May 23, 2023
Jay Lofstead from Sandia National Laboratories and Jakob Luettgau from the University of Tennessee gave a highly audience interactive session on Ethics in AI an Read more…
May 18, 2023
2023 finds every major tech player working furiously to build out tools and infrastructure amid the massive surge in large-language models (LLMs). Long-time AI Read more…
May 9, 2023
Intel acquired AI chipmaker Habana Labs just four years ago; now, the division is serving – per Habana COO Eitan Medina – as “effectively the center of ex Read more…
May 2, 2023
Today, AMD reported its financial results for Q1 2023. The headline: revenues ($5.4 billion) are down by 9.2% year-over-year, just barely beating expectations a Read more…
April 22, 2023
Esperanto Technologies is working to accelerate software support for its novel, high-performance AI chips. The company has ported a large-language model (LLM) f Read more…
April 12, 2023
Generative AI is taking the tech world – and the broader world – by storm, but relatively little word has come out of the major supercomputer centers amid t Read more…
April 6, 2023
Financial firm Bloomberg is trying to prove that there are smarter ways to fine-tune artificial intelligence applications without the ethical or security concer Read more…
April 5, 2023
MLCommons today released the latest MLPerf Inferencing (v3.0) results for the datacenter and edge. While Nvidia continues to dominate the results – topping al 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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