New AI Research Hub to Leverage Artificial Intelligence to Tackle Major Military Challenges

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The U.S. Army Artificial Intelligence (AI) Task Force was inaugurated when Commander General John Murray applied the U.S. Army Futures Command (AFC) patch to the left arm of Brigadier General Matthew Easley's uniform with a hearty slap. Easley is now officially in charge of the new taskforce. In close collaboration with Carnegie Mellon University (CMU), the U.S. Army has also established the first AI Hub to be located in Pittsburgh, Pennsylvania and Carnegie Mellon's National Robotics Engineering Center. A key role of the AI Hub will be to increase collaboration with ANSYS and other academic, industry and government agency partners. The Army AI Taskforce will be focused on developing and prototyping AI capabilities for several critical areas of the Army -- including an on-going project focused on predictive maintenance.


ANSYS Electronics Simulation Expo: Engineering The Internet Of Things

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The ANSYS Electronics Simulation Expo was conducted in Bangalore on the 3rd of June 2016, with a focus on helping the engineering community improve electronic system design. The event started off with a welcome note by Rafiq Somani, the country manager for India, ASEAN and ANZ at ANSYS. This was followed with a keynote talk delivered by Sudhir Sharma, global industry director, High Tech, ANSYS. One of the most interesting sessions at the event was a panel discussion on "Engineering the Internet of Things". The topic is quite apt, as most other IoT related events tend to focus only on business aspects pertaining to how massive connectivity and big data affected systems and processes.


First big data and machine learning system for engineering simulation

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ANSYS has released its SeaScape architecture for product developers. SeaScape is claimed to allow organisations to innovate faster than the ever by bringing together the advanced computer science of elastic computing, big data and machine learning and the physics-based world of engineering simulation. Engineering simulation generates huge amounts of data - more than most organisations can effectively leverage for future product designs. At the same time, engineering supercomputing resources are not keeping pace with the demand for higher fidelity simulations needed for increasingly complex products. By leveraging such big data technologies as elastic compute and map reduce, SeaScape is said to provide an infrastructure to address these issues in the context of almost any engineering design objective.


Machine learning digs big data within EDA tools

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Engineering simulation generates tremendous amounts of data – far more than most organizations can effectively leverage for future product designs. A typical integrated circuit, for example, has billions of variables that can be simulated. At the same time the highly specialized engineering supercomputing resources are not keeping pace with the demand for even higher fidelity simulations needed for increasingly complex products. By leveraging such big data technologies as elastic compute and map reduce, SeaScape provides an infrastructure to address these issues in the context of almost any engineering design objective. ANSYS has collaborated with Intel Corporation to optimize SeaScape to take full advantage of the many-core Intel Xeon processor and Intel Xeon Phi processor families.


Siemens simulation offering hastens the arrival of self-driving cars

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Leveraging advanced, physics-based simulation and innovative sensor data processing technologies, the new Siemens solution is designed to help automakers and their suppliers address this industry challenge with the potential to shave years off the development, verification and validation of self-driving cars. TASS' PreScan simulation environment produces highly realistic, physics-based simulated raw sensor data for an unlimited number of potential driving scenarios, traffic situations and other parameters. The data from PreScan's simulated LiDAR, radar and camera sensors is then fed into Mentor's DRS360 platform, where it is fused in real time to create a high-resolution model of the vehicle's environment and driving conditions. Customers can then leverage the DRS360 platform's superior perception resolution and high-performance processing to test and refine proprietary algorithms for critical tasks such as object recognition, driving policy and more. "Automakers are quickly realizing that physical prototypes and road testing alone cannot reproduce the multitude of complex driving scenarios self-driving cars will encounter.