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NVIDIA says its supercomputer Pegasus will drive fully autonomous robotaxis

In what could truly make self-driving cars a reality, NVIDIA has designed world’s first AI computer codenamed “Pegasus” that is capable of handling Level 5 driving without requiring steering wheels, pedals, or mirrors. It will instead consist of sensors, cameras, radars and lidars to facilitate driving fully autonomous robotaxis. The advanced computing system NVIDIA Drive PX Pegasus is extending the capabilities of its predecessor NVIDIA Drive PX 2 by more than 10 times in terms of the processing power and performance. “Driverless cars will enable new ride- and car-sharing services. New types of cars will be invented, resembling offices, living rooms or hotel rooms on wheels. Travelers will simply order up the type of vehicle they want based on their destination and activities planned along the way. The future of society will be reshaped,” NVIDIA founder and CEO Jensen Huang said. There are hundreds of tech companies who are striving to bring autonomous self-driving cars on the road, and Pegasus will be marketed to them from the second half of 2018, the company said in its announcement. Shares of NVIDIA hit a record high following the news.

IBM in News

IBM advances analytics by integrating PowerAI and Data Science Experience

IBM is bringing their two key data science tools, Data Science Experience and IBM PowerAI, together. The company said in an announcement that the integration is intended to provide machine learning and deep learning on a single machine. The Data Science Experience gives users collaboration tools for managing and monitoring data models, according to Dinesh Nirmal, IBM’s vice president of analytics development. PowerAIi, meanwhile, brings in GPUs as well as deep learning libraries and algorithms that can be used on multiple frameworks, such as TensorFlow, he said. With this significant integration, users can create and train intelligence-led models using the deep learning frameworks to gain expanded data insights. Nirmal said that while 80% of enterprise problems can be solved with machine learning, there are specific use cases where deep learning is more effective. “If you’re running a huge neural network, that complexity requires deep learning. Or if you’re FedEx, to know what happened to a damaged box and how it got damaged, you would use deep learning. Anything that is data and process intensive,” he noted.

Others in Data Science News

Sage launches Sage Business Cloud to provide unified set of business solutions

Sage, the leading provider of cloud business management solutions, has unveiled Sage Business Cloud. The platform offers a powerful set of core products and add-on applications as a complete solution that meets unique business needs. The company claimed that Sage Business Cloud could be the “only cloud platform that businesses will ever need” and that it could also use the latest advancements in AI and machine learning to further help businesses improve productivity and efficiency. “Sage Business Cloud is the next transformative wave of business software. As the fourth industrial revolution continues to take hold, we want to make our customers lives simple. Businesses of all shapes and sizes need products that aid productivity, enable them to respond at lightning speed and deliver insights as well as opportunity,” Sage CEO Stephen Kelly said.

Puppet partners Google to offer customers cloud platform modules supporting migration and management

Puppet has entered into a collaboration with Google Cloud which could offer its customers Google Cloud Platform (GCP) services, including its advanced machine learning and data analytics capabilities. The partnership may also help slash their IT costs. Puppet is known for its automated approach to delivery and operations of the software, and now its customers can avail the Google Cloud’s flexibility and agility as well. According to the joint announcement, Google Cloud will also release the technology they used to generate modules so that the Puppet module ecosystem could move faster, keeping up with rapidly changing APIs in the cloud. “Our customers want choice, flexibility and the ability to manage everything they have, from their physical infrastructure to cloud resources for maximum operational efficiency and scale,” said Nigel Kersten, Chief Technical Strategist at Puppet, “With Google Cloud’s expertise in providing world class infrastructure and Puppet’s widely adopted enterprise management platform, we’re helping customers accelerate their move to the cloud.”

NICE accelerates machine learning capabilities in next evolution of cognitive process automation

NICE has announced the next evolution in its cognitive automation platform – an integration with technology partner Celaton to infuse NICE Robotic Automation with enhanced machine learning capabilities. This integration slashes manual effort by as much as 85% across some of the most complex business processes, and reduces process time by almost 95%. With cognitive machine learning capabilities, complex data is quickly consumed and interpreted, and sound judgments made by robots, who are instructed to respond to customer queries or complaints in an intelligent and highly personalized manner. “Robotic Process Automation has already made great strides globally by significantly impacting business efficiencies and ROI. We have now entered a new era of cognitive automation, and we are delighted to be at the forefront of innovation as we boldly expand our machine learning capabilities,” Miki Migdal, president of the NICE Enterprise Product Group said, “The integration with Celaton not only addresses many of the more complex and challenging business problems facing our customers today, but also marks a significant contribution to the cognitive automation arena.”


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