TypeDB is a strongly-typed database with a rich and logical type system. TypeDB empowers you to tackle complex problems, and TypeQL is its query language. TypeDB allows you to model your domain based on logical and object-oriented principles. Composed of entity, relationship, and attribute types, as well as type hierarchies, roles, and rules, TypeDB allows you to think higher-level as opposed to join-tables, columns, documents, vertices, edges, and properties.
 
TypeDB allows you to model your domain using the well-known Entity-Relationship model. It is composed of entity types, relation types, and attribute types, with the introduction of role types. TypeDB allows you to leverage the full expressivity of the ER model, and describe your schema through first normal form.
 
Types provide a way to describe the logical structures of your data, allowing TypeDB to validate that your code inserts and queries data correctly. Query validation goes beyond static type-checking, and includes logical validation of meaningless queries. With strict type-checking errors, you have a dataset that you can trust.
 
TypeDB encodes your data for logical interpretation by a reasoning engine. It enables type-inference and rule-inference, which create logical abstractions of data. This allows the discovery of facts and patterns that would otherwise be too hard to find; and complex queries become much simpler.
 
TypeDB's API is provided through a gRPC client, providing bi-directional streaming, compression, and strong message typing, that REST APIs could not provide. TypeDB Clients are delivered as libraries in dedicated languages that provide stateful objects, Session and Transactions, for you to interact with the database programmatically.

TypeDB is a strongly-typed database with a rich and logical type system. TypeDB empowers you to tackle complex problems, and TypeQL is its query language. TypeDB allows you to model your domain based on logical and object-oriented principles. Composed of entity, relationship, and attribute types, as well as type hierarchies, roles, and rules, TypeDB allows you to think higher-level as opposed to join-tables, columns, documents, vertices, edges, and properties.

TypeDB - A strongly-typed database

Pyro is a universal probabilistic programming language (PPL) written in Python and supported by PyTorch on the backend. Pyro enables flexible and expressive deep probabilistic modeling, unifying the best of modern deep learning and Bayesian modeling. 
 
Probability is the mathematics of reasoning under uncertainty, much as calculus is the mathematics for reasoning about rates of change. Models built in the language of probability can capture complex reasoning, know what they do not know, and uncover structure in data without supervision. Further, probability provides a way for human experts to provide knowledge to AI systems in the form of a priori beliefs.
 
Specifying probabilistic models directly can be cumbersome and implementing them can be very error-prone. Probabilistic programming languages (PPLs) solve these problems by marrying probability with the representational power of programming languages. A probabilistic program is a mix of ordinary deterministic computation and randomly sampled values; this stochastic computation represents a generative story about data.

Pyro is a universal probabilistic programming language (PPL) written in Python and supported by PyTorch on the backend. Pyro enables flexible and expressive deep probabilistic modeling, unifying the best of modern deep learning and Bayesian modeling.

Pyro - Deep universal probabilistic programming with Python and PyTorch

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