How Real World Ontology can help us in the Data Science World of AI Technology? The World Data Ontology could serve as the Single Source/Point of Truth (SSOT/SPOT), Knowledge and Intelligence, Human and Machine. It could be applied as the world model engine for intelligence, learning, inference, decision-making, complex problem-solving and interaction of man-machine superintelligence, innovated as Trans-AI or Meta-AI. Global Data Ontology (GDO) is the prime Single Source/Point of Truth (SSOT/SPOT). The single source of truth, knowledge and intelligence is the world and its data universe, with its causal entities, forces, relationships, principles, mechanisms, laws and regularities.

How Artificial Intelligence will revolutionize financial services is a hot topic among Wall Street technologists. But, just as a home renovation might be delayed by the discovery of extensive foundation problems that need to be repaired first, the financial services industry must improve the quality of its data before it can realize the benefits of AI. Early front-office AI applications, such as Deutsche Bank using AI to predict equity pricing, have won headlines. But there is also significant momentum around applying AI to post-trade processing, compliance and risk management: Instead of manually searching for a needle in a haystack to learn why a trade failed to identify a real issue, AI can pre-emptively flag problems and solve the exception. However, while many capital markets firms have explored AI initiatives, few of these pilot programs (less than 15% according to Forrester Research) have made it into production to yield real business value.

What do disease diagnostics, language learning, and image recognition have in common? All depend on the organization of collective intelligence: data ontologies. In this episode of the a16z Podcast, guests Luis von Ahn, founder of reCaptcha and Duolingo, Jay Komarneni, founder of HumanDX, a16z General Partner Vijay Pande, and a16z Partner Malinka Walaliyadde break down what data ontologies are, from the philosophical (Wittgenstein and Wikipedia!) to the practical (a doctor identifying a diagnosis), particularly as they apply to the field of healthcare and diagnosis. It is data ontologies, in fact, that enable not only human computation -- but that allow us to map out, structure, and scale knowledge creation online, providing order to how we organize massive amounts of information so that humans and machines can coordinate in a way that both understand.