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AI for Security vs Security for AI: From IBM Master Inventor to Microsoft AI Architect

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Innhold levert av By Harness. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av By Harness 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.

Dewan Ahmed sits down with Fatih Bulut, AI Architect at Microsoft and former IBM Research Master Inventor, to separate hype from reality in AI for software delivery and cybersecurity.

Fatih clarifies AI for security vs security for AI, walks through detection engineering as real software engineering, and explains proactive defense across an attack’s phases. He digs into the hard part of shipping: execution, product alignment, and tight feedback loops with customers. On code generation, he calls out failure modes like plausible but wrong outputs and hard coded shortcuts, and raises open questions about responsibility and auditability when AI writes code.

The pair map AI across the SDLC, from pipeline generation and troubleshooting to vulnerability triage, then explore transformer limits with huge telemetry and why verifiable tasks such as code and math are near term wins. Fatih remains bullish on AI where outputs are testable and where context usage actually works at scale.

Connect with Fatih on LinkedIn.

  continue reading

39 episoder

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Manage episode 505352254 series 2817626
Innhold levert av By Harness. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av By Harness 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.

Dewan Ahmed sits down with Fatih Bulut, AI Architect at Microsoft and former IBM Research Master Inventor, to separate hype from reality in AI for software delivery and cybersecurity.

Fatih clarifies AI for security vs security for AI, walks through detection engineering as real software engineering, and explains proactive defense across an attack’s phases. He digs into the hard part of shipping: execution, product alignment, and tight feedback loops with customers. On code generation, he calls out failure modes like plausible but wrong outputs and hard coded shortcuts, and raises open questions about responsibility and auditability when AI writes code.

The pair map AI across the SDLC, from pipeline generation and troubleshooting to vulnerability triage, then explore transformer limits with huge telemetry and why verifiable tasks such as code and math are near term wins. Fatih remains bullish on AI where outputs are testable and where context usage actually works at scale.

Connect with Fatih on LinkedIn.

  continue reading

39 episoder

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