Category: artificial intelligence

Exploring the Top 3 Vector Databases: Weaviate, Milvus, and Qdrant as Semantic Caches for LLM-Based Applications

In the dynamic landscape of artificial intelligence (AI) and natural language processing (NLP), the demand for efficient and high-performance vector databases has never been more crucial. These databases serve as the backbone for various applications, including language models (LLMs) that rely on semantic understanding. In this blog post, we delve into three leading vector databases […]

Unlock Efficiency: Slash Costs and Supercharge Performance with Semantic Caching for Your LLM App!

A semantic cache for large language model (LLM) based applications introduces a plethora of advantages that revolutionize their performance and usability.  Primarily, it significantly enhances processing speed and responsiveness by storing precomputed representations of frequently used language elements.  This minimizes the need for repetitive computations, leading to quicker response times and reduced latency, thereby optimizing […]

InqueryIQ – A fully-automatic OpenAI email support agent for your own products and services

Providing human support engineers to handle incoming queries about products and services can be both costly and limited in its scalability. This is particularly challenging for self-published mobile apps and small to medium-sized businesses, as they often lack the financial resources to offer human support. I personally experienced this issue when I published my own […]

Learn to Deploy Cloud Apps with Google Cloud Skill Boost

Last week I stumbled across a great opportunity that was announced within the Google Cloud Blog, which I am regularly scanning for latest GCP innovations. They offered a 30 days free subscription for their new Google Cloud Skill Boost learning platform, which I immediately accepted. Eager to deepen my existing knowledge on GCP cloud services, […]