Artificial intelligence is rapidly transforming how researchers approach complex global challenges, especially in healthcare and biological sciences. As innovation accelerates, institutions are increasingly leveraging AI to drive discoveries that can improve human health and societal well-being. As one example, Virginia Tech has announced Debswapna Bhattacharya has received a five-year, $2.1 million award from the National Institutes of Health. This funding will support the development of advanced AI methods to map proteins and RNA structures in three dimensions—an effort that can accelerate disease understanding and treatment discovery. Where this gets especially innovative is the use of AI to analyze complex biological data at scale, enabling researchers to uncover patterns and insights that would be difficult or impossible to detect through traditional methods. By improving how scientists visualize molecular structures, these tools can significantly speed up breakthroughs in medicine and biotechnology. Here is how this can help: Enable faster discovery of disease mechanisms and potential treatments. Enhance collaboration between computer science and life sciences. Support the development of scalable, AI-driven research tools for public good. Looking to the future, we are going to see continued growth in AI-driven research across healthcare, environmental science, and beyond. Initiatives aligned with “AI for good” are expected to play a critical role in solving global challenges—ranging from improving patient outcomes to advancing sustainable development. As these technologies evolve, ongoing investment and interdisciplinary collaboration will be essential to fully realize their…

Is privacy in the age of AI (artificial intelligence) a lost cause? One new research program aims to create greater privacy, aka privacy by design, where the AI platform never sees a face on an image, but the final edited image still looks natural. The research is being done at Purdue University, where a new patent-pending system leverages before and after photos uploaded to an AI editing platform. It allows users to mask sensitive regions of a photo, such as the face. The technology can then reintegrate the sensitive region back into the image. Here is how this can help: Full privacy, as sensitive data never leaves the user’s device. High-quality edits and photorealism. Compatibility with commercial generative AI models. Research shows the system reduced the ability of AI models to detect attributes such as eye color, facial hair, and age group. In some cases, attribute-classification accuracy dropped by more than 80%, demonstrating strong protection against identity leakage. Looking to the future, the team is taking steps to bring the patent-pending technology to the real world. Researchers hope to expand the system to protect additional sensitive features such as medical details, ID documents, and other privacy-critical…