Powered by Deep Learning
MulticoreWare delivers state-of-the-art high performance AI based analytics solutions for any media content. We differentiate our solutions by leveraging our core competencies in Video, Deep Learning and Micro-architecture aware performance optimizations.
Machine Learning and Neural Network techniques can be applied to large range of problems across multiple industries. We’ve worked on many areas and can bring that experience to your specific problem.
MulticoreWare’s LipSync technology uses Deep Neural Networks to “watch” and “listen” to videos and determine if content is correctly synchronized. Trained classifiers are used to find and match human faces to human speech, allowing LipSync to detect errors that are not found by current automated video quality control systems.
Neural networks can require vast amounts of training data, but often data does not come labeled or tagged. MulticoreWare has a dedicated team of in-house data analysts to perform any type of labeling task. Tagging can be performed confidentially and the team can be trained for complex labeling tasks that cannot typically be done by untrained eyes. We use our own custom tools to perform labeling quickly and accurately and also provide these tools to our customers.
The platform for running the prediction path of neural networks can include server-class hardware with accelerators, mobile device SoCs, FPGAs, and custom embedded platforms. Based on your target platform, compute resources, memory footprint, and mathematical precision must be chosen very carefully. We’re experienced in optimizing a neural network path for a number of architectures and platforms to improve performance and power efficiency while retaining its accuracy and predictive capability.
Choosing a neural network architecture for your target hardware and applications and training it is no trivial task. Our team of 50+ experts can leverage their research knowledge to design and train a network for your task and provide a comprehensive solution using our own proprietary technology or using open-source technology such as Torch7, Caffe, CUDA Convent, Theano and others. We can also provide consulting services based around these technologies.
Mobile devices and handsets equipped with cameras represent the largest market for image and vision processing. We’ve worked with device manufacturers, app developers, and semiconductor vendors to improve the capability of their devices by utilizing the CPU, GPU, DSP, and other processing elements available in modern SoCs.
MulticoreWare has experience in using, optimizing, and porting the most popular and high performance Neural Network frameworks available for building NN applications. We also develop tools for customers to support interoperability and conversions between the unique Neural Network representations used by each framework.