Results


Intel To Duke It Out With Nvidia In The Coprocessor Market

Forbes

In our previous analysis, we discussed how Intel is competing with Nvidia in the data center coprocessor market. These computational capabilities make GPUs ideally suited for use as coprocessors in High Performance Computing environments. It is worth noting that GPUs have a parallel architecture with hundreds of cores, making it highly suited for matrix and vector operations in both deep learning and 3D computer graphics. Currently, it is debatable as to which one – Intel's Xeon Phi processor family (formerly code-named Knightsbridge) or Nvidia's Tesla processors – is better in terms of performance.


Using Machine Learning Algorithms to Improve Your Business Workflows

#artificialintelligence

For example, when you apply machine learning algorithms to a sales workflow process, the technology is constantly learning from its mistakes and reprogramming itself to improve performance. The next generation of productivity software and machine learning might also include more intelligent document creation tools and processes. There's also the prospect of machine learning that complements traditional customer relationship management and collaboration platforms, helping users better capture and interact with customer data and internal content and saving them the time of searching for content across platforms. Applying machine learning to customer service enables organizations to offer a layer of proactive self-help tools that can provide customers with options to resolve their issues without having to call into the actual customer service department.


Context Levels in Data Science Solutioning in real-world

@machinelearnbot

Solution development: Using historical data, involves extensive experimentation, testing and validation; Solution deployment: Using the solution to get the insight and/or decision support; Solution assimilation: In the workflow enabling actions based on insight and/or prediction made by the solution; Solution maintenance and update: Periodic checking and validation of the solution performance and update to improve performance if required. Solution maintenance and update: Periodic checking and validation of the solution performance and update to improve performance if required. Solution maintenance and update: Periodic checking and validation of the solution performance and update to improve performance if required. An algorithm works with available data footprint of the process of interest; It discovers the relationships between the process characteristics and the outcomes; The above relationships are, more often than not, in form of complex patterns; Discovering these patterns require application of powerful learning algorithms on the historical data; Discovered patterns lead to learning the required model parameters; An analysis/model application algorithm use these parameters to create the model and apply it on the new data in order to compute the output.


How telecom providers are embracing cognitive app development

#artificialintelligence

As an example, mobile network operators are increasing their investment in big data analytics and machine learning technologies as they transform into digital application developers and cognitive service providers. With a long history of handling huge datasets, and with their path now led by the IT ecosystem, mobile operators will devote more than $50 billion to big data analytics and machine learning technologies through 2021, according to the latest global market study by ABI Research. Machine learning can deliver benefits across telecom provider operations with financially-oriented applications - including fraud mitigation and revenue assurance - which currently make the most compelling use cases. Predictive machine learning applications for network performance optimization and real-time management will introduce more automation and efficient resource utilization.


How telecom providers are embracing cognitive app development

#artificialintelligence

As an example, mobile network operators are increasing their investment in big data analytics and machine learning technologies as they transform into digital application developers and cognitive service providers. With a long history of handling huge datasets, and with their path now led by the IT ecosystem, mobile operators will devote more than $50 billion to big data analytics and machine learning technologies through 2021, according to the latest global market study by ABI Research. Machine learning can deliver benefits across telecom provider operations with financially-oriented applications - including fraud mitigation and revenue assurance - which currently make the most compelling use cases. Predictive machine learning applications for network performance optimization and real-time management will introduce more automation and efficient resource utilization.


GE Expands Predix Platform to Advance Industrial Internet Opportunities for Customers

#artificialintelligence

The Digital Hydro Plant complements GE's Digital Wind Farm, Digital Power Plant for Gas and Digital Power Plant for Steam, enhancing power generation reliability, efficiency, cybersecurity and profitability – targeted to reduce maintenance costs by up to 10%, increase plant availability by as much as 1% and boost revenues by up to 3%. ACQUISITIONS OF BIT STEW SYSTEMS, WISE.IO ACCELERATE DIGITAL INDUSTRIAL TRANSFORMATION GE Digital announced it has acquired Bit Stew Systems to bring its data intelligence capabilities to Predix and other industrial solutions. Wise.io's deep machine learning expertise – combined with GE Digital's existing data science talent and massive portfolio of industrial assets – will advance GE's Digital Twin capabilities and solidify its role as a leader in industrial machine learning. This news follow GE's recent acquisition of ServiceMax, a leader in cloud-based field service management solutions, which enables GE Digital customers to immediately gain more productivity from their assets and find greater efficiency in their field service processes.


NVIDIA Tesla P100 Available on Google Cloud Platform NVIDIA Blog

#artificialintelligence

NVIDIA Tesla P100 GPUs and Tesla K80 GPUs will be available on Google Cloud Platform, starting early next year. On Google Cloud Platform, Tesla P100 GPUs will be available to Google Compute Engine and Google Cloud Machine Learning users around the world. The Tesla K80 GPU accelerator delivers exceptional performance, with increased throughput that allows researchers to advance their scientific discoveries and developers to boost their web services. Learn more about NVIDIA GPU cloud computing and read Google's announcement.


NVIDIA Tesla P100 Available on Google Cloud Platform NVIDIA Blog

#artificialintelligence

NVIDIA Tesla P100 GPUs and Tesla K80 GPUs will be available on Google Cloud Platform, starting early next year. On Google Cloud Platform, Tesla P100 GPUs will be available to Google Compute Engine and Google Cloud Machine Learning users around the world. The Tesla K80 GPU accelerator delivers exceptional performance, with increased throughput that allows researchers to advance their scientific discoveries and developers to boost their web services. Learn more about NVIDIA GPU cloud computing and read Google's announcement.


Artificial intelligence and HR: partnering now for better business tomorrow

#artificialintelligence

AI-powered technologies such as predictive analytics solutions machine learning platforms, and advanced natural language generation applications are being applied to HR data to analyze and facilitate decision-making in a range of areas related to culture, team productivity, and personnel development. Advanced analytics enabled eBay's HR team to capture a comprehensive view of their culture and address areas for improvement. Advanced analytics enabled eBay's HR team to capture a comprehensive view of their culture and address areas for improvement. As available data related to employee behavior and communications grow, HR departments should think about how they can use emerging technologies to answer larger questions facing the organization, like "how do remote employees spend their time versus in-office employees?"


Artificial intelligence and HR: partnering now for better business tomorrow

#artificialintelligence

AI-powered technologies such as predictive analytics solutions machine learning platforms, and advanced natural language generation applications are being applied to HR data to analyze and facilitate decision-making in a range of areas related to culture, team productivity, and personnel development. Advanced analytics enabled eBay's HR team to capture a comprehensive view of their culture and address areas for improvement. Advanced analytics enabled eBay's HR team to capture a comprehensive view of their culture and address areas for improvement. As available data related to employee behavior and communications grow, HR departments should think about how they can use emerging technologies to answer larger questions facing the organization, like "how do remote employees spend their time versus in-office employees?"