IEML, the Information Economy MetaLanguage, is a constructed language with the same expressive power as a natural language and with computable semantics.
Distinguished from pragmatic and referential semantics, linguistic semantics have been incompletely formalized, with only its syntactic dimension mathematized in the form of regular languages. The paradigmatic dimension of language remained to be formalized. The good news is that, thanks to IEML, linguistic semantics can finally be completely coded. This website introduces IEML’s 3000-word dictionary, its formal grammar, and its tools for building semantic graphs. For an overview of the language, go there.
In the future, IEML could become a vector for a fluid calculation and communication of meaning – semantic interoperability – capable of de-compartmentalizing the digital memory, and to feed the progress of collective intelligence, artificial intelligence, and digital humanities.
INTLEKT Metadata long-term vision is to gather a community of users able to exchange semantic models and sub-models on a collaborative platform, which will accumulate a trove of metadata commons.
Which new perspectives would IEML bring if it was adopted as a Semantic Protocol?
First, general semantic interoperability. Semantic interoperability means that – coded in IEML – the meaning will be computable and easily sharable. Semantic interoperability is not about formats (like RDF, for example) but about architectures of concepts, ontologies and data models that would be connected across different domains, because nodes and links can be brought back automatically to the same dictionary according to the same grammar. Semantic interoperability means essentially an augmented collective intelligence.
For neuronal AI, if the tokens taken into account by the models were variables of a semantic algebra instead of phonetic chains of characters in natural languages, the machine learning would be more effective, and the results would be more transparent and explainable. My intention is to pursue the research direction of « semantic Machine learning ». Labelling / annotating data with good ontologies helps *generalization* in machine learning!
For symbolic IA, we would have concepts and their relations generated by semantic functions. Even more importantly, the mode of definition of concepts would change radically. Instead of having concepts that are defined separately from each other by means of unique identifiers (the URIs) on the model of referential semantics, we would have concepts defined by other concepts of the same language, like in a dictionary.
We know that there are problems of accumulation, sharing and recombination of knowledge between AI systems / models. A semantic protocol based on IEML will lead to logical de-compartmentalization, neuro-symbolic integration, accumulation and fluid recombination of knowledge.
The blockchain domain is important because it means the automation of value allocation. Today, smart contracts are written in many different programming languages, bringing problems of interoperability between machines and readability for non-programming humans. With a semantic protocol based on IEML, smart contracts would be readable by humans and executable by machines.
The metaverse is about an immersive, interactive, social and playful user experience. Today, it includes mainly simulations, reproductions or augmentations of a physical 4D universe. With a semantic protocol based on IEML, the Metaverse could contain new sensory-motor simulations of the world of ideas, memory and knowledge.
A scientific revolution has already started with the digitization of archives, the abundance of data produced by human activities, the increased computer power availability, and data sharing within transdisciplinary teams. The name of this revolution is of course «digital humanities». But the field is still plagued by theoretical and disciplinary fragmentation, and weak mathematical modelling. With a semantic protocol based on IEML, the world of meaning and value would be unified and made computable. (Again, this does not mean reduction to quantity, or any kind of reductionism, for that matter). It would foster the emergence of an inexhaustible and complex semantic cosmos allowing for every point of view and every interpretation system to express itself. It would also lead to a better exploitation of a common memory, bringing a more reflexive knowledge to human communities.
Semantic Interoperability at the Service of Collective Intelligence
At INTLEKT, we create semantic metadata systems fitting your organization’s needs with a focus on complex human systems like games, health, education, the environment and urban phenomena.
Benefiting from our unique technology IEML, the Information Economy MetaLanguage, complex models becomes explorable, interoperable and can be translated automatically in several natural languages.
Our lead consultant Pierre Levy, Ph.D., Fellow of the Royal Society of Canada, has a deep experience in knowledge engineering. He has published thirteen books translated in twelve languages, including the titles Collective Intelligence, Becoming Virtual and The Semantic Sphere exploring epistemological and anthropological aspects of digital technologies.