Edge AI

We have very good experience with our customers in so-called "Fast Track Joint Labs": Together with you we develop a first solution for your embedded AI application within one month.

Typically the process is as follows:

• Kick-Off
• Selection of the required components of the solution
• Fast Proof-of-Concept 
• Box stop meeting and review
  
• Joint development of the final AI application

As a result, an executable solution is created and the know-how is exchanged during the project.

• We guide you quickly through a joint project to the finished AI pipeline in C/C++ or Python
• Jointly developed software components enable you to replicate the development process

If you already have a data set, a proof-of-concept can emerge after just a few days.

• Know-how transfer happens during the project, not afterwards
• Your employees become AI experts for processing your applications (integrated training).

Some of our customers increasingly rely on AI functions in their products. To enable them to act independently, we provide a software suite with which our customers can develop, evaluate and deploy embedded AI pipelines themselves.

• Software suite in the form of coordinated Jupyter notebooks and libraries developed by Fraunhofer in the background.
• Export of final AI pipelines for embedded systems.
• Adaptation of the software suite to your problems, e.g. processing of specific data sources (sensor data, audio, video)
• A half-day introductory workshop, if possible on the basis of your own data

• We recommend the combination with the seminar to build up extended know-how.
• Support for one year, if necessary also incl. development hours
• We are also happy to support you during the final integration, e.g. in the form of a joint lab (see on the right side)

• Enormous know-how transfer through best practices implemented in the software suite
• Immediate ability to act in your AI projects
• We do not leave you alone in your projects

We offer a two-day Zero-to-Hero seminar in order to be able to implement the basics of machine learning in a practical way. The seminar can be tailored to you with the help of your data, if you want further training for your organizational unit.

• With your data and wishes, we create an adapted version of our proven ML Seminar.
• Your participating employees will learn the basics of machine learning including best practices in theory and with practical examples.
• You will receive the seminar materials including the source code used (Jupyter notebooks).

• Quickly build up knowledge in your own team
• Knowledge that can be put into practice immediately

Potential analysis of your problem / your data set as report answering the following questions:

• How well is your problem solvable?
• Which AI processing chains meet your requirements?

• Overview of power requirements / computational demand vs. achievable performance of AI pipelines on embedded hardware.
• The report contains an overview of Pareto-optimal solutions with both classical ML and Deep Learning.
• → How to decide:
  • Is there a compelling need for Deep Learning?
  • On which hardware does a solution fit best?

• Quick assessment of the feasibility on your hardware
• Early information on hardware decisions