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Showing posts from June 2, 2017

Non-volatile memories overcome the limitations of traditional non-volatile memory

For those who are unfamiliar, the emerging non-volatile memories overcome the limitations of traditional non-volatile memory in terms of scalability, endurance, and others. Also, the emerging non-volatile memories are widely being used in data center applications such as searching, mining, business analytics, digital media creation/transmission, and financial modeling to minimize downtime. According to Research and Markets, the non-volatile memory market is mostly driven by connected and wearable devices. Smartphones, digital cameras, gaming devices, and other consumer electronics devices also demand non-volatile memory in bulk. APAC is expected to be the fastest-growing market for non-volatile memory during the forecast period.

Non-Volatile Memory Market

The most exciting regarding the non-volatile memory market is to see that, the global perspectives are encouraging. According to Research and Markets, non-volatile memory market is projected to grow at a CAGR of 9.96% between 2016 and 2022. The drivers for this market are the need for high-speed, low-power consuming, and highly scalable memory devices and the growing demand for non-volatile memory in connected and wearable devices. The main restraint for this market is the low write endurance.

Businesses around the world are beginning to harness deep learning

Steadily, one can observe that, Businesses around the world are beginning to harness deep learning due to its ability to drive efficiencies in the form of speed, accuracy, agility, and access in several key areas. These areas include product development and improvement, process optimization and functional workflows, personalization and customer insight, sales optimization, and innovation and long-range strategy.

Top 10 use cases for deep learning

Tractica forecasts that deep learning software revenue will grow from $655 million in 2016 to $34.9 million worldwide by 2025. The firm anticipates that the top 10 use cases for deep learning, in terms of revenue, will be as follows: 1.Static image recognition, classification, and tagging 2.Machine/vehicular object detection/identification/avoidance 3.Patient data processing 4.Algorithmic trading strategy performance improvement 5.Converting paperwork into digital data 6.Medical image analysis 7.Localization and mapping 8.Sentiment analysis 9.Social media publishing and management 10.Intelligent recruitment and HR systems.

Deep Learning, as the most promising enabling technologies in the world of artificial intelligence (AI)

For those who are unfamiliar, Deep learning, a computing construct based on the architecture of the human brain, has emerged as one of the most promising enabling technologies in the world of artificial intelligence (AI). According to Tractica, although many of the concepts underlying artificial intelligence (AI) and technological biomimicry of human intelligence are over 50 years old, deep learning’s growth today is the result of a rather sudden convergence of three key trends: big, even colossal, data generation; advancements in hardware capabilities; and improvements in algorithms.

Here is what Data Loss Prevention refers to

For those who are unfamiliar, Data loss prevention (or DLP) refers to the strategy that ensures end-users do not exchange or send critical data outside their corporate stronghold. Term Data loss prevention (or DLP) is also used to illustrate software products that empowers network administrators to put a check on what sensitive data end-users can exchange or transfer. These software products apply business precept to categorize and safeguard confidential and sensitive data so that unaccredited end-users cannot share information as such revelation could put a company at risk.

Data protection in cloud and virtual models has created new opportunities for data loss prevention technology

The emergence of Data loss prevention (DLP) technology provides both information technology and security staff a complete 360 degree perspective of a specific location, circulation and utilization of information across the company.
Enterprises concerned about their next audit and intend to maintain data compliance with complicated regulation trust Data loss prevention (or DLP) technology. In effect, the technology is an interesting opportunities for those trying to safeguard their proprietary data against security breaches caused by enhanced staff mobility and advent of innovative channels. Success of sensitive data protection in cloud and virtual models has created new opportunities for data loss prevention technology.

World Entreprise Governance, Risk, and Compliance (eGRC) Market

The most exciting when it comes to World Enterprise Governance, Risk, and Compliance (eGRC) Market, is to recall that, there are several drivers, restraints and opportunities shaping the future of the market. Rising number of risks against critical data are likely to increase the rate of adoption of compliance solutions across different business verticals. This, in turn is anticipated to accelerate the expansion of enterprise governance worldwide. However, according to Research and Markets, lack of awareness about the benefits of enterprise governance, risks and compliance (also popular as eGRC) has hindered market growth. The firm also reveals that, Business verticals such as telecom and information technology would open new avenues of growth for the enterprise governance, risk and compliance market is years to come.