Rosetta Stone Translations

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The Rosetta Stone was carved in 196 BC for Egyptian King Ptolemy V. .Rediscovered in 1799, the 114.4 x 72.3 x 27,9 cm (45 x 28.5 x 11 inch) granodiorite stone is unique in that it is inscribed with three written languages: Egyptian hieroglyphs, Demotic, and Greek script that all pronounce the same royal decree.

Science

"An Overview of the Paleoclimatic Influences on the Genetic Variation of Chelydra" published in the Bulletin of the Chicago Herpetological Society by Jack M. Corbo (MS) and Dr. H Greg McDonald, 51(7): 105-117, 2016. Author contributions: J.M.C. led the writing and conceived most of the ideas with some editing while H.G.M. led the editing with some writing and conceived some ideas. Cover art by Richard F. Deckert (1919) suggested and provided by Jack Corbo.

2002 CV of Dr. Peter Dunham (field advisor to Jack Corbo)

Jack Corbo

Rampart Cave Ground Sloth Habitat

Jack Corbo

Rampart Cave Fire in 1976

Jack Corbo

Rampart Cave discovered in 1936 is located Grand Canyon National Park, Arizona. The rare cave was inhabited by Nothrotheriops shastensis (Shasta Ground Sloth) 13 kya and 36 kya. Paleontological excavations found deposits of this megafauna species at depths of 6 m (20 ft) deep. A majority consisted of dung deposits that gave the cave the smell of a horse stable. The dry dung was also combustible which tragically occurred in 1976. The cave could be considered a repository or archive of the ecology and the genetic change of N. shastensis over more than 30,000 years.

Jack Corbo CV (unedited)

Jack Corbo

Jack Corbo CV (unedited)

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Lunar Mining of Helium-3 for Fusion Reactors

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FAIR & AI Ready KGs for Explainable Predictions

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The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed. In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine. Bio Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.

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Rosetta Stone Translations

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