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Innhold levert av Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.
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The Future of Software Engineering and Acquisition with Generative AI

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Manage episode 397576331 series 1264075
Innhold levert av Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.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

174 episoder

Artwork
iconDel
 
Manage episode 397576331 series 1264075
Innhold levert av Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.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

174 episoder

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