that complements the human sensory analogue of object pattern extraction, the core competency of present AI/AGI architectures, by offering the cerebral equivalent of assigning and extending consistent native semantics to so identified patterns. Such subject-side-tilt of the proposed method provides an integrated basis for machine comprehension, intelligence, sentience, and common sense, while relatively extraneous cognitive conceptions to the method such as multiple perception modalities, memory management, attention mechanisms etc. were scoped out of this project.
Though the proposed model for general intelligence is domain neutral, linguistics provides a convenient context for illustration purpose owing to its relatability with the notion of semantics and other reasons. Consequently, Pragmatic Analysis in the domain of NLP was chosen to demonstrate the method in this project. Multi-agent scenarios were conceptualized to emphasize the characterization of the envisaged variant of AI. Essentially, such synthetic intellect could break through the reserve of current day AI in terms of application, to encompass the realms of ‘the abstract‘.
Glossary of Terms
Acontextuality: The postulated working principle behind all human cognition – the focal point for all A3ilabs activity.
Acontextuality abstracts the working principle, deemed to be at the source of human cognition, that endows human specific traits to the ensuing intelligence that are commonly qualified as original thinking, abstract thinking, & intuition etc. The fundamental levels of cognition at which Acontextualization is supposed to play out provides consistent basis for various aspects of human intelligence viz. analytical, linguistic, emotional, spatial etc., albeit within respective operational setup. The fundamental aspect of this study conjectures such notion as Acontextualization to be the fount of all human intelligence, which when applied programmatically in connection to synthetic intelligences is the proposed method for human-level general intelligence.
Though Acontextuality provides the focus for Project POC, the purpose of the project is much humbler in demonstrating a prerequisite thereof – Adjectivization of AI in the interest of a human-like variant of intelligence.
Adjectivization: A prerequisite for Acontextualization in the pursuit of human-like synthetic intelligence – the focus for A3ilabs Project POC.
Adjectivization (of AI) refers to the architectural, modeling, and procedural considerations involved in devising an enabler framework for programmatic Acontextualization. This process realized in multiple stages essentially transforms the intelligence latent in object representations to a semblance of human contextual comprehension. Such synthetic subjective comprehension allows for a self-sustained progression of the resultant intelligence in a silo separate from the intelligence that created it.
Essentially, Project POC aims at generating Adjectivized Artificial Intelligence (A2I).
Dimensions of Freedom (of AI): Abstract notions along which synthetic agents could maneuver native capabilities afforded to them.
Abstract notions that determine the interaction dynamics between Thesis-Types (analogues to object-oriented datatypes) in attaining what is termed Epistemic Specificity (loosely, contextual knowledge or comprehension).
As part of Project POC, three such dimensions of freedom will get demonstrated viz. theses contiguity (possible in case of NLP because of innate domain object structure), ontologic query contexts (query types that could be posed of Theses), and meta-semantic constructs (predicates signified by Semantic vowels).
Finite Persuadability (of Algorithms): One of the criteria for generated algorithms, implied intelligence of which may be deemed human-like.
Refers to the possibility of a synthetic agent to ascertain a transformation path between two valid interpretations (algorithms depicting potential subjective responses) within given semantic neighborhood of a systemic object.
In general, this property of generated Omnijective algorithms plays a key role in our ability to reason with synthetic agents and provides motivation for inter-agent communication within an Omnijective intelligence system.
Human-like & Human-level Intelligence: Operational definitions for Omnijective variants of AI, analogous to General AI, Strong AI or AGI.
Though Artificial General Intelligence (AGI), general AI, and strong AI have been used across the description of Project POC for relatability purposes, the proposed variant of AI follows an alternate hierarchy of more rigorous operational definitions based on Adjectivization and Acontextualization capabilities of the synthetic intelligence.
As the name suggests, Adjectivization aims at realizing an intelligence that a software agent is as opposed to what it has (been conferred), within contained scopes. Such contention of intelligence, in a non-casual drift, is profoundly distinct from the implicit intelligence-as-a-noun paradigm subscribed by current day approaches to AI/AGI. While prevailing cognitive architectures attempt to make sense of an object in terms of human Semantic that is alien (or superficial, at best) to the synthetic intelligent agents, Adjectivized intelligence is native to the semantic context space of corresponding Omnijective intelligence system. Such contextual intelligence could further be Acontextualized.
Whereas Adjectivized Artificial Intelligence (A2I) corresponds to the human-like intelligence, Acontextualized & Adjectivized Artificial Intelligence (A3I) refers to the eventual goal of human-level intelligence. It may be noted here that human-level intelligence (A3I) is not on the continuum with human-like intelligence (A2I). The difference between these varieties of intelligences is not merely a matter of emphasis but of the kind. And so is the distinction between state-of-the-art AI and proposed Adjectivized variant of intelligence for Project POC.
Inward Extensibility: A desired attribute of knowledge representation modalities for AI systems capable of original & autonomous behavior.
Inward extensibility refers to an attribute of seed knowledge representation formalisms to potentiate indefinitely within set boundaries. All prevailing knowledge modeling paradigms like rules or meta-rules comprise eventualized forms of object semantics at some level of abstraction. These limit availability of inherently original knowledge to current day cognitive architectures.
In case of Omniject-Oriented systems, knowledge eventualization is program scoped with the seed purely depicting the potential for the kind of knowledge to be generated. Semantic alphabet provides such a seed and knowledge is realized in an analogue to the way indefinite linguistic phraseology gets formed from finite alphabet.
Micro-algorithms: Software building blocks that shape up human-like cognitive faculties such as comprehension, sentience, logic etc.
Micro-algorithms are explicit enunciators of the semantic content innate to human-coded programs. For example, a rather simple object-oriented assignment operation of int i=0 is accompanied by several implicit semantic connotations namely –
- ontologic existence of the category of quantitative intuition with cardinality predicate of discrete measure,
- ontologic quantitative polymorph of qualitative nothingness,
- epistemic patterns of variability and assignability, and
- ego-centric pattern/s signifying the purpose/motivation of the programmer in the overall context of the problem at hand, to go for such an assignment.
The machines, of course, neither understand nor care for these semantic undertones in typically assigning a memory segment for the variable ‘i’. An explicit definition to such semantics in object-oriented (algorithmic and statistical) sense might produce more generic classes of programs such as meta-programs or neural networks, but these merely result in shifting the target. In contrast, micro-algorithms directly or indirectly reference the Omnijective fundamentals in providing overt definitions to such semantics from systemic subject standpoint.
Object-Orientation: Defines the generic nature of de facto operational method for all human scientific endeavor.
Object-Orientation relates to the generic characterization of all human pursuit of structured knowledge, classified as such in view of the nature of principal involvement. The approach is marked inevitably by a supplementing deterministic intent of the involved subject agent towards given object entity, as both a means and an end. While such human natural attitude with regard to the object reality has performed exceptionally well – evident from the technological & scientific advancement all around, quest for human-like synthetic intelligence may not however be subjected to this approach.
This understanding is not confined to the programming paradigm that shares the name (Object Oriented Programming) but extends to all human-coded programs ever written. In fact, its roots in the very foundations of human cognitive contexts influence every formal aspect of human episteme including all of our sciences, mathematics, language, programming etc., not to mention our own human logic.
Omnijectivity/Omniject: A fundamentally divergent worldview rolled out in the interest of human-like/level synthetic intelligence. Omniject refers to corresponding operational abstraction.
Omnijectivity refers to the philosophical positioning that the entire paraphernalia sustaining the notions of intelligence, its generation and manifestation are contained within the existence (or an intelligence system), with none taking up a more fundamental pedestal in relation to others. Such a stand not only contends the absolute disposition of the determiner and the determinable but of the determination itself. Subsequently, conviction in the unequivocality of mind-independent object of the realists, object-agnostic mind of the solipsists, indisputable human logic of the rationalists, and the experiential reliance of the empiricists etc. are all brought under the scanner of suspicion.
Although such uber-radical skepticism appears to deprive of all practicability from any possible inquiry, it affords an unprecedented vantage from an external standpoint of the orchestrating intent (human programmer, in case of synthetic intelligence systems) to the melee of existence. Such perspective of an intelligent existence allows for an abstraction thereof as an Omniject, encompassing a wide variety of notions as we see them, including but not limited to the subject and object components, reasoning, and sentience.
Omniject-Orientation: Generic characterization of proposed Theory of Mind in attaining human-like/level synthetic intelligence.
The deterministic intent implied of Object-Orientation relies on the underlying belief in the absolute disposition of the (human) Subject, the Object, and the involved cognitive interfaces (like Comprehension, Sentience, Logic etc.) that enable a liaison between the entities. This belief is what is contested in essence, in an Omniject-Oriented worldview where an original variant of artificial intelligence is possible if and only if the synthetic agents are enabled in native contexts. Such an enabler intent results in a dynamic concoction of native object phenomena and cognitive faculties required in dissecting it.
Project POC illustrates programmatic Omnijective-Orientation in materializing the demonstrables, while highlighting the need of such enabler intent to propagate to other tools & techniques of object exploration like Mathematics in terms of what could not be demonstrated.
Omnijective Axiomatic Scaffold: A support structure for the systemic foundationalist Semantic that is in sync with the human equivalent.
An elaborate schema of axiomatic hierarchies belonging to Ontologic, Epistemic, and Ego-centric tiers of associated Omniject. These axiom taxonomies not only delineate the generic object contexts in terms of corresponding subjective beliefs, but also let evolve subject contexts in line with the target domain-specific object, as stipulated by the laid out Omnijective contractual guidelines.
As could be expected, identification of the axioms is the starting point in practical implementations of Omnijective intelligence systems. These axioms further facilitate the development methodology of Omniject Oriented Programming and help in evolving a foundationalist seed semantic with a potential character.
Omnijective Contract: This contract between the systemic Subject and the Object components, constitutes the core of the proposed method.
Omnijective contract essentially signifies the mind of the programmer in relation to the intelligence system – an intentionality dump encapsulating the systemic notions of the Ontologic reality, qualified autonomy privileged to the Ego-centric agencies, and an abstract Epistemic basis to tie these together. All systemic subject agencies inherit so abstracted out programmer’s mind in extending skewed instances of the creator’s intent as per independently enabled subjective sensibilities/tendencies. Required mathematical formalism to abstract involved complexities & various operational specificities in drafting such contract for human-level intelligence is not determined yet, though Omnijectivity is projected to provide required contexts for such an undertaking.
Project POC illustrates the subjective enablement required in engaging agents to the contract by way of assigning saliences to the epistemic patterns in simulating mind analogues of individual agencies. Though this violates one of the core contractual clauses – non-triviality of the Semantic (refer to Native, Non-trivial Semantic in the listed demonstrables under The Prototype) – enabled multi-agent scenarios due to such external intervention help in demonstrating several features of human-like intelligence.
(Omnijective) Heuristics: Antidotes to the limitations posed by an algorithmic approach in synthesizing human-like/level intelligence.
Conceptually, heuristics denote fundamental units of the enabled system native behavior – of both the generic subject and object components of the Omniject. While subject-side heuristics combine to shape up various epistemic and ego-centric patterns, object-side heuristics (called H-lets) help in modeling the ties between ontologic contextualities. Corresponding units of software building blocks developed in Omniject-Oriented Programming paradigm are also called Heuristics. One of the most important type of heuristics in quest for human-like/level intelligence are Micro-algorithms.
(Omnijective) Intentionality: A comprehensive subjective response to given systemic object that further goes on to synthesize the behavior.
A phenomenological notion adapted to Omnijective contexts. It is an amalgamation of intelligent agent’s systemic purpose, motivation, and inherent capabilities in synthesizing a native intent directed towards given object instance. Impetus for such an amalgamation forms the prime differentiator between human-like and human-level intelligences. In case of the former, the impetus partly originates from the programmer’s intelligence whereas the later sources the impetus purely from within (Acontextuality in a nutshell). Algorithmic core of state-of-the-art AI entirely relies on the intentionality of the programmer, the only available source of Acontextual intelligence in the process of intelligence synthesis.
In case of Project POC, for example, the overall intent of paraphrasing the input NL object arises from the programmer’s mind. However, various novel demonstrable features (as listed in The Prototype) owe their possibility to the internalization of certain facets of required intentionality.
Omniject Oriented Programming: An unconventional programming paradigm resulting from a fundamental switch in programmer’s intent.
Omniject oriented programming paradigm offers an object-view to the nested Omnijective realities of Adjectivized or Acontextual intelligence systems. This facilitates development of the fundamental units of system native behavior, as heuristics, which when orchestrated as per the ask of given object, afford an algorithmic structure to associated systemic response. In addition to so leveraging subject-side programming of the ‘machine mind’, heuristics also provide formal logic structures to model the ties between Ontologic contextualities of corresponding Semantic.
Omnijective enablement of the subject component (synthetic agents) involves providing an Ego-centric view of the Ontologic reality that is made up of axioms and other fundamental constructs. These are mere bits and pieces of information that need be coalesced to afford a cohesive object-oriented view of the systemic object reality to the synthetic agents. Consequently, the principles of Object-Oriented Programming find applicability in such an undertaking, although subject to few provisos. The fundamental units of the enabler software, the Heuristics, for example, encapsulate Ontologic contextualities and meta-heuristics as data and behavioral elements respectively. Polymorphism extends to the data representational aspects of a Heuristic, allowing context specific interpretations not just to meta-heuristics but also to the contextuality ingredients viz. semantic vowels and consonants. Heuristic inheritance hierarchies that together constitute the behavioral framework specific to the Omniject, necessarily find their roots in the Ego-centric axioms/anchors. Although the heuristic development governed by these principles helps in adhering to the Omnijective contract in the conduct of general intelligence, Omniject Orientation essentially relies on various abstract programming & design directives, that flow out of the principles of Omnijectivity.
Radical transformation required of the programming intent & other intricacies of such counter intuitive paradigm may to some extent be harnessed by fashioning Omniject-Oriented dialects of Object-Oriented programming languages (like Java/Python). The point of these dialects is to consume the Omniject referencing object contextualities in abstracting the abducible predicates as custom keywords and annotations, in the interest of a wider adaptation of an otherwise prohibitively complex endeavor. However, proposed method illustration presents under-the-hood Object-oriented (Java) code of the heuristics, for demonstration purpose.
Omniject-Oriented Mathematics & Physics: Future research prospects with high dividend potential in applied Omnijective domains.
Work for the future in both enhancing human-like capabilities & in empowering human-level autonomy of the agent programs. The application of these branches is likely to spill over to other fundamental research domains as well.
In illustrating human-like synthetic intelligence, Project POC underlines the need for varied multi-disciplinary fields of research required to mitigate the limitations inherent to the method. Whereas Omnijectivity provides both the contexts and the methods for these research areas, several grey areas of varying shades abound that require further attention.
Potential Semantic Schemata: Fundamental abstraction of systemic knowledge that cedes scope for subjective interpretation & discovery.
The ‘being and becoming’ aspects of the systemic object reality get abstracted by the Ontologic axiom hierarchy, while Ego-centric axioms wrap the reality, associating subject specific system-native understanding to it. Epistemic patterns provide a structure to the systemic body of knowledge that constitute these subjective interpretations, that may or may not have been eventualized yet. Omnijective intelligence systems thrive within the definition of such a schema representing the fundamental levels of knowledge abstraction, referred to as potential semantics.
Bootstrapping an Omniject for Adjectivized/Acontextual intelligence systems, with an intent of human-like/level intelligence, requires synchronization of the fundamental axioms on which the body of systemic potential knowledge stands with those of the human Semantic. The point is not just to match the seed values but also to align bounds of the resulting semantic space within which the foundationalist knowledge transpires. These form the prime considerations in the formulation of the principles of Omnijectivity (esp. the Principle of Composition).
Principles of Omnijectivity: Principles that govern the erection of an Omniject and hence of enabling Omniject-Orientation.
Project POC is supposed to be an applied illustration of the principles of Omnijectivity in the restricted contexts of NLP. Though a fuller fundamental deliberation of the principles is not within the scope of the project, an overview of the principles in relation to proposed POC prototype is provided here –
0) Fundamental Principle of Omnijectivity: Defines the nature of intelligence in Omnijective contexts. This forms the basis for the proposed human-like intelligence in Project POC.
1) Principle of External Complementarity: Establishes a complementary relationship uniting the Programmer & the Program in a programmatic approach for synthetic intelligence. The need for a continual dialogue between the counterparts is implied in synthesizing intelligence.
2) Principle of Composition: Stipulates the character of dialogue between the enabling intent of the programmer and deterministic intent of programs in generating original intelligence. Also, Omnijective composition and boundaries get defined here.
3) Principle of Internal Complementarity: Concerns the subsistence & a symbiotic relationship between various internal complementing dualities of program-programmable, program and associated intentionalities, programmable and corresponding semantic contexts etc. This provides the contexts for drafting the Omnijective (Subject-Object) contract.
Semantic Alphabet: One of the Omnijective contractual artifact that is an abstraction of higher-level semantic combinations of axioms.
Semantic Alphabet is one of the principal contractual artifacts that is an abstraction of common denominatorial patterns constituting subject and object contexts. These fundamental building blocks coalesce to form word analogies, that in turn come together adhering to human comprehension-oriented semantic grammar rules, to reference ‘object meaning’ as understood by the human modeler/programmer. The relative Omnijective reality represented thus is primed for Adjectivization (& eventual Acontextualization) in the process of intelligence squeeze. Several convenience constructs such as semantic domain anchors, various types of semantic dictionaries and thesaurus etc. also comprise the Omnijective contract, with obvious analogies and implications.
Leave a Reply