A research team has developed a cutting-edge deep learning framework, TM-WSNet, that dramatically improves the accuracy of rubber tree identification and measurement in dense plantation environments.

Learn how to fine-tune AI models for your unique needs with this easy-to-follow guide. Simplify AI customization and achieve ...

Meta shifts focus to advanced AI with its Super Intelligence Lab, raising questions about the future of FAIR and open AI ...

The open source AI ecosystem took a decisive leap forward today as the PyTorch Foundation announced that Ray, the distributed computing framework originally developed by Anyscale, has officially ...

Ray joins leading open source AI projects including PyTorch and vLLM to minimize AI computing complexity and speed production SAN FRANCISCO, Oct. 22, 2025 ...

Abstract: Training deep learning models is computationally demanding and data-intensive. Existing approaches utilize local SSDs within training servers to cache datasets, thereby accelerating data ...

We will build a Regression Language Model (RLM), a model that predicts continuous numerical values directly from text sequences in this coding implementation. Instead of classifying or generating text ...

The stock market snapped its three-day skid after the Federal Reserve’s preferred inflation gauge met expectations. The Dow Jones Industrial Average rose 300 points, or 0.7%. The S&P 500 gained 0.6%.

FTX’s bankruptcy estate is set to release $1.6 billion of funds to creditors at the end of the month, marking the third major payout following the crypto exchange's implosion nearly three years ago.

As artificial intelligence proliferates across healthcare, with AI now used for clinical and financial imperatives from disease diagnosis to cost and capacity predictions, there's big potential for ...

SCDL seems to me to have two parts: a format for efficient access to row-wise data, and a PyTorch Dataset derivative. The former has many uses beyond PyTorch and the project I work on explicitly tries ...