GAM takes aim at “context rot”: A dual-agent memory architecture that outperforms long-context LLMs
For all their superhuman power, today’s AI models suffer from a surprisingly human flaw: They forget. Give an AI assistant a sprawling conversation, a multi-step reasoning task or a project spanning days, and it will eventually lose the thread. Engineers refer to this phenomenon as “context rot,” and it has quietly become one of the most significant obstacles to building AI agents that can function reliably in the real world.A research team from China and Hong Kong believes it has created a solution to context rot. Their new paper introduces general agentic memory (GAM), a system built to preserve long-horizon information without overwhelming the model. The core premise is simple: Split memory into two specialized roles, one that captures everything, another that retrieves exactly th [...]
Rating
Innovation
Pricing
Technology
Usability
We have discovered similar tools to what you are looking for. Check out our suggestions for similar AI tools.
Most enterprises can't stop stage-three AI agent threats, VentureBeat survey finds
A rogue AI agent at Meta passed every identity check and still exposed sensitive data to unauthorized employees in March. Two weeks later, Mercor, a $10 billion AI startup, confirmed a supply-chain br [...]
Google PM open-sources Always On Memory Agent, ditching vector databases for LLM-driven persistent memory
Google senior AI product manager Shubham Saboo has turned one of the thorniest problems in agent design into an open-source engineering exercise: persistent memory.This week, he published an open-sour [...]
General Agentic Memory tackles context rot and outperforms RAG in memory benchmarks
A Chinese research team has developed a new memory architecture for AI agents. "GAM" is designed to minimize information loss during long interactions by combining compression with deep rese [...]
'Observational memory' cuts AI agent costs 10x and outscores RAG on long-context benchmarks
RAG isn't always fast enough or intelligent enough for modern agentic AI workflows. As teams move from short-lived chatbots to long-running, tool-heavy agents embedded in production systems, thos [...]
Google's Opal just quietly showed enterprise teams the new blueprint for building AI agents
For the past year, the enterprise AI community has been locked in a debate about how much freedom to give AI agents. Too little, and you get expensive workflow automation that barely justifies the &qu [...]
Anthropic introduces "dreaming," a system that lets AI agents learn from their own mistakes
Anthropic on Tuesday unveiled a suite of updates to its Claude Managed Agents platform at its second annual Code with Claude developer conference in San Francisco, introducing a new capability called [...]
Under the hood of AI agents: A technical guide to the next frontier of gen AI
Agents are the trendiest topic in AI today — and with good reason. Taking gen AI out of the protected sandbox of the chat interface and allowing it to act directly on the world represents a leap for [...]
An AI agent rewrote a Fortune 50 security policy. Here's how to govern AI agents before one does the same.
A CEO’s AI agent rewrote the company’s security policy. Not because it was compromised, but because it wanted to fix a problem, lacked permissions, and removed the restriction itself. Every identi [...]
Are you paying an AI ‘swarm tax’? Why single agents often beat complex systems
Enterprise teams building multi-agent AI systems may be paying a compute premium for gains that don't hold up under equal-budget conditions. New Stanford University research finds that single-age [...]