Deep Fakes in real time
Deep Fakes are imitations of pictures and video, created using artificial intelligence. Common scenarios include exchanging faces in order to create the illusion to see another person in a video. Within the scope of a research project, the TNG Innovation Hacking team investigated Deep Fakes to better understand what is technically feasible. Furthermore, we wanted to explore the limitations of the technology - especially if and with what image quality it is possible to create Deep Fakes in real time.
Our research shows that it is possibled to exchange the face of a person filmed via a real-time video streamwith the face of another person, including applying facial expressions and movements of the person filmed.
By applying various techniques from the area of computer vision and neural networks, faces in the video feed are recognized, transformed and embedded in the video output. The project uses autoencoder networks trained in Keras. They were trained using so called GANs (Generative Adversarial Networks). Aditionally, the developers used different neuronal networks for face recognition and segmentation.
AI Size Recommender for Fashion
For a large fashion retailer, TNG developed an application that makes individual size recommendations for web shop customers. The task for the solution was – despite a large number of size ranges and partly low availability – to display to individual customers only those products really likely to fit. To do this, we started with an idea workshop, convinced our client by developing a prototype, and finally rolled out a production solution with measurable success. To create the individual size profiles, we experimented with various machine learning approaches. The final version was then implemented using AWS Lambda and Elasticsearch.
Launch of a Real Time Chat App
To strengthen the contact between customers and pharmacists we supported a wholesale pharmaceutical company in the development of a chat system.
As a "progressive web app", the chat is available without installation and is optimized for mobile devices. We employed cloud services and among many other services a GraphQL interface.
Users' feedback is collected and incorporated into the product, along with improvements and features, in an agile scrum process.
Modularization of a Monolithic Legacy Application through New Architecture and UI
We designed and verified a new architecture for a provider in the logistics sector, enabling incremental migration from two monolithic legacy applications to state-of-the-art modules. We supported risk reduction though various proofs of concept – particularly for the seamless integration of a modern React UI into the existing ExtJS application, as well as to verify backend integration mechanisms.
Introduction of a Cloud Microservice-Platform
We supported a client in building a microservice platform as part of a worldwide technology program. The platform is based on AWS and Kubernetes, which act as a blueprint for new service development and serve as a means to move the concern towards agile processes and Dev Ops.
The implementation of an automated, cloud-based CI/CD pipeline and templates for service development and deployment processes allow services to be delivered in a quality-controlled as well as cost-efficient way.