Safeguarding AI agents and other conversational AI applications to ensure safe, on-brand and reliable behavior is essential for enterprises. NVIDIA NeMo Guardrails offers robust protection with AI guardrails for content safety, topic control, jailbreak detection, and more to evaluate and optimize guardrail performance. In this post, we explore techniques for measuring and optimizing your AI…
]]>AI agents present a significant opportunity for businesses to scale and elevate customer service and support interactions. By automating routine inquiries and enhancing response times, these agents improve efficiency and customer satisfaction, helping organizations stay competitive. However, alongside these benefits, AI agents come with risks. Large language models (LLMs) are vulnerable to…
]]>As enterprises adopt generative AI applications powered by large language models (LLMs), there is an increasing need to implement guardrails to ensure safety and compliance with principles of trustworthy AI. NVIDIA NeMo Guardrails provides programmable guardrails for ensuring trustworthiness, safety, security, and controlled dialog while protecting against common LLM vulnerabilities.
]]>An easily deployable reference architecture can help developers get to production faster with custom LLM use cases. LangChain Templates are a new way of creating, sharing, maintaining, downloading, and customizing LLM-based agents and chains. The process is straightforward. You create an application project with directories for chains, identify the template you want to work with…
]]>A retrieval-augmented generation (RAG) application has exponentially higher utility if it can work with a wide variety of data types—tables, graphs, charts, and diagrams—and not just text. This requires a framework that can understand and generate responses by coherently interpreting textual, visual, and other forms of information. In this post, we discuss the challenges of tackling multiple…
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