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Episode Summary
Bob Remeika, CEO and Co-Founder of Ragie, joins host Danny Allan to demystify Retrieval-Augmented Generation (RAG) and its role in building secure, powerful AI applications. They explore the nuances of RAG, differentiating it from fine-tuning, and discuss how it handles diverse data types while mitigating performance challenges. The conversation also covers the rise of AI agents, security best practices like data segmentation, and the exciting future of AI in amplifying developer productivity.
Show Notes
In this episode of The Secure Developer, host Danny Allan is joined by Bob Remeika, co-founder and CEO of Ragie, a company focused on providing a RAG-as-a-Service platform for developers. The conversation dives deep into Retrieval-Augmented Generation (RAG) and its practical applications in the AI world.
Bob explains RAG as a method for providing context to large language models (LLMs) that they have not been trained on. This is particularly useful for things like a company's internal data, such as a parental leave policy, that would be unknown to a public model. The discussion differentiates RAG from fine-tuning an LLM, highlighting that RAG doesn't require a training step, making it a simple way to start building an AI application. The conversation also covers the challenges of working with RAG, including the variety of data formats (like text, audio, and video) that need to be processed and the potential for performance slowdowns with large datasets.
The episode also explores the most common use cases for RAG-based systems, such as building internal chatbots and creating AI-powered applications for users. Bob addresses critical security concerns, including how to manage authorization and prevent unauthorized access to data using techniques like data segmentation and metadata tagging. The discussion then moves to the concept of "agents," which Bob defines as multi-step, action-oriented AI systems. Bob and Danny discuss how a multi-step approach with agents can help mitigate hallucinations by building in verification steps. Finally, they touch on the future of AI, with Bob expressing excitement about the "super leverage" that AI provides to amplify developer productivity, allowing them to get 10x more done with a smaller team. Bob and Danny both agree that AI isn't going to replace developers, but rather make them more valuable by enabling them to be more productive.
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Episode Summary
Bob Remeika, CEO and Co-Founder of Ragie, joins host Danny Allan to demystify Retrieval-Augmented Generation (RAG) and its role in building secure, powerful AI applications. They explore the nuances of RAG, differentiating it from fine-tuning, and discuss how it handles diverse data types while mitigating performance challenges. The conversation also covers the rise of AI agents, security best practices like data segmentation, and the exciting future of AI in amplifying developer productivity.
Show Notes
In this episode of The Secure Developer, host Danny Allan is joined by Bob Remeika, co-founder and CEO of Ragie, a company focused on providing a RAG-as-a-Service platform for developers. The conversation dives deep into Retrieval-Augmented Generation (RAG) and its practical applications in the AI world.
Bob explains RAG as a method for providing context to large language models (LLMs) that they have not been trained on. This is particularly useful for things like a company's internal data, such as a parental leave policy, that would be unknown to a public model. The discussion differentiates RAG from fine-tuning an LLM, highlighting that RAG doesn't require a training step, making it a simple way to start building an AI application. The conversation also covers the challenges of working with RAG, including the variety of data formats (like text, audio, and video) that need to be processed and the potential for performance slowdowns with large datasets.
The episode also explores the most common use cases for RAG-based systems, such as building internal chatbots and creating AI-powered applications for users. Bob addresses critical security concerns, including how to manage authorization and prevent unauthorized access to data using techniques like data segmentation and metadata tagging. The discussion then moves to the concept of "agents," which Bob defines as multi-step, action-oriented AI systems. Bob and Danny discuss how a multi-step approach with agents can help mitigate hallucinations by building in verification steps. Finally, they touch on the future of AI, with Bob expressing excitement about the "super leverage" that AI provides to amplify developer productivity, allowing them to get 10x more done with a smaller team. Bob and Danny both agree that AI isn't going to replace developers, but rather make them more valuable by enabling them to be more productive.
Links
Follow Us
171 قسمت
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