April 1, 2013
Increasingly, it’s a Big Data world we live in. Just in case you’ve been living under a rock and need proof of that, <a href="http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/" target="_blank">a major retailer can use an unimaginable number of data points to predict the pregnancy of a teenage girl outside Minneapolis before she gets a chance to tell her family</a>. That’s just one example, but there are countless others that point to the idea that mining huge data volumes can uncover gold nuggets of actionable proportions (although sometimes they freak people out...) Read more…
April 1, 2013
Increasingly, it’s a Big Data world we live in. Just in case you’ve been living under a rock and need proof of that, <a href="http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/" target="_blank">a major retailer can use an unimaginable number of data points to predict the pregnancy of a teenage girl outside Minneapolis before she gets a chance to tell her family</a>. That’s just one example, but there are countless others that point to the idea that mining huge data volumes can uncover gold nuggets of actionable proportions (although sometimes they freak people out...) Read more…
September 25, 2012
This week, not one but two groups of IT heavyweights launched with plans to expand the scope of the Internet while protecting the free flow of ideas it provides. The Internet Infrastructure Coalition (i2Coalition) counts already 42 founding members, including infrastructure providers Rackspace, Softlayer, ProfitBricks and Tucows, while the Internet Association's 14-strong roster claims Web giants Google, Yahoo, Facebook, eBay and Amazon. Read more…
September 13, 2012
IaaS provider ProfitBricks proclaims noteworthy performance-metrics, pits service against the top two cloud providers. Read more…
The increasing complexity of electric vehicles result in large and complex computational models for simulations that demand enormous compute resources. On-premises high-performance computing (HPC) clusters and computer-aided engineering (CAE) tools are commonly used but some limitations occur when the models are too big or when multiple iterations need to be done in a very short term, leading to a lack of available compute resources. In this hybrid approach, cloud computing offers a flexible and cost-effective alternative, allowing engineers to utilize the latest hardware and software on-demand. Ansys Gateway powered by AWS, a cloud-based simulation software platform, drives efficiencies in automotive engineering simulations. Complete Ansys simulation and CAE/CAD developments can be managed in the cloud with access to AWS’s latest hardware instances, providing significant runtime acceleration.
Two recent studies show how Ansys Gateway powered by AWS can balance run times and costs, making it a compelling solution for automotive development.
Five Recommendations to Optimize Data Pipelines
When building AI systems at scale, managing the flow of data can make or break a business. The various stages of the AI data pipeline pose unique challenges that can disrupt or misdirect the flow of data, ultimately impacting the effectiveness of AI storage and systems.
With so many applications and diverse requirements for data types, management systems, workloads, and compliance regulations, these challenges are only amplified. Without a clear, continuous flow of data throughout the AI data lifecycle, AI models can perform poorly or even dangerously.
To ensure your AI systems are optimized, follow these five essential steps to eliminate bottlenecks and maximize efficiency.
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