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Blog Posts
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)
The Challenge of Adversarial Machine Learning
This SEI Blog post examines how machine learning systems can be subverted through adversarial machine learning, the motivations of adversaries, and what researchers are doing to mitigate their attacks.
• By Matt Churilla, Nathan M. VanHoudnos, Robert W. Beveridge
In Artificial Intelligence Engineering
![Headshot of Matt Churilla](/media/images/thumb_big_m-churilla_blog_autho.max-180x180.format-webp.webp)
![Headshot of Nathan Van Houdnos](/media/images/thumb_big_n-vanhoudnos_blog_aut.max-180x180.format-webp.webp)