engram
PulseAugur coverage of engram — every cluster mentioning engram across labs, papers, and developer communities, ranked by signal.
8 day(s) with sentiment data
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Engram architecture enhances LLMs with efficient memory lookup
A new language model architecture called Engram has been developed, which integrates a scalable lookup table for memory alongside its neural network weights. This approach allows the model to efficiently retrieve common…
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Engram tool cuts AI token use by 89% with local code graph
Engram is a new open-source tool designed to reduce token waste and improve AI debugging by creating a local graph of code files. This approach allows the AI to access information more efficiently, cutting token usage b…
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AI agent memory experiment reveals performance gains from typed retrieval
A recent experiment explored the impact of memory type on AI agent performance, specifically comparing a unified memory store against a system that categorizes and applies distinct retrieval rules for different memory t…
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llama.cpp adds DeepSeek-V4.1-Flash model support with optimizations
The llama.cpp project has released version b11870, which includes support for the DeepSeek-V4.1-Flash model. This update incorporates several optimizations for the DeepSeek model, such as converting its Engram table to …
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Developer builds graph-based AI memory system to overcome tool context limitations
A developer has created Engram, a novel memory system for AI tools that utilizes a graph database instead of traditional vector stores. This approach addresses the issue of AI tools lacking shared context and memory, wh…
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MemoryAthena system explores generated memories for language models
Researchers have developed MemoryAthena, a novel system that explores the use of generated memories in addition to retrieved ones for language models. This system employs three pathways: direct retrieval from an explici…
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UK Politician Sues xAI Over Deepfake; AI Development Trends Discussed · 10 sources tracked
A UK politician, Jess Asato, is suing xAI after being deepfaked, highlighting concerns about AI misuse. Separately, discussions around AI development cover the orchestration and tooling necessary for production-ready AI…
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Engram adds persistent memory to coding agents via local knowledge graph
Engram, a new tool, aims to provide coding agents with persistent memory across sessions by storing decisions, reasons, and warnings in a local knowledge graph. This graph, built using SQLite, allows agents to recall re…
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STAPLE method enhances LLM capacity with static sparse memory
Researchers have developed STAPLE, a novel method for integrating static sparse memory into pretrained language models. This approach enhances model capacity without a proportional increase in computational cost, outper…
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SemiAnalysis discusses GPU economics, InferenceX, and new hardware
SemiAnalysis discussed the economics of GPUs, featuring the InferenceX team's insights on Engram memory offloading and AgentX's profit calculator. The conversation also touched upon TPU v7, a comparison between Vera Rub…
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MIT PhD candidate explores Recursive Language Models and agent swarms
Alex Zhang, a PhD candidate at MIT, is exploring the potential of Recursive Language Models (RLMs) and advanced agent systems to unlock greater AI capabilities. His research, detailed in a Latent Space podcast, delves i…
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Mastodon users critique AI's pervasiveness, ethical concerns, and environmental impact · 10 sources tracked
Multiple Mastodon users are expressing concerns and criticisms regarding the pervasive influence and ethical implications of AI. Discussions touch upon the potential for AI to undermine business models, the violation of…
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FactorEngram enhances language models with factorized n-gram memory
Researchers have introduced FactorEngram, a novel approach to enhance language models by incorporating factorized n-gram memory with basis-level contextual gating. This method improves upon existing lookup-based memory …
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Developer releases new 2B parameter AI model 'Engram' with novel token probability table
A developer has created a new 2 billion parameter model called Engram, which utilizes a 1 billion parameter Engram table for enhanced token probability. Despite training on only 15 million tokens, the model demonstrates…
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Researchers explore small AI models using n-gram techniques
A user on the r/LocalLLaMA subreddit is inquiring about the existence of experimental small language models (9 billion parameters or less) that utilize n-gram or engram techniques. The user notes a lack of such models o…
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AI coding tools gain persistent memory via Model Context Protocol
Developers using AI coding assistants like Cursor and Claude Code often face the frustration of these tools forgetting project context between sessions. Solutions range from static rules files to memory plugins, but man…
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Engram's persistent memory system debugged for coding agents
The author details their experience using Engram, a local persistent memory system for coding agents, during a short break. They found the architecture straightforward, utilizing Go, SQLite with FTS5, and an MCP server,…
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Engram AI Tool Emerges to Aid Coding Tasks
Engram is a new AI tool designed to assist with coding tasks. The tool aims to streamline the development process by providing intelligent assistance to programmers. Further details about its specific functionalities an…
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Engram memory transfer between LLMs relies on reader adaptation
Researchers have developed a method called "Engram" for transferring external knowledge between large language models. Their study indicates that the effectiveness of this transfer relies more on the target model's "rea…
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Chinese team EverMind publishes full-stack self-evolving AI framework · 1 source tracked
A Chinese research team, EverMind, has published three papers detailing a comprehensive approach to self-evolving AI, addressing key challenges in the field. Their work focuses on improving AI's long-term memory and ena…