engram
PulseAugur coverage of engram — every cluster mentioning engram across labs, papers, and developer communities, ranked by signal.
4 day(s) with sentiment data
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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…
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DeepSeek's Engram Module Made Tokenizer-Agnostic
Researchers have developed a tokenizer-agnostic engram module for large language models, building upon DeepSeek's original design. The new approach replaces XOR-based hashing with polynomial hashing, creating a joint em…
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Hongxiong AI raises hundreds of millions for AI memory science
Hongxiong AI has secured several hundred million yuan in Series A+ funding, valuing the company at nearly 3 billion yuan. This latest round, their sixth in 15 months, was co-led by Zhejiang Jiuwei Private Equity and Jia…
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Brex, Weaviate, and Paper enhance AI agent security and functionality
Brex has developed CrabTrap, an HTTP/HTTPS proxy designed to enhance AI agent security by monitoring outbound network requests and automatically drafting security policies based on observed agent behavior. This approach…
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Codex user surge to 7M sparks debate with Claude Code · 2 sources tracked
Codex has experienced a significant surge in user growth, reaching 7 million active users by mid-July 2026, with over a million new users in the preceding 24 hours following the GPT-5.6 launch. This growth trajectory ha…
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AI agent Engram uses 'forgetting' as a feature to improve memory recall
An AI agent named Engram was developed for the Global AI Hackathon, incorporating a novel forgetting mechanism to manage its memory. Unlike traditional agents that store all information, Engram uses an Ebbinghaus-inspir…
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Engram tool centralizes AI code memories for team sharing
Engram is a new open-source tool designed to help developers manage their AI's code memories. This text-based user interface (TUI) centralizes an AI's memory, allowing it to be shared with a team using standard Git prac…
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Engram pioneers AI 'memory' by baking knowledge into weights, not just context
AI startup Engram is developing a novel approach to AI memory and continual learning, aiming to embed specialized knowledge directly into model weights rather than relying solely on retrieval-augmented generation (RAG) …
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Engram raises $98M for private-context AI models
Engram has secured $98 million in funding from prominent venture capital firms including General Catalyst, Kleiner Perkins, and Sequoia. The company aims to develop AI models that are trained on a single company's priva…
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New 'User as Engram' method personalizes LLMs with brain-inspired memory edits
Researchers have proposed a new method called "User as Engram" for personalizing language models, drawing inspiration from the human brain's memory systems. Unlike current approaches that store user data externally or u…
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New TN-gram module enhances LLM memory efficiency
Researchers have introduced Tensorized Engram (TN-gram), a novel memory module for large language models designed to improve how they handle multi-token patterns. Unlike previous methods that use separate memory structu…
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Engram Module's Role in Image Generation Questioned in New Research
A new paper investigates the Engram module, a component designed to enhance Transformer layers with associative memory, and its application to autoregressive image generation. The research adapted Engram for vision task…
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Lngram module learns discrete symbols for improved sequence modeling
Researchers have introduced Lngram, a novel module for sequence modeling that operates in latent space. Unlike previous methods that rely on tokenization, Lngram learns discrete symbols directly from hidden states and p…
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New 'Misattribution Gap' Attack Targets AI Memory Layers
A new research paper, "The Misattribution Gap," introduces "Semantic Norm Drift" (SND) as a novel attack vector for agentic AI systems. This attack exploits the memory layer, making it difficult to distinguish from mode…