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Showing posts from November 16, 2016

Digital Forensics in our ever-connected era

The stakes remain the same around PC forensics, arrange forensics, cloud forensics, cell phone forensics, database forensics and others, with PC forensics holding the biggest share
According to Research and Markets, the key elements helping the development of PC forensics incorporate expanded hierarchical spending in their data innovation spending plans for PC and system security
One can also observe that, the market is commanded by a few players, contingent upon their significant skills. The key players in this market are FireEye, Inc., Cellebrite Mobile Synchronization Ltd, Guidance Software Inc, Oxygen Forensic, AccessData Group LLC, LogRhythm Inc and Nuix Pty Ltd.

IBM PowerAI, a new deep learning software toolkit available

It is very exciting to scrutinize collaboration on a new deep learning tool optimized for the latest IBM and NVIDIA technologies to help train computers to think and learn in more human-like ways at a faster pace.
I effect, IBM PowerAI is designed to run on IBM’s highest performing server in its OpenPOWER LC lineup, the IBM Power S822LC for High Performance Computing (HPC), which features NVIDIA NVLink technology optimized for the Power architecture and NVIDIA’s latest GPU technology. 
I can also observe that, the new solution supports emerging computing methods of artificial intelligence, particularly deep learning.

Caffe as the most popular deep learning community applications

I can recall that, Caffeis a widely-used deep learning framework developed by Berkeley Vision and Learning Center (BVLC) and is recognized within the technology industry as one of the most popular deep learning community applications. Caffe is one of five deep learning software frameworks available in the IBM PowerAI toolkit.

The toolkit leverages NVIDIA GPUDL libraries including cuDNN, cuBLAS and NCCL as part of NVIDIA SDKs to deliver multi-GPU acceleration on IBM servers.

Deep learning as a fast growing machine learning method in our digital ever-connected world

I have a pleasure to recall that, Deep learning is defined a fast growing machine learning method that extracts information by crunching through millions of pieces of data to detect and rank the most important aspects from the data. Publicly supported among leading consumer web and mobile application companies, deep learning is quickly being adopted by more traditional business enterprises. 
Deep learning and other artificial intelligence capabilities are being used across a wide range of industry sectors; in banking to advance fraud detection through facial recognition; in automotive for self-driving automobiles and in retail for fully automated call centers with computers that can better understand speech and answer questions.

High Performance Computing (HPC) to mainstream enterprises

The requirements of our ever-connected data-driven era are huge for data-driven companies that need to deal with vast among of data from multiple sources in real-time.
One can then observe that, the global HPC market forecast exceeds $30 billion in 2016 for all products and services spending, including servers, software, storage, cloud, and other categories, with continued growth expected at 5.2 percent CAGR through 2020.
EMC and Dell aim to hold the number-one position in total HPC revenue share heading into 2017 with interesting capabilities easily accessible and deployable for organizations and businesses of all sizes.

The Availability of Hortonworks Data Cloud for Amazon Web Services

The ability to harness the agility and elasticity of Apache® Hadoop™ and Apache® Spark™ in the cloud for powering new workloads and analytic applications is at the core of stakes.
In effect,the Availability of HortonworksData Cloud for Amazon Web Services can deliver the enterprise-grade capabilities of Hortonworks Data Platform (HDP®) with both hourly and annual billing options available on the AWS Marketplace. 
I can also observe that, Hortonworks Data Cloud for AWS is specifically optimized to run well on AWS for enterprise ephemeral workloads and is designed to integrate with AWS services such as Amazon Simple Storage Service (S3), Amazon RDS and Amazon Elastic Compute Cloud (EC2).