Project

Challenge

An efficient and goal-oriented use of artificial intelligence (AI) in real application scenarios requires detailed knowledge and, above all, experience in handling and using the corresponding technologies and concepts. Especially for SMEs the entry barriers are therefore high to position themselves on the market with innovative business models and products using AI.

This applies equally to new innovative approaches to combining AI and quantum computing (QC). Although there are a large number of algorithms for quantum computers, for example on websites, in textbooks and scientific publications - however, which algorithm can be used in which situation and how AI methods and algorithms can be executed on a manufacturer-specific quantum computer requires a comprehensive understanding of the theory and technology. Even if suitable algorithms are found, their implementation in executable programs that provide added value requires deep knowledge of the development environment of the respective quantum computers, as well as of the data essential for machine learning to train models.

Due to the complexity and novelty of these technological trends, there is a lack of easy access to know-how, data, algorithms, and experts in these fields, and especially the exchange of knowledge about open ecosystems and platforms.

Therefore, the development of a broad community based on a common platform for knowledge and technology exchange for Quantum-inspired Machine Learning (ML) is an opportunity to enable the economy and especially many SMEs to use both fields of technology and to guarantee access to these future key technologies.

Approach

This is exactly where the concept of PlanQK comes into play. The goal is the development of an open platform for Quantum-inspired Artificial Intelligence - QAI for short - to create and promote a corresponding ecosystem of Artificial Intelligence (AI) & Quantum Computing (QC) specialists, developers of concrete QKI applications as well as users, customers, service providers and consultants. The PlanQK platform, thus, provides the technical basis for the development of a community for Quantum-inspired Artificial Intelligence (QAI). The central artifacts are corresponding QAI algorithms, applications as well as data pools, which can originate from different sources.

PlanQK Vision

The QAI-Platform allows the capturing of algorithms from sources such as the web, published articles or books. In addition to ML and QC-algorithms, data also play a central role and should be able to be distributed and sold via the platform. Corresponding data pools can for example come from publicly available sources or from users and customers of the PlanQK-Platform. These algorithms and data pools are stored in a special database, the QAI-Algorithm & Data Content Store.

A public community (analogous to an open source community) or specialists of the PlanQK-Platform operator can access this database and analyze, clean up and unify the algorithms and data pools. As a result, each such quality assured algorithm and a number of data pools are stored in the QAI-Algorithm or QAI-Data-Repository. The data pools are used for quality assurance and validation by enabling customers and the community to compare different QAI-Algorithms, for example by using the data pools as training and test data.

Based on the quality-assured algorithms, developers can now implement these algorithms for execution on a quantum computer. These programs, called QAI-Apps, are also quality-assured and stored in the QAI-App-Repository.

Customers of the PlanQK platform can search for algorithms or data and buy corresponding, quality-assured algorithms and data pools. They can also use content directly without payment, which is provided for free. Likewise, programs that implement such algorithms, i.e. QAI-Apps, can be searched, purchased or, if applicable, used free of charge. If an algorithm or a data pool for a certain problem or domain cannot be found or if an algorithm is not yet implemented by a program, the customer can make corresponding requests to the community, service providers or even the platform operator.

When a purchase is made, the platform is capable of automatically packaging the algorithm or the program and any corresponding data to provision the package to a desired runtime and quantum computer for immediate execution and use.