5 stories tagged Scalability
Researchers introduce BatchDAG, a system where an LLM generates typed directed acyclic graphs (DAGs) of operations—SQL queries, semantic searches, and parallel fan-outs—to enable scalable, ad-hoc analysis over enterprise-scale datasets without context overflow or linear latency.
Researchers created GraphDC, an AI system that divides complex graph problems into smaller parts for easier solving. This could help with tasks like network analysis and logistics planning.
Researchers propose TTKV, a temporal-tiered KV cache that prioritizes recent memories in LLMs, improving efficiency for long-context inference. This method mimics human memory systems, offering a more scalable solution than existing approaches.
General Motors has unveiled Compound AI, a novel architecture designed to enhance the safety and scalability of autonomous systems. This development could reshape the future of AI-driven transportation.
Operating 14 AI agents for half a year revealed critical insights on scalability, cost, and reliability. The experience highlights the need for robust infrastructure and continuous monitoring.