semantic

In: Artificial Intelligence

As companies and individual users deal with constantly growing amounts of video content, the ability to perform low-effort search to retrieve videos or video segments using natural language becomes increasingly valuable. Semantic video search offers a powerful solution to this problem, so users can search for relevant video content basedContinue Reading

In: Artificial Intelligence

Customers today expect to find products quickly and efficiently through intuitive search functionality. A seamless search journey not only enhances the overall user experience, but also directly impacts key business metrics such as conversion rates, average order value, and customer loyalty. According to a McKinsey study, 78% of consumers areContinue Reading

In: Artificial Intelligence

Large language models (LLMs) excel at generating human-like text but face a critical challenge: hallucination—producing responses that sound convincing but are factually incorrect. While these models are trained on vast amounts of generic data, they often lack the organization-specific context and up-to-date information needed for accurate responses in business settings.Continue Reading

In: Artificial Intelligence

Amazon Kendra is an intelligent enterprise search service that helps you search across different content repositories with built-in connectors. AWS customers use Amazon Kendra with large language models (LLMs) to quickly create secure, generative AI–powered conversational experiences on top of your enterprise content. As enterprises adopt generative AI, many areContinue Reading

In: Artificial Intelligence

In the field of generative AI, latency and cost pose significant challenges. The commonly used large language models (LLMs) often process text sequentially, predicting one token at a time in an autoregressive manner. This approach can introduce delays, resulting in less-than-ideal user experiences. Additionally, the growing demand for AI-powered applicationsContinue Reading

In: Artificial Intelligence

With the rise of generative artificial intelligence (AI), an increasing number of organizations use digital assistants to have their end-users ask domain-specific questions, using Retrieval Augmented Generation (RAG) over their enterprise data sources. As organizations transition from proofs of concept to production workloads, they establish objectives to run and scaleContinue Reading