August 5, 2021
“We’re pretty far from being out of this mess right now,” cautioned BioTeam CEO Ari Berman as he opened for the latest ASF Roundtable, Fighting COVID with Read more…
February 24, 2021
Last Thursday, a range of experts joined the Advanced Scale Forum (ASF) in a rapid-fire roundtable to discuss how advanced technologies have transformed the way humanity responded to the COVID-19 pandemic in indelible ways. The roundtable, held near the one-year mark of the first... Read more…
February 16, 2021
With the one-year mark of the pandemic in the U.S. rapidly approaching and vaccinations ramping up, decision-makers and stakeholders are beginning to look back Read more…
June 10, 2020
The rise of AI – machine and deep learning – in life sciences has stirred the same excitement and same ‘fits-and-starts’ reality as elsewhere. Today, AI is mostly used in two areas: 1) embedded in life science instruments such as cryo-electron microscopes where it assists in feature recognition and lies largely hidden from users, and... Read more…
May 11, 2020
Intel and the University of Pennsylvania today announced a collaboration involving 29 international medical centers to train models to recognize brain tumors. The project is part of the Informatics Technology for Cancer Research (ITCR) program of the National Cancer Institute (NCI) and will use ‘federated learning architecture’ to mine relevant data while maintaining... Read more…
July 29, 2019
The story of NIH’s supercomputer Biowulf is fascinating, important, and in many ways representative of the transformation of life sciences and biomedical res Read more…
February 25, 2019
Weary of the constant din of AI hype. So is Ari Berman, vice president and general manager of consulting services for BioTeam, a research computing consultancy specializing in life sciences. “Every vendor is selling AI. I think it has become the gluten-free tag of life sciences because it is everywhere.... Read more…
July 31, 2018
The National Institutes of Health, with the help of Google, last week launched STRIDES - Science and Technology Research Infrastructure for Discovery, Experimen Read more…
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.
Karlsruhe Institute of Technology (KIT) is an elite public research university located in Karlsruhe, Germany and is engaged in a broad range of disciplines in natural sciences, engineering, economics, humanities, and social sciences. For institutions like KIT, HPC has become indispensable to cutting-edge research in these areas.
KIT’s HoreKa supercomputer supports hundreds of research initiatives including a project aimed at predicting when the Earth’s ozone layer will be fully healed. With HoreKa, projects like these can process larger amounts of data enabling researchers to deepen their understanding of highly complex natural processes.
Read this case study to learn how KIT implemented their supercomputer powered by Lenovo ThinkSystem servers, featuring Lenovo Neptune™ liquid cooling technology, to attain higher performance while reducing power consumption.
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