The AI memory crisis just hit DDR2, a standard from 2003, with 60% price hikes
The AI-driven memory shortage has now reached the oldest DRAM standard still in production. DDR2 contract prices rose 55 to 60 percent in the second quarter of 2026, according to Taiwanese market intelligence firm TrendForce, with a further 35 to 40 percent increase forecast for the third quarter. The price surge is being driven by […]<br /> This story continues at The Next Web [...]
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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 [...]
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 [...]
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 [...]
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 [...]
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 [...]
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 [...]
'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 [...]