In this special guest feature, Rob Farber from TechEnablement writes that the Intel Scalable Systems Framework is pushing the boundaries of Machine Learning performance. “machine learning and other data-intensive HPC workloads cannot scale unless the storage filesystem can scale to meet the increased demands for data.”
[SPONSORED POST] Organizations can now confidently embrace Elastic, enhance their hot tier storage, and seamlessly manage historical data with cost-efficient capacity-optimized storage. Pure Storage not only meets the demands of the modern data landscape but also empowers organizations to simplify their Elastic architecture, reflecting the industry trend towards a more streamlined and efficient approach.
In today’s fast-paced world, driven by demands for speed and efficiency, the field of clinical development has undergone a remarkable transformation. The way trials are being conducted has changed significantly with decentralized clinical trials (DCT) becoming mainstream and the collection of clinical data from wearables and other remote-monitoring devices becoming common practice. While these advances […]
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