Researchers push "Context Engineering 2.0" as the road to lifelong AI memory
Researchers are calling for a fundamental overhaul of how AI handles memory and context. Their proposal: a Semantic Operating System that can store, update, and forget information over decades, functioning more like human memory than today's short-lived context windows.<br /> The article Researchers push "Context Engineering 2.0" as the road to lifelong AI memory appeared first on THE DECODER. [...]
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A 0.12% parameter add-on gives AI agents the working memory RAG can't
AI agents forget. Every time a coding assistant loses track of a debugging thread, or a data analysis agent re-ingests the same context it already processed, the team pays in latency, token costs, and [...]
MeMo's memory model lets teams upgrade their LLM without retraining it — and performance jumps 26%
Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context window limits.MeMo, a [...]
DeepSeek’s conditional memory fixes silent LLM waste: GPU cycles lost to static lookups
When an enterprise LLM retrieves a product name, technical specification, or standard contract clause, it's using expensive GPU computation designed for complex reasoning — just to access stati [...]
98% of market researchers use AI daily, but 4 in 10 say it makes errors — revealing a major trust problem
Market researchers have embraced artificial intelligence at a staggering pace, with 98% of professionals now incorporating AI tools into their work and 72% using them daily or more frequently, accordi [...]
New KV cache compaction technique cuts LLM memory 50x without accuracy loss
Enterprise AI applications that handle large documents or long-horizon tasks face a severe memory bottleneck. As the context grows longer, so does the KV cache, the area where the model’s working me [...]
MIT's MeMo lets teams swap in a better LLM without retraining — and performance jumps 26%
Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context window limits.MeMo, a [...]
Tencent's Team Memory shares AI agent memory across a team — with no governance yet for when it's wrong
A VB Pulse survey this June found that 57% of enterprises had traced a confidently wrong agent answer back to missing or inconsistent context — the latest sign of how central context has become to w [...]
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 [...]
MemRL outperforms RAG on complex agent benchmarks without fine-tuning
A new technique developed by researchers at Shanghai Jiao Tong University and other institutions enables large language model agents to learn new skills without the need for expensive fine-tuning.The [...]