The rapid adoption of large language model (LLM) systems across the federal government has prompted the U.S. General Services Administration (GSA) ...

Data lakehouses offer a solid footing, but when agents access the data autonomously, enterprises need to consider security, ...

Prompt injection remains the most effective way to compromise enterprise AI systems because it exploits the fundamental way ...

NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — using step-by-step reasoning.

Google Cloud Summit came to London last week, and we took the opportunity to sit down with database execs Sailesh ...

Tom Fenton explains how local AI fits into the broader private AI discussion for VMware environments, distinguishing enterprise-scale private AI deployments from smaller local AI setups running on ...

Gemini for Home is the last thing I want to implement into my smart home ...

Jeongho Park, engineer at GraphAI and second author; Donghyoung Han, CTO of GraphAI and third author; Geonho Lee ...

With the advent of AI-mediated APIs, the era of manually hard-coding every integration between every microservice may be ...

Sales, a function that obviously runs on language, has been among the least changed by the technology built on language.

Tether successfully integrated Google’s TurboQuant into the inference engine of its local AI framework, QVAC. It is the ...

Token minimizing is the fastest way to lower LLM costs and latency. Learn practical techniques: prompt trimming, compaction, ...