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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 [...]
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 [...]
Joint studies from OpenAI and MIT found links between loneliness and ChatGPT use
New studies from OpenAI and MIT Media Lab found that, generally, the more time users spend talking to ChatGPT, the lonelier they feel. The connection was made as part of two, yet-to-be-peer-reviewed s [...]
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 [...]
'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 [...]