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Showing posts from September 27, 2017

IBM New High-Powered Analytics System for Fast Access to Data Science

At the core of stakes, we have IBM Data Science Experience, Apache Spark embedded to give users high-performance data science across public, private or hybrid clouds. In effect, the Integrated Analytics System, a new unified data system is designed to give users fast, easy access to advanced data science capabilities and the ability to work with their data across private, public or hybrid cloud environments.  One can also observe that, the system, which comes with a variety of data science tools built-in, allows data scientists to get up and running quickly to develop and deploy their advanced analytics models in-place, directly where the data resides for greater performance.

Hybrid transactional analytical processing (HTAP) in our ever-connected data-driven world

For those who are unfamiliar, in contrast to typical business environments where transaction processing and analytics are run on distinct architectures, Hybrid transactional analytical processing (HTAP) runs predictive analytics, transactional and historical data on the same database at accelerated response times.

The IBM Data Science Experience

For those who are unfamiliar, the IBM Data Science Experienceprovides a set of critical data science tools and a collaborative work space through which data scientists can create new analytic models that developers can use to build intelligent applications quickly and easily. One can observe that, the inclusion of Apache Spark, the popular open source framework, enables in-memory data processing, which speeds analytic applications by allowing analytics to be processed directly where the data resides.

The factors contributing to the growth of global social gaming market

Steadily, one can observe that, for many analysts, the factors contributing to the growth of global social gaming market is advances in gaming consoles such as Playstation and Xboxes. The free or low cost of games is also at the core of stakes.
According to Research and Markets, the Global Social Gaming market was USD 7.97 billion in 2016 and is estimated to reach USD 19.1 billion by 2022 at a CAGR of 15.67% for the forecasted period.

Help computers self-organize and make decisions based on patterns and associations

According to Intel, the Loihi research test chip includes digital circuits that mimic the brain’s basic mechanics, making machine learning faster and more efficient while requiring lower compute power. One can observe that, Neuromorphic chip models draw inspiration from how neurons communicate and learn, using spikes and plastic synapses that can be modulated based on timing. For certain analysts, this could help computers self-organize and make decisions based on patterns and associations.

Use cases, type of logic, and potential benefits from self-learning chips

For many analysts, the potential benefits from self-learning chips are limitless. Dr. Michael Mayberry recalls that, self-learning chip provides a person’s heartbeat reading under various conditions; after jogging, following a meal or before going to bed; to a neuromorphic-based system that parses the data to determine a “normal” heartbeat. The system can then continuously monitor incoming heart data in order to flag patterns that do not match the “normal” pattern. One can also observe that, the system could be personalized for any user. This type of logic could also be applied to other use cases, like cybersecurity where an abnormality or difference in data streams could identify a breach or a hack since the system has learned the “normal” under various contexts.

Intel has developed a first-of-its-kind self-learning neuromorphic chip; codenamed Loihi

At the core of stakes, we have a novel approach to computing via asynchronous spiking, and the ability to mimic how the brain functions. In effect, Intel has developed a first-of-its-kind self-learning neuromorphic chip: codenamed Loihi that mimics how the brain functions by learning to operate based on various modes of feedback from the environment. It is billed as an energy-efficient chip, which uses the data to learn and make inferences, gets smarter over time and does not need to be trained in the traditional way.

A future with Intel’s New Self-Learning Chip

Imagine a future where, complex decisions could be made faster and adapt over time. Where societal and industrial problems can be autonomously solved using learned experiences. It’s a future where first responders using image-recognition applications can analyze streetlight camera images and quickly solve missing or abducted person reports. It’s a future where stoplights automatically adjust their timing to sync with the flow of traffic, reducing gridlock and optimizing starts and stops. It’s a future where robots are more autonomous and performance efficiency is dramatically increased. By Dr. Michael Mayberry.

Recent advanced investments and R&D in artificial intelligence (AI) and neuromorphic computing

Very exciting to observe that, an increasing need for collection, analysis and decision-making from highly dynamic and unstructured natural data is driving demand for compute that may outpace both classic CPU and GPU architectures. 
To keep pace with the evolution of technology and to drive computing beyond PCs and servers, Intel on the past six years paves its way on specialized architectures that can accelerate classic compute platforms.  The company has also recently advanced investments and R&D in artificial intelligence (AI) and neuromorphic computing.

The major factors that are augmenting the growth of the global Digital forensics market

For many analysts, the major factors that are augmenting the growth of the global Digital forensics market are increasing cyber-attacks and crimes and increasing demand of IOT devices. Increasing demand of cloud computing forensic and data security along with the regulatory enforcement and compliance are estimated to be one of the major factors that are augmenting the growth of the market. According to Research and Markets, advancement in forensic tools and rise in the incidences of the insider attacks are developing numerous expansion opportunities for the growth of the digital forensics market.

Digital forensics at stake with

Lack of skilled professionals, high level of encryption in mobile applications and limitations of the cloud forensics are at the core of stakes. In effect, steadily, one can observe that, Lack of skilled professionals, high level of encryption in mobile applications and limitations of the cloud forensics are the major constraints in the growth of the global Digital forensics market.