According to Andrew Ng (@AndrewYNg), Redisinc experts @tchutch94 and @ilzhechev have launched a new course on semantic caching for AI agents. This course demonstrates how semantic caching technology can dramatically lower inference costs and reduce response latency for AI applications by recognizing and reusing semantically similar queries, such as refund requests phrased differently. The practical implications include greater scalability for AI-driven customer support, improved user experience, and significant operational cost savings for businesses deploying large language models (LLMs). Semantic caching is rapidly gaining traction as a critical optimization for enterprise AI workflows, especially in high-traffic environments (source: Andrew Ng on Twitter).