Sony has made available in open source its “Neural Network Libraries” which serve as framework for creating deep learning programmes for AI. Software engineers and designers can use these core libraries free of charge to develop deep learning programmes and incorporate them into their products and services. This shift to open source is also intended to enable the development community to further build on the core libraries’ programmes.

Deep learning refers to a form of machine learning that uses neural networks modelled after the human brain. By making the switch to deep learning-based machine learning, the past few years have seen a rapid improvement in image and voice recognition technologies, even outperforming humans in certain areas. Compared to conventional forms of machine learning, deep learning is especially notable for its high versatility, with applications covering a wide variety of fields besides image and voice recognition, including machine translation, signal processing and robotics. As proposals are made to expand the scope of deep learning to fields where machine learning has not been traditionally used, there has been an accompanying surge in the number of deep learning developers.Neural network design is very important for deep learning programme development.........To continue reading click here

Cisco is reinventing networking with the network intuitive. Cisco employs machine learning (ML) to analyse huge amounts of network data and understand anomalies as well as optimal network configurations. Ultimately, Cisco will enable an intent-based, self-driving and selfhealing network. The network will redirect traffic on its own and heal itself from internal shocks, such as device malfunctions, and external shocks, such as cyberattacks.......To continue reading click here

With the clinical introduction of digital pathology, pioneered by Philips, it has become possible to implement more efficient pathology diagnostic workflows. This can help pathologists to streamline diagnostic processes, connect a team, even remotely, to enhance competencies and maximise use of resources, unify patient data for informed decision-making, and gain new insights by turning data into knowledge. Philips is working with PathAI to build deep learning applications. By analysing massive pathology data sets, we are developing algorithms aimed at supporting the detection of specific types of cancer and that inform treatment decisions......To continue reading click here

Microsoft’s Project InnerEye developed machine learning techniques for the automatic delineation of tumours as well as healthy anatomy in 3D radiological images. This technology helps to enable fast radiotherapy planning and precise surgery planning and navigation. Project InnerEye builds upon many years of research in computer vision and machine learning. The software learned how to mark organs and tumours up by training on a robust data set of images for patients that had been seen by experienced consultants..... To continue reading click here

Siemens has been using smart boxes to bring older motors and transmissions into the digital age. These boxes contain sensors and communication interfaces for data transfer. By analysing the data, AI systems can draw conclusions regarding a machine’s condition and detect irregularities in order to make predictive maintenance possible.

AI is used also beyond industrial settings, for example to improve the reliability of power grids by making them smarter and providing the devices that control and monitor electrical networks with AI. This enables the devices to classify and localise disruptions in the grid. A special feature of this system is that the associated calculations are not performed centrally at a data centre, but de-centrally between the interlinked protection devices.....To continue reading click here