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Securing AI: Addressing the Emerging Threat of Prompt Injection

Subscribe • Previous Issues Mitigating Prompt Injection Risks to Secure Generative AI Apps I’m optimistic about the potential for generative AI, particularly its benefits for companies and knowledge workers. However, in the rapidly evolving landscape of AI, understanding and addressing vulnerabilities like prompt injection is crucial for the safe integration of these technologies into our digital ecosystem.   As LLMs find their way…

Generative AI 2023: Why This Year Marks a Major Turning Point

Subscribe • Previous Issues The Promise and Progress of Generative AI One year after ChatGPT’s launch, generative AI is gaining mainstream traction. Large language models (LLMs) like GPT-4 are being adopted across diverse real-world applications, from chatbots to computer programming to medicine and law. The speed of adoption has been remarkable – shortly after the release of GPT-4, chatbots leveraging its capabilities…

Charting the Graphical Roadmap to Smarter AI

Subscribe • Previous Issues Boosting LLMs with External Knowledge: The Case for Knowledge Graphs When we wrote our post on Graph Intelligence in early 2022, our goal was to highlight techniques for deriving insights about relationships and connections from structured data using graph analytics and machine learning. We focused mainly on business intelligence and machine learning applications, showcasing how technology companies were…

Best Practices in Retrieval Augmented Generation

Subscribe • Previous Issues Techniques, Challenges, and Future of Augmented Language Models After attending several conferences in the past month, it’s evident that Retrieval Augmented Generation (RAG) has emerged as one of the most popular techniques in AI over the past year, widely adopted by many AI teams. RAG refers to the process of supplementing a large language model (LLM) with additional…


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