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Pattern Computer Comes Out of Stealth Mode and Launches Groundbreaking Pattern Discovery Technology

Pattern Computer, Inc., which has developed a proprietary pattern discovery system to uncover valuable insights from vast data sets, announced a pattern computer system and the public launch of its platform technology after being in stealth mode for the past two years. Pattern discovery is an emerging category – an extension of the machine learning field – that distinguishes itself by using both supervised and unsupervised learning.

Parallel Storage Fuels Groundbreaking Neuroscience and Behavioral Research at Harvard

To alleviate bottlenecks and achieve the ideal balance of parallel performance and optimized availability, Harvard University’s Faculty of Arts and Sciences Research Computing (FASRC) deployed the DataDirect Networks (DDN®) GRIDScaler® GS7KX® parallel file system appliance with 1PB of storage. The installation has sped the collection of images detailing synaptic connectivity in the brain’s cerebral cortex.

Deep Threat Analysis: Going Beyond the Obvious to Improve Border Security

In this special guest feature, John Kendall, Director of the Border and National Security Program for the global public sector practice at Unisys, discusses how border security experts around the world can improve their threat analysis with new AI and machine learning tools. A new approach, known as “deep threat analysis,” uses predictive analytics to examine the complex web of relationships and actions surrounding a traveler or shipment crossing a border.

DDN and Parabricks Announce Solution for GPU Acceleration of Genome Analysis

DDN Storage (DDN®) and Parabricks announced the availability of a jointly-integrated technology solution that provides massive acceleration for analysis of human genomes. The breakthrough platform combines GPU supercomputing performance with DDN’s Parallel Flash Data Platforms for fastest time to results, and enables unprecedented capabilities for high-throughput genomics analysis pipelines.

Interview: Ashutosh Garg, CEO at Eightfold.ai

I recently caught up with Ashutosh Garg, CEO at Eightfold.ai to discuss how he and his team have deployed AI and machine learning to help with the needs of the talent management industry. For example, the company uses Deep Learning to take the candidate data available inside the enterprise and combine it with publicly available data to create a current, rich and deep profile of candidates.

The Future of AI and Education

In this contributed article, freelance human Avery Phillips discusses the practical uses of AI in the education industry as well as an assessment of AI’s role in current and future educational activities. Education professionals are taking on the task to implement AI into operations, and finding it to be quite beneficial.

The Devil’s in the Data: Why Optimizing In-Store Marketing Spend is Critical to CPG and Retail Success

In this special guest feature, John Weller, Chief Knowledge Officer and Co-Founder of T-Pro Solutions, discusses how in-store marketers can optimize the data from their spreadsheets and use key analytics to stay ahead of industry trends.

Big Data’s Role in Taxation & Public Administration

In this contributed article, freelance human Avery Phillips discusses how the application of big data in taxation has eased the effort required for high levels of accuracy, and has increased the uses for tax information around the world. Big data in public administration has yet to play a significant role across the industry, however, its potential awaits untapped.

How Big Data and Behavior Prediction are Shaping Automotive Dealerships

In this special guest feature, Johannes Gnauck, CEO and Co-Founder of automotiveMastermind, discusses how big data and behavior prediction are shaping automotive dealerships. Through the use of big data and behavioral analytics, it’s possible to precisely target who is ready to buy and create personalized, micro-marketing campaigns designed to increase the probability of completing a sale.

The Doctor Is In: Consumers are More Comfortable with AI in Healthcare than Other Industries, Per a SAS Survey

While the buzz around artificial intelligence (AI) can seem ominous, consumers are surprisingly comfortable with the technology in healthcare. A recent survey conducted by SAS, a leader in analytics, found that when presented with a variety of real-world AI scenarios, a majority of people were at ease with AI in healthcare, and more comfortable with AI in healthcare settings than banking or retail. Despite consumer comfort with AI in the medical industry, the SAS survey of 500 Americans found that a lack of human interaction was the top reason respondents cited for feeling uncomfortable with the technology.