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Building enterprise-scale RAG applications with Amazon S3 Vectors and DeepSeek R1 on Amazon SageMaker AI
ByRicardoOrganizations are adopting large language models (LLMs), such as DeepSeek R1, to transform business processes, enhance customer experiences, and drive innovation at unprecedented speed. However, standalone LLMs have key limitations such as hallucinations, outdated knowledge, and no access to proprietary data. Retrieval Augmented Generation (RAG) addresses these gaps by combining semantic search with generative AI,…
Generative AI in Healthcare: Innovations, Challenges, and the Role of High-Quality Data
ByRicardoHowever, generative AI models, despite their transformative potential, entail serious privacy and security risks due to the vast amounts of data involved and the opacity of their development. Moreover, there is widespread concern about models hallucinating—inventing false or misleading information when faced with insufficient data. These roadblocks are preventing the smooth implementation of generative AI…
Red Teaming for LLMs: Exposing Risks, Reinforcing Safety, and Building Trustworthy AI
ByRicardoWith their capacity to generate human-like content at a massive scale, LLMs are exposed to additional risks compared to traditional software systems. They can produce harmful responses, such as hallucinated content, various forms of toxic/ hate speech, copyrighted material, and personally identifiable information that is not meant to be shared. These kinds of failures can…
