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+[NIH Developer Seminar: PennyLane, GPUs, and QML,QiML](https://www.chemicalqdevice.com/nih-developer-seminar-pennylane-gpus-and-qiml) PDF + Discussion 11/30/23.
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+NIH's Office of Data Science Strategy Initiatives is catalyzing new opportunities in AI through the availability of FAIR and complete AI-ready data. With the goal of increasing widespread AI adoption, the nation's medical research agency aims to utilize important discoveries that improve health and save lives. NIH currently uses AI/ML in 27 of their institutes and centers, which includes the Office of the Director's 'Smart and Connected Health' initiative. (Slides 01, 02) 
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+NIH is also engaged in quantum information science research through the National Quantum Initiative to ensure researchers benefit from new technologies; and is also collaborating with the Department of Energy’s Advanced Scientific Computing Research Office to explore opportunities at the intersection of quantum computing, biomedical research, and data science. (Slide 19)
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+Adoption of advanced physics based machine learning approaches using classical data generating and classical data processing systems has recently become a greater priority to many leading organizations. (Slide 04) With a Python based notebook, a quantum machine learning library, and classical hardware - further benefiting from the effects of quantum algorithms for medical dataset analysis remains a key area of research. (Slide 05) 
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+With that being said, there are now many resources available to Healthcare developers for further QML/QiML implementation. (Slide 17) Next steps include increasing the number of Human-QiML Team interactions, additional testing for efficacy, and further implementing real world data in a community setting while forming prospective standards.