For customers who must run high-performance AI workloads cost-effectively at scale, neoclouds provide a truly purpose-built solution.
The new version of the in-memory database offers more than five times the throughput on ARM systems and extended features for streams and time-series.
In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...
Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...
The Stellar P3E is the first automotive microcontroller to ship with ST’s Neural-ART Accelerator. It offers a 20x to 30x improvement in inference operations compared to a similar MCU without a ...
Sahil Dua discusses the critical role of embedding models in powering search and RAG applications at scale. He explains the ...
The financial cost of running LLMs is astonishing. In response, the industry has rushed toward FinOps for AI, the practice of meticulously tracking and optimizing every dollar spent on computation.
Large language models (LLMs) can suggest hypotheses, write code and draft papers, and AI agents are automating parts of the research process. Although this can accelerate science, it also makes it ...
Catalysis is key to address today’s most pressing environmental and public health challenges; from pollutant degradation and clean water generation to ...
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