2025-12-04
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 rol [...]
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2025-10-16
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 [...]
2025-11-30
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 [...]
2025-10-08
New memory framework builds AI agents that can handle the real world's unpredictability
Researchers at the University of Illinois Urbana-Champaign and Google Cloud AI Research have developed a framework that enables large language model (LLM) agents to organize their experiences into a m [...]
2025-11-21
Google’s ‘Nested Learning’ paradigm could solve AI's memory and continual learning problem
Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after trai [...]
2025-10-16
ACE prevents context collapse with ‘evolving playbooks’ for self-improving AI agents
A new framework from Stanford University and SambaNova addresses a critical challenge in building robust AI agents: context engineering. Called Agentic Context Engineering (ACE), the framework automat [...]
2025-11-28
Anthropic says it solved the long-running AI agent problem with a new multi-session Claude SDK
Agent memory remains a problem that enterprises want to fix, as agents forget some instructions or conversations the longer they run. Anthropic believes it has solved this issue for its Claude Agent [...]
2025-10-12
We keep talking about AI agents, but do we ever know what they are?
Imagine you do two things on a Monday morning.First, you ask a chatbot to summarize your new emails. Next, you ask an AI tool to figure out why your top competitor grew so fast last quarter. The AI si [...]
2025-11-04
Attention ISN'T all you need?! New Qwen3 variant Brumby-14B-Base leverages Power Retention technique
When the transformer architecture was introduced in 2017 in the now seminal Google paper "Attention Is All You Need," it became an instant cornerstone of modern artificial intelligence. Ever [...]
2025-10-02
'Western Qwen': IBM wows with Granite 4 LLM launch and hybrid Mamba/Transformer architecture
IBM today announced the release of Granite 4.0, the newest generation of its homemade family of open source large language models (LLMs) designed to balance high performance with lower memory and cost [...]