Microsoft Research has released Skala 1.1, an updated deep-learning exchange-correlation functional that offers greater accuracy, broader accessibility across the computational chemistry ecosystem, and a living benchmark for tracking computational performance.
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Microsoft Research releases Skala 1.1, claiming improvements in accuracy, computational chemistry ecosystem accessibility, and performance tracking, but specific details are yet to be disclosed.
On August 20, 2026, Microsoft Research announced the release of Skala 1.1 via its official X account, an updated version of its deep learning exchange-correlation functional. The official statement claims that this version 'offers higher accuracy, expands accessibility within the computational chemistry ecosystem, and provides a living benchmark to track computational performance.'
The announcement was made in a brief tweet with a link, but no specific technical details or performance data were included in the tweet.
The official statement explicitly mentions 'higher accuracy' and 'expanded accessibility' as the main improvements in Skala 1.1. Accuracy enhancement is a core goal for deep learning functionals, while accessibility expansion may imply support for more computational chemistry software or platforms.
However, the statement does not specify the magnitude of accuracy improvement or the exact scope of accessibility expansion, such as which software or hardware is supported.
Skala 1.1 introduces a 'living benchmark' to track computational performance. This concept may imply that the benchmark is continuously updated to reflect the latest hardware and software environments.
But the official announcement does not explain the specific form of the benchmark, its update frequency, or how to access it.
Currently, all information comes from Microsoft Research's official tweet, which is a source claim rather than confirmed fact. The tweet provides no quantitative data, such as percentage improvements in accuracy, benchmark results, or a list of supported software.
Therefore, the actual performance and degree of improvement of Skala 1.1 await the release of subsequent technical documentation or papers.
This report is based on Microsoft Research's official tweet; all information is source claims and has not been independently verified. The tweet provides no specific data, so the actual extent of accuracy improvement and accessibility expansion cannot be confirmed.
The release of Skala 1.1 marks Microsoft's continued investment in deep learning exchange-correlation functionals, but specific improvements are yet to be disclosed.
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