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The Future of Software Engineering and Acquisition with Generative AI

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Content provided by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.

We stand at a pivotal moment in software engineering, with artificial intelligence (AI) playing a crucial role in driving approaches poised to enhance software acquisition, analysis, verification, and automation. While generative AI tools initially sparked excitement for their potential to reduce errors, scale changes effortlessly, and drive innovation, concerns have emerged. These concerns encompass security risks, unforeseen failures, and issues of trust. Empirical research on generative AI development assistants reveals that productivity and quality gains depend not only on the sophistication of tools but also on task flow redesign and expert judgment.

In this webcast, Software Engineering Institute (SEI) researchers will explore the future of software engineering and acquisition using generative AI technologies. They’ll examine current applications, envision future possibilities, identify research gaps, and discuss the critical skill sets that software engineers and stakeholders need to effectively and responsibly harness generative AI’s potential. Fostering a deeper understanding of AI’s role in software engineering and acquisition accentuates its potential and mitigates its risks.

What Attendees Will Learn

• how to identify suitable use cases when starting out with generative AI technology

• the practical applications of generative AI in software engineering and acquisition

• how developers and decision makers can harness generative AI technology

  continue reading

148 episoade

Artwork
iconDistribuie
 
Manage episode 397576331 series 1264075
Content provided by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.

We stand at a pivotal moment in software engineering, with artificial intelligence (AI) playing a crucial role in driving approaches poised to enhance software acquisition, analysis, verification, and automation. While generative AI tools initially sparked excitement for their potential to reduce errors, scale changes effortlessly, and drive innovation, concerns have emerged. These concerns encompass security risks, unforeseen failures, and issues of trust. Empirical research on generative AI development assistants reveals that productivity and quality gains depend not only on the sophistication of tools but also on task flow redesign and expert judgment.

In this webcast, Software Engineering Institute (SEI) researchers will explore the future of software engineering and acquisition using generative AI technologies. They’ll examine current applications, envision future possibilities, identify research gaps, and discuss the critical skill sets that software engineers and stakeholders need to effectively and responsibly harness generative AI’s potential. Fostering a deeper understanding of AI’s role in software engineering and acquisition accentuates its potential and mitigates its risks.

What Attendees Will Learn

• how to identify suitable use cases when starting out with generative AI technology

• the practical applications of generative AI in software engineering and acquisition

• how developers and decision makers can harness generative AI technology

  continue reading

148 episoade

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