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Showing posts from September 28, 2016

Cybersecurity Framework for Government and Industry

In our increasingly disruptive digital-world where state-sponsored cyber attacks scale at a dangerous pace, the Internet Security Alliance (ISA) released Social Contract 3.0: Implementing a Market-Based Model for Cybersecurity at its 15th Anniversary Conference. 

I can recall that, written by experts from a variety of industries, the book seeks to provide a systemic framework for collaborative action on cybersecurity, integrating public policy and economics. 
The bookis intended to serve as a guide for policymakers from both sides of the aisle, proposing practical solutions to the very real cyber threats facing America. 
Recommendations to mitigate risks within the power utility sector include, among others, enhanced information sharing between utilities and the Federal Government, reforming the clearance attainment process for private sector executives, and encouraging public-private collaboration to manage the risks that can be posed by the introduction of third-party vendors.

Adoption of Internet of Robotic Things by e-commerce industry on the Internet of Robotic Things market

The momentum is exciting, and according to Research and Markets, the Internet of Robotic Things market is expected to be valued at USD 21.44 Billion by 2022, growing at a CAGR of 29.7% between 2016 and 2022.
Many findings converge on the fact that, the growth of this market is majorly driven by adoption of IoRT by e-commerce industry, increasing application areas owing to integration of robots with various technologies, short payback period and ROI.

The collaborative and smart robots in industrial sector

I have a great pleasure to recall that, the collaborative robots in industrial sector are used in manufacturing industries to speed up the production processes, increase productivity and efficiency, and minimize the costs involved in production in the long term. The smart robots are being adopted by the industrial sector to work along with the humans. Collaborative robots are used in the various industrial segments to help humans in the activities such as welding, painting, sorting, among others. 
It is expected that smart robots performing autonomous tasks would solve the problem of scarcity of labor among industries.

The impact of Artificial Intelligence (AI) technologies on business

Increasingly, there are lots of speculations and predictions on the real and potential impact of AI technologies on business.
From Machine Learning and Deep Learning, Natural language processing to Computer Vision, it is clear that, these Artificial Intelligence technologies are fundamentally changing the way work is done, the way people and machine interact with data and reinforcing the role of people to drive growth in business.
For many analysts, the impact of AI technologies on business is projected to boost labor productivity. AI can propel economic growth and potentially serve as a powerful remedy for stagnant productivity and labor shortages of recent decades. 
The Accenture Institute for High Performance, in collaboration with Frontier Economics, modeled the impact of AI for 12 developed economies that together generate more than 50 percent of the world’s economic output. AI was found to yield the highest economic benefits for the United States, increasing its annual growth rate …

Extended power and reach of the Splunk® Platform through Acalvio and Insight Engines

Splunk’s ability to ingest, process and analyze machine data at scale and human language to produce actionable intelligence from data is at the core of stakes.
Splunk Inc., has invested in two companies: Acalvio and Insight Engines with the goal to further drive innovation and extend the power and reach of the Splunk® Platform. I salute this momentum that can deeply help organizations detect, engage and respond to advanced attacks in a precise and timely manner.
For those who are unfamiliar,Acalvio is an innovator in advanced threat defense whose technology leverages and integrates with Splunk Enterprise and Splunk Enterprise Security (ES) to combat cyberthreats. Insight Engines empowers Splunk users to search and analyze data within Splunk solutions using natural language search to quickly draw actionable insights from machine data.

The IBM DataFirst Method in our data-driven world

It is obvious that, with the vast amount of data generated in real-time, many enterprises are struggling with how to continually increase the value they get from it. In fact, they need a clear roadmap that shows them how to progress in their use of data.
The DataFirst Method can help them derive the full benefits of these innovations. 
The IBM DataFirst Method is a methodology that enables organizations to assess the skills and roadmap needed to transform into a cognitive business that is driven by insight and gains the most value from data.

Cognitive capabilities, such as cognitive-based machine learning

It is increasingly exciting to see that, data-centric projects as Project DataWorks, among others are underpinned by core cognitive capabilities, such as cognitive-based machine learning. This helps speed up the process from data discovery to model deployment, and helps users uncover new insights that were previously hidden to them.

A game-changing with IBM Project DataWorks for you

I have a pleasure to recall that, Businesses today increasingly understand the competitive advantage of gaining insights from data. However, obtaining those insights can be increasingly complex.
In effect, most of this work is done by highly skilled data professionals, but who work in silos with disconnected tools and data services that may be difficult to manage, integrate, and govern. Also, because data is never static, businesses must continually iterate their data models and products, often manually to benefit from the most relevant, up-to-date insights.
Based on these realities, Project DataWorks aims to help businesses break down these barriers by connecting all data and insights for their users. All data-driven professionals can work together on an integrated, self-service platform, sharing common datasets and models in a trusted manner that helps ensure governance, while rapidly iterating data projects and products.

IBM DataWorks combines Machine Learning, Apache Spark, IBM Watson Analytics, and the IBM Data Science Experience

The streamlined combination featurescognitive capabilities; intelligent deployment of data productsonthe IBM Cloud; one environment for collaboration among data professionals and business users of all types, and involve all endpoints: enterprise databases, Internet of Things, streaming, weather, and social media. “Project DataWorks,” as a Watson initiative that is cloud-based data and analytics platforms that integrates all types of data and enable AI-powered decision-making. In effect, Project DataWorks is designed to make it simple for business leaders and data professionals to collect, organize, govern and secure data. 
Project DataWorks is available on Bluemix, IBM’s Cloud platform.

Archeio is combining Machine learning, cloud computing to service, Energy Industry and oilfield data

At the heart of stakes, we have machine learning, cloud computing, and smart search technologies to help energy companies access oilfield data more efficiently.
In effect, using next-generation technologies like machine learning and cloud computing, Archeio has developed a new way for oil & gas operators to intelligently search, manage, and analyze vast amounts of oilfield data.  I can observe that, Archeio’s new well file software-as-a-service (SaaS) offering applies intelligent algorithms to classify and structure this data.
The solution features map visualization and data analytics to display data in a variety of ways. It can also serves as a centralized hub for energy companies to securely share well information with partners, investors, and contractors.