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Blog Posts
Auditing Bias in Large Language Models
This post discusses recent research that uses a role-playing scenario to audit ChatGPT, an approach that opens new possibilities for revealing unwanted biases.
• By Katherine-Marie Robinson, Violet Turri
In Artificial Intelligence Engineering
![Katherine-Marie Robinson](/media/images/kmrobinson.max-180x180.format-webp.webp)
![Headshot of Violet Turri](/media/images/thumb_big_v-turri_blog_authors_.max-180x180.format-webp.webp)
Cost-Effective AI Infrastructure: 5 Lessons Learned
This post details challenges and state of the art of cost-effective AI infrastructure and five lessons learned for standing up an LLM.
• By William Nichols, Bryan Brown
In Artificial Intelligence Engineering
![Will Nichols](/media/images/nichols_will.max-180x180.format-webp.webp)
![Bryan Brown](/media/images/brown_bryan.max-180x180.format-webp.webp)
Applying Large Language Models to DoD Software Acquisition: An Initial Experiment
This SEI Blog post illustrates examples of using LLMs for software acquisition in the context of a document summarization experiment and codifies the lessons learned from this experiment and related …
• By Douglas Schmidt (Vanderbilt University), John E. Robert
In Artificial Intelligence Engineering
![Douglas C. Schmidt](/media/images/thumb_big_d-schmidt_blog_author.max-180x180.format-webp.webp)
![Headshot of John Robert](/media/images/thumb_big_j-robert_blog_authors.max-180x180.format-webp.webp)
OpenAI Collaboration Yields 14 Recommendations for Evaluating LLMs for Cybersecurity
This SEI Blog post summarizes 14 recommendations to help assessors accurately evaluate LLM cybersecurity capabilities.
• By Jeff Gennari, Shing-hon Lau, Samuel J. Perl
In Artificial Intelligence Engineering
![Jeffrey Gennari](/media/images/thumb_big_j-gennari_blog_author.max-180x180.format-webp.webp)
![Headshot of Shing-hon Lau.](/media/images/thumb_big_s-lau_blog_authors_56.max-180x180.format-webp.webp)
Using ChatGPT to Analyze Your Code? Not So Fast
This blog post explores the efficacy of ChatGPT 3.5 in identifying errors in software code.
• By Mark Sherman
In Artificial Intelligence Engineering
![Mark Sherman](/media/images/thumb_big_m-sherman_blog_author.max-180x180.format-webp.webp)
Creating a Large Language Model Application Using Gradio
This post explains how to build a large language model across three primary use cases: basic question-and-answer, question-and-answer over documents, and document summarization.
• By Tyler Brooks
In Artificial Intelligence Engineering
![Headshot of Tyler Brooks](/media/images/thumb_big_t-brooks_blog_authors.max-180x180.format-webp.webp)
Generative AI Q&A: Applications in Software Engineering
This post explores the transformative impacts of generative AI on software engineering as well as its practical implications and adaptability in mission-critical environments.
• By John E. Robert, Douglas Schmidt (Vanderbilt University)
In Artificial Intelligence Engineering
![Headshot of John Robert](/media/images/thumb_big_j-robert_blog_authors.max-180x180.format-webp.webp)
![Douglas C. Schmidt](/media/images/thumb_big_d-schmidt_blog_author.max-180x180.format-webp.webp)
Harnessing the Power of Large Language Models For Economic and Social Good: 4 Case Studies
This blog post, the second in a series, outlines four case studies, that explore the potential of large language models, such as ChatGPT, and explores their limitations and future uses.
• By Matthew Walsh, Dominic A. Ross, Clarence Worrell, Alejandro Gomez
In Artificial Intelligence Engineering
![Headshot of Matthew Walsh.](/media/images/mmwalsh.max-180x180.format-webp.webp)
![Dominic Ross](/media/images/thumb_big_d-ross_blog_authors_5.max-180x180.format-webp.webp)
Harnessing the Power of Large Language Models For Economic and Social Good: Foundations
This blog post explores the capabilities and limitations of large language models.
• By Matthew Walsh, Dominic A. Ross, Clarence Worrell, Alejandro Gomez
In Artificial Intelligence Engineering
![Headshot of Matthew Walsh.](/media/images/mmwalsh.max-180x180.format-webp.webp)
![Dominic Ross](/media/images/thumb_big_d-ross_blog_authors_5.max-180x180.format-webp.webp)
Contextualizing End-User Needs: How to Measure the Trustworthiness of an AI System
As potential applications of artificial intelligence (AI) continue to expand, the question remains: will users want the technology and trust it? This blog post explores how to measure the trustworthiness …
• By Carrie Gardner, Katherine-Marie Robinson, Carol J. Smith, Alexandrea Steiner
In Artificial Intelligence Engineering
![Headshot of Carrie Gardner](/media/images/1c4bf388-4197-47d4-9d0c-808db7c.max-180x180.format-webp.webp)
![Katherine-Marie Robinson](/media/images/kmrobinson.max-180x180.format-webp.webp)