Abstract: Despite the remarkable success of end-to-end intelligent diagnosis methods, the shortage of available training data remains one of the most challenging issues in real industrial scenarios.

The company said on Tuesday that it was holding back on releasing the new technology but was working with 40 companies to explore how it could prevent cyberattacks. By Kevin Roose Reporting from San ...

Abstract: This article introduces a novel approach that combines a multimodel technique with model-free adaptive control (MFAC) to address the limitations of the full-form dynamic linearization (FFDL) ...

Washington-based Starcloud launched a satellite with an Nvidia H100 graphics processing unit in early November, sending a chip into outer space that's 100 times more powerful than any GPU compute that ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

This isn't really an issue (discussions are disabled) and it isn't exactly related to the Device model group, but since you, the Smart Data Model maintainers, have a lot of experience with JSON-LD and ...

Singapore-based AI startup Sapient Intelligence has developed a new AI architecture that can match, and in some cases vastly outperform, large language models (LLMs) on complex reasoning tasks, all ...

Personally identifiable information has been found in DataComp CommonPool, one of the largest open-source data sets used to train image generation models. Millions of images of passports, credit cards ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...