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AWS claims 90% vector cost savings with S3 Vectors GA, calls it 'complementary' - analysts split on what it means for vector databases
Vector databases emerged as a must-have technology foundation at the beginning of the modern gen AI era. What has changed over the last year, however, is that vectors, the numerical representations o [...]
From shiny object to sober reality: The vector database story, two years later
When I first wrote “Vector databases: Shiny object syndrome and the case of a missing unicorn” in March 2024, the industry was awash in hype. Vector databases were positioned as the next big thing [...]
Moving past speculation: How deterministic CPUs deliver predictable AI performance
For more than three decades, modern CPUs have relied on speculative execution to keep pipelines full. When it emerged in the 1990s, speculation was hailed as a breakthrough — just as pipelining and [...]
Agent context layers: Enterprises governing their AI data are catching twice as many bad answers as the ones who aren't
Across 101 enterprises, the context feeding AI agents is failing often and repeatedly. Sixty-eight percent have traced a confident but wrong agent answer to missing or inconsistent business context in [...]
The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix
Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context sourc [...]
Architectural patterns for graph-enhanced RAG: Moving beyond vector search in production
Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private data. The standard architecture — chunking documents, embedding them into [...]
This tree search framework hits 98.7% on documents where vector search fails
A new open-source framework called PageIndex solves one of the old problems of retrieval-augmented generation (RAG): handling very long documents.The classic RAG workflow (chunk documents, calculate e [...]
Oracle converges the AI data stack to give enterprise agents a single version of truth
Enterprise data teams moving agentic AI into production are hitting a consistent failure point at the data tier. Agents built across a vector store, a relational database, a graph store and a lakehous [...]