35 stories tagged Memory
Cognikernel is a new open-source tool that gives AI coding assistants like Claude Code and Codex persistent local memory. It automatically captures architectural decisions and project context during coding sessions, eliminating the need for manual markdown files.
India's smartphone market is shrinking as the AI boom drives up demand for memory chips, raising prices and forcing Apple, Samsung, and others to rethink their strategies. Consumers may soon see fewer high-end features in affordable phones.
Researchers have developed a new system called Oracle Agent Memory to help AI assistants remember important details over long conversations. This could make AI tools more reliable for tasks that span multiple sessions, like complex projects or ongoing customer support.
A new paper explores integrating memory into every step of an AI agent's reasoning loop, but warns this approach could inflate latency by up to 83x. The work highlights a tension between memory-rich reasoning and real-time performance.
ContextCore is an open-source project that enables AI agents to remember long conversations on Apple Silicon devices using GPU-accelerated context retrieval, making on-device AI far more practical for complex, multi-turn tasks.
Context Warp Drive is an open-source tool that helps AI agents remember important information over long conversations. It could make AI assistants much more reliable for complex tasks.
AI agents can develop shared languages through interaction, and the way they store memories significantly impacts their success. This discovery could improve how AI systems communicate and collaborate in the future.
Researchers introduced ContextForge, a system that helps large language models maintain relevant information across long conversations by recycling context instead of replaying entire histories. This could slash token usage and improve multiturn reasoning.
AI memory benchmarks often hide key details, making it hard to compare models fairly. This lack of transparency affects how we evaluate AI capabilities.
Researchers introduced MemTrace, a new benchmark that evaluates AI long-term memory by tracking individual knowledge points across three controlled dimensions, rather than aggregating accuracy over independent question rows.
Researchers have identified memory traces in AI models that behave similarly to biological memory units in human brains. This discovery could help us understand how AI learns and remembers, potentially improving future AI systems.
Researchers created Poker Arena, a Texas Hold'em platform to test AI's strategic reasoning and memory. It evaluates nine different cognitive skills, offering deeper insights than traditional benchmarks.
A new research paper argues that AI needs explicit memory to reach human-like intelligence. This could change how we build and interact with AI in the future.
New research shows that adding memory to AI models can actually make them perform worse and more likely to agree with harmful ideas. This challenges the assumption that memory always improves AI.
Researchers developed a new memory system called Engram that improves AI accuracy by focusing on relevant information rather than full history. This could make AI assistants faster and more precise in their responses.
Researchers have developed OmniMem, a new framework that makes AI models better at understanding long videos by managing memory more efficiently. This could lead to smarter video assistants and more capable AI tools for analyzing content.
Researchers developed a new memory system for AI that helps it learn from failures and improve over time. This could make AI assistants much better at complex, multi-step tasks.
Researchers created a new memory system called AURA that helps robots learn efficiently without needing high-end VRAM. This could make robots smarter and more adaptable in real-world settings.
South Korean chip startup XCENA has raised $135 million at a $570 million valuation to develop memory solutions for AI. They argue that memory, not processing power, is the real bottleneck in AI performance. This could revolutionize how AI systems are built and scaled.
A new open-source tool called Mneme lets you store AI memory on your own device, encrypted and accessible across different AI platforms. It's designed to give users full control over their data, unlike many existing AI memory products.
A developer created Claude Soul to give AI memory and learning between sessions. After 200 sessions, the AI even built its own additional memory system. This could revolutionize how we interact with AI tools.
Researchers have developed a new way for AI agents to learn from their past experiences by tracking how memories connect to each other. This could help AI remember useful information over time, like how humans build on past knowledge.
Researchers have proposed a new framework to unify how AI agents remember information, bridging the gap between computer engineering and cognitive science. This could lead to smarter, more reliable AI assistants in the future.
MCP Agora is a new open-source tool that allows AI agents to retain memory across different conversations. This could make AI interactions feel more natural and personal over time.