We are developing a platform and ecosystem for Quantum Assisted Artificial Intelligence, PlanQK for short. Users should be able to access a quantum AppStore, developers should be able to use quantum platforms in a convenient way and specialists should be able to provide concepts that make quantum computing easily accessible.
Do artificial intelligence applications also need quantum computing?
AI applications consume more and more computing time. Currently, special hardware (graphics cards, neuromorphic chips) is already being used to cover the demand for computing capacity. In the long run, however, a real "quantum leap" in terms of computing power will be necessary if the possibilities are to be expanded.
Why should the new technology of quantum computing start with artificial intelligence?
In the short term, so-called Noisy Intermediate-Scale Quantum Computers (NISQs) are expected, which cannot yet reach the reliability of classical computers. However, AI in particular thrives on the random variation in calculations, which is generated in a complex way on classical computers, but which is quite natural and unavoidable for NISQ systems.
The Challenge: In order to develop AI applications that can benefit from quantum computers, one needs knowledge about the specific quantum hardware platforms and how to connect everything, in addition to domain and AI expertise. This combination of skills is difficult for companies to develop!
The Solution: A community of different experts who can work together through technically useful interfaces, in short PlanQK.
- Users can access a Quantum-AppStore to select directly usable solutions or can submit new development requests, which are implemented by experts
- Developers can easily use Quantum-Platforms to extend and improve their AI-algorithms
- Specialists provide concepts that make Quantum Computing easily accessible even without special expertise
„PlanQK offers companies of all industries and sizes a comprehensive platform for quantum computing and AI with direct access to an extensive community of experts, consultants and service providers. Together we can play a significant role in this large future market, at least in Europe and perspectively also worldwide.“
Andreas Liebing, CEO, StoneOne AG
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.
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.
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.