The widespread adoption of open-source and enterprise software has accelerated development velocity but also expanded the attack surface. Among the most pressing concerns is the unintentional exposure ...

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited AI expertise in industrial fields such as factories, medical, and ...

A project is trying to cut the cost of making machine learning applications for Nvidia hardware, by developing on an Apple Silicon Mac and exporting it to CUDA. Machine learning is costly to enter, in ...

Code generation AI -- AI systems that can write in different programming languages given a prompt -- promise to cut development costs while allowing coders to focus on creative, less repetitive tasks.

In my first semester of graduate school at Tufts University, I sat across from a young professor as he pitched me on joining his lab to work on genetic code expansion (GCE). Even though I'd just ...

A unified ML management system requires careful orchestration of multiple components, from experiment tracking with MLflow to model serving with FastAPI. Interactive ...

By allowing organizations to run these models locally on their own hardware, open-source AI prevents a dangerous data ...

Most ML projects fail to reach production. Five recurring pitfalls drive failures in ML projects: choosing the wrong problem, data quality/labeling issues, the model-to-product gap, offline-online ...