How Do I Find ~ AI Resources

• Hassani, H., & Silva, E. S. (2023). The Role of ChatGPT in Data Science: How AI-Assisted Conversational Interfaces Are Revolutionizing the Field. Big Data and Cognitive Computing, 7(2), 62-. https://doi.org/10.3390/bdcc7020062
  This paper discusses how ChatGPT can assist data scientists in automating various aspects of their workflow, including data cleaning and preprocessing, model training, and result interpretation. It also highlights how ChatGPT has the potential to provide new insights and improve decision-making processes by analyzing unstructured data.

• Perry, C. (2023, December 19). Democratizing Access to AI-enabled coding with colab. Google. https://blog.google/technology/ai/democratizing-access-to-ai-enabled-coding-with-colab/

• Tu, X., Zou, J., Su, W. J., & Zhang, L. (2023). What Should Data Science Education Do with Large Language Models? https://doi.org/10.48550/arxiv.2307.02792

• Luccioni, S., Jernite, Y., & Strubell, E. (2024). Power hungry processing: Watts driving the cost of AI deployment?. In Proceedings of the 2024 ACM conference on fairness, accountability, and transparency (pp. 85-99). https://doi.org/10.1145/3630106.3658542 

• Zewe, A. (2025, January 17). Explained: Generative AI’s environmental impact. MIT News. https://news.mit.edu/2025/explained-generative-ai-environmental-impact-0117

• Zhuk, A. (2023). Artificial intelligence impact on the environment: Hidden ecological costs and ethical-legal issues. Journal of Digital Technologies and Law, 1(4), 932-954. https://doi.org/10.21202/jdtl.2023.40

• Ethical AI for Teaching and Learning - Center for Teaching Innovation. Cornell University

• Brandon, E., Eaton, L., Gavin, D., & Papini, A. (2023, December 12). Cross-campus approaches to building a generative AI policy. Educause Review. https://er.educause.edu/articles/2023/12/cross-campus-approaches-to-building-a-generative-ai-policy
   
• Hodges, C., & Ocak, C. (2023, August 3). Integrating generative AI into higher education: Considerations. Educause Review. https://er.educause.edu/articles/2023/8/integrating-generative-ai-into-higher-education-considerations

Readings

• Huerta, E. A., Khan, A., Davis, E., Bushell, C., Gropp, W. D., Katz, D. S., Kindratenko, V., Koric, S., Kramer, W. T. C., McGinty, B., McHenry, K., & Saxton, A. (2020). Convergence of artificial intelligence and high performance computing on NSF-supported cyberinfrastructure. Journal of Big Data, 7(1), 1–12. https://doi.org/10.1186/s40537-020-00361-2
  The authors present a summary of recent developments in this field, and describe specific advances they are spearheading to accelerate and streamline the use of HPC platforms to design and apply accelerated AI algorithms in academia and industry.

Software

• PyTorch
  A fully featured framework for building deep learning models.

• TensorFlow
  Open source platform for machine learning.

Tutorials and Learning Materials

• PyTorch documentation
• TensorFlow documentation

Websites to Explore

• AWS Marketplace
  Build AI and ML solutions faster with pre-trained machine learning models.

• GitHub
  Run or train open source LLMs locally.

• IEEE Transactions on Parallel and Distributed Systems (journal)

• Model Zoo
  Discover open source deep learning code and pretrained models.

• TOP500 The List
  The top 500 most powerful computer clusters.

• Brandon Pugh, S. W. (2023, July 12). What does ai need? A comprehensive federal data privacy and security law. https://iapp.org/news/a/what-does-ai-need-a-comprehensive-federal-data-privacy-and-security-law
   
• Busch, K. E. (2023). Generative Artificial Intelligence and Data Privacy: A Primer. Congressional Research Service. https://crsreports.congress.gov/product/pdf/R/R47569
   
• ChatGPT is a data privacy nightmare. If you’ve ever posted online, you ought to be concerned. (2024, April 3). http://theconversation.com/chatgpt-is-a-data-privacy-nightmare-if-youve-ever-posted-online-you-ought-to-be-concerned-199283