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 of data used by LLMs, have increasingly become just another data type in all manner of different databases. Now, Amazon Web Services (AWS) is taking the next leap forward in the ubiquity of vectors with the general availability of Amazon S3 Vectors. Amazon S3 is the AWS cloud object storage service widely used by organizations of all sizes to store any and all types of data. More often than not, S3 is also used as a foundational component for data lake and lakehouse deployments. Amazon S3 Vectors now adds native vector storage and similarity search capabilities directly to S3 object storage. I [...]
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 [...]
Amazon Web Services on Tuesday announced a new class of artificial intelligence systems called "frontier agents" that can work autonomously for hours or even days without human intervention, [...]
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 [...]
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 [...]
AI agents run on file systems using standard tools to navigate directories and read file paths. The challenge, however, is that there is a lot of enterprise data in object storage systems, notably Am [...]
The landscape of enterprise artificial intelligence shifted fundamentally today as OpenAI announced $110 billion in new funding from three of tech's largest firms: $30 billion from SoftBank, $30 [...]