scalability

SSOG-Attention introduces a novel attention mechanism using Sum of Separable Gaussians to achieve sub-quadratic complexity, outperforming or matching SDPA with faster convergence and improved efficiency.

In a 2005 Harvard lecture, a 21-year-old Mark Zuckerberg explains Facebook's competitive advantage over Google through smart people and nimbleness.

A tweet from @venkateshdotdev listing 10 challenging system design interview questions covering URL shorteners, scaling, consistency, rate limiting, fault tolerance, and handling traffic spikes.

AWS engineer Zak van der Merwe shares insights from his 14 years building control planes for EC2 and DSQL, discussing the distributed systems challenges of running infrastructure at massive scale.

A roundup covering new quantum dot qubit technologies from HRL Laboratories and a processor using diamond vacancies, highlighting progress in scalable quantum computing hardware.

The Model Context Protocol receives a major update, transforming it into a stateless protocol with improved scalability, governance, and security for enterprise AI integration.

This blog post debunks the myth that Postgres LISTEN/NOTIFY does not scale, showing how to optimize it for 60K writes per second with millisecond latency.

This paper proposes a constrained multi-source inference framework for accurate distribution system topology identification, using heterogeneous utility data and physical constraints. Tested on three feeders with over 8,000 AMI meters, it achieves over 95% reconstruction accuracy.

This article explains how Gnutella scaled its query traffic by evolving from flood routing to the Query Routing Protocol (QRP), which uses compact summaries to avoid flooding all peers.

The paper presents a scalable framework for multi-domain dialogue state tracking using BERT, achieving zero-shot generalization and improving performance on the SGD dataset.

This paper introduces drXAI, a method that uses XAI attribution to reduce data size for time series classification, achieving 80-90% data reduction while maintaining accuracy, enabling large models to scale.

Google discusses the challenges of monolithic prompts for AI agents and proposes a modular prompt transpilation approach using templates, includes, and build systems to improve maintainability and reliability.

CityBehavEx is a scalable LLM-assisted urban simulation platform that combines established human mobility models with fine-tuned cross-encoders to generate realistic, empirically validated mobility patterns for city-sized populations, demonstrating 100,000 agents over 75 days in under one hour on a single consumer GPU.

PRIME-RL is a framework for large-scale asynchronous reinforcement learning, designed to be hackable and scale to 1000+ GPUs with support for various models and environments.

Discusses the failure modes of shared state in large multi-agent systems with 50+ nodes, including race conditions, multi-node desync, and poisoned context, and asks for war stories from practitioners.

A guide to 40 backend concepts organized into six stages, from HTTP basics to system architecture, designed to help engineers prepare for system design interviews.

ClickHouse Managed Postgres scales PgBouncer to 4x throughput by running a fleet of processes with SO_REUSEPORT, enabling multi-core utilization and solving cancellation forwarding via peering.

Introduces AgenticAI-Supervisor, an API and UI-driven simulation environment for scalable reinforcement learning of LLM agents, using verifiable execution outcomes and reward shaping to mitigate reward hacking.

Aaron Levie argues that most valuable data resides inside organizations, not on the open web, and that effectively getting this data to AI agents will define competitive advantage in the future.

PgDog is a new Postgres connection pooler that preserves application code by handling SET statements and LISTEN/NOTIFY, unlike existing poolers that require trade-offs.