SE Radio 647: Praveen Gujar on Gen AI for Digital Ad Tech Platforms

Praveen Gujar, Director of Product at LinkedIn, joins SE Radio host Kanchan Shringi for a discussion on how generative AI (GenAI) is transforming digital advertising technology platforms. The conversation starts with a look at how GenAI facilitates scalable ad content creation, using self-attention mechanisms for customized ad generation. They explore AI's role in simplifying campaign management, automating tasks such as audience targeting and performance measurement. Praveen emphasizes that ad tech platforms use AI models tailored to different needs leveraging both first-party and third-party data sources, with privacy maintained through methods such as CAPI (conversion API). They also consider the differences between retrieval-augmented generation (RAG) and fine-tuning in AI models: Whereas RAG uses brand-specific data at runtime for precise ad content, fine-tuning focuses on broader model optimization. The segment highlights the importance of vector embeddings and vector search in storing and retrieving contextual content. Lastly, Praveen discusses the integration of AI teams within product development to improve collaboration and AI proficiency across organizations. Brought to you by IEEE Computer Society and IEEE Software magazine.

Praveen Gujar, Director of Product at LinkedIn, joins SE Radio host Kanchan Shringi for a discussion on how generative AI (GenAI) is transforming digital advertising technology platforms. The conversation starts with a look at how GenAI facilitates scalable ad content creation, using self-attention mechanisms for customized ad generation. They explore AI’s role in simplifying campaign management, automating tasks such as audience targeting and performance measurement. Praveen emphasizes that ad tech platforms use AI models tailored to different needs leveraging both first-party and third-party data sources, with privacy maintained through methods such as CAPI (conversion API). They also consider the differences between retrieval-augmented generation (RAG) and fine-tuning in AI models: Whereas RAG uses brand-specific data at runtime for precise ad content, fine-tuning focuses on broader model optimization. The segment highlights the importance of vector embeddings and vector search in storing and retrieving contextual content. Lastly, Praveen discusses the integration of AI teams within product development to improve collaboration and AI proficiency across organizations.

Brought to you by IEEE Computer Society and IEEE Software magazine.

Show Notes

Related Episodes

• SE Radio 493: Ram Sriharsha on Vectors in Machine Learning

• SE Radio 610: Phillip Carter on Observability for Large Language Models

• SE Radio 594: Sean Moriarity on Deep Learning with Elixir and Axon

Other References

• Forbes – Elevating Conversational Marketing with Artificial Intelligence

• Forbes – How Marketers Can Improve Short-form Video Ads in the Age of GenAI

• IEEE Article – “Evolving Product Engineering Teams in the AI Era” by Sriram Panyam, Praveen Gujar, and Gunjan Paliwal

• IEEE Article – “AI Integrated Product Development: Building Sustainable Competitive Advantage” by Praveen Gujar, Sriram Panyam, and Gunjan Paliwal

• Microsoft Azure Blog – Introducing Phi-3: Redefining what’s possible with SLMs

• Attention in Transformers

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