AI · alternatives · 2026
24 alternatives to Living Memory Dynamics – "living" episodic memory embedding space
I built Living Memory Dynamics (LMD), a Python framework for simulating biologically-inspired "living" episodic memory directly in embedding space—no external LLM required for the core dynamics. Memories evolve over time like living entities: they have metabolic energy states (vivid → active → dormant → fading → ghost), emotional trajectories, and resonance fields that let them influence each other. The central piece is a new differential equation I derived (the Joshua R. Thomas Memory Equation) that drives continuous-time evolution: dM/dt = ∇φ(N) + Σⱼ Γᵢⱼ R(vᵢ, vⱼ) + A(M, ξ) + κη(t)…
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
- 1
Most RAG setups fail because they treat memory like a static filing cabinet. When every transient bug fix or abandoned rule is stored forever, the context window eventually chokes on noise, spiking token costs and degrading the agent's reasoning. This implementation experiments with a biological approach by using the Ebbinghaus forgetting curve to manage context as a living substrate. Memories are assigned a "strength" score where each recall reinforces the data and flattens its decay curve (spaced repetition), while unused data eventually hits a threshold and is pruned. To solve the…
Apr 2026 · github.com · its alternatives →
- 2
Memori▲168Persistent memory from agent trace, not just conversation
May 2026 · memorilabs.ai · its alternatives →
- 3RG
Hey HN! I'm José, and I built Recall to solve a problem that was driving me crazy. The Problem: I use Claude for coding daily, but every conversation starts from scratch. I'd explain my architecture, coding standards, past decisions... then hit the context limit and lose everything. Next session? Start over. The Solution: Recall is an MCP (Model Context Protocol) server that gives Claude persistent memory using Redis + semantic search. Think of it as long-term memory that survives context limits and session restarts. How it works: - Claude stores important context as "memories" during…
2025 · npmjs.com · its alternatives →
- 4
CogniMemo▲120AI that remembers, learns, and evolves
Dec 2025 · app.cognimemo.com · its alternatives →
- 5
Hi HN, I turned the freshly published paper “The Constructor Theory of Time” by David Deutsch and Chiara Marletto (arXiv, 13 May 2025) into an executable Python library. What you’ll find • One-to-one translation of the paper’s formalism: Substrates, Attributes, Tasks, Constructors, and task-algebra operators • Possibility / impossibility predicates and counterfactuals encoded exactly as defined • Test suite that mirrors every lemma and example (>95 % coverage, mypy-typed) • Reproductions of key results: time-keeping substrates, irreversibility proofs, quantum branching tasks, and a…
2025 · github.com · its alternatives →
- 6
YourMemory▲93This is a project that I have been building for a while now, YourMemory is a solution to agentic memory which focuses on pruning of noise rather than hoarding of data. In the current state of agentic memory most of the context is stored in the form of a MD file or is derived through a RAG model where you store each and everything. Both of the solution leads to bloated context which does not optimize the usage of any tokens. In this system we only keep relevant data in our memory and prune all the unnecessary data. The relevance of a data is derived through multiple factors such as recall…
Apr 2026 · yourmemoryai.vercel.app · its alternatives →
- 7
A research project simulating the evolution of virtual corals - 2018.
2018 · joelsimon.net · its alternatives →
- 8
Hi HN, I have been recently geeking on agentic memories, and I believe I finally came up with something that works. I spent the last couple of weeks building a memory[0] for Claude Code that dynamically evolve as you talk with it. I followed a new paradigm inspired from zettelkasten method. Whenever Claude discover something new in the codebase or during your conversation with it, it writes a note about it, link it with related memories, update the related memories accordingly, and store it in chromaDB (this part where it keeps self-evolving based on new inputs). Later when you ask it to…
Jan 2026 · github.com · its alternatives →
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- 10
I have a proposal that addresses long-term memory problems for LLMs when new data arrives continuously (cheaply!). The program involves no code, but two Markdown files. For retrieval, there is a semantic filesystem that makes it easy for LLMs to search using shell commands. It is currently a scrappy v1, but it works better than anything I have tried. Curious for any feedback!
Apr 2026 · github.com · its alternatives →
- 11
Claude.ai artifacts can call the Anthropic API and have persistent storage (5MB via window.storage). I used these two capabilities to build a memory system modeled on how human memory actually works — salience scoring, forgetting curves, and sleep consolidation — all running inside a single React artifact with no external dependencies. Just add artifact to your chat and paste instructions into your personal preferences setting.
Feb 2026 · github.com · its alternatives →
- 12
Robot Memory - Persistent memory system for AI robots. MCP Server + hybrid search + spatial retrieval. - robotmem/robotmem
Mar 2026 · github.com · its alternatives →
- 13
An agent that remembers across sessions can keep its memory as curated markdown files, as an auto-mined structured store, or as trained experience.
Aug 2026 · pinglin.tw · its alternatives →
- 14WI
Hi HN! I've been exploring what happens when we treat code not as architecture but as a living ecosystem. Demo: https://nabolitains.github.io/plasma/ This started from a simple question: The slime mold Physarum can solve mazes without a brain. What if our code could similarly self-organize? The result is Plasma - computational cells that: - Metabolize energy from their environment - Reproduce with mutations - Form emergent colonies nobody designed - Die (and that's a feature) No ML, no complex algorithms. Just simple rules creating complex behaviors. The entire thing is…
2025 · nabolitains.github.io · its alternatives →
- 15IM
Just a fun toy I wanted to make. I've been studying and playing around with language models lately and have always been intrigued by how words are processed by these models. Since the vectors generated by embedding models is in very high dimensional space, I thought it would be cool to reduce them to 3D vectors and visualise them myself. This is what I have so far!
2023 · seesaurus.com · its alternatives →
- 16
Hello HN! I built collabmem, a simple memory system for long-term collaboration between humans and AI assistants. And it's easy to install, just ask Claude Code: Install the long-term collaboration memory system by cloning https://github.com/visionscaper/collabmem to a temporary location and following the instructions in it. To collaborate with AI over weeks, months, or even years, there needs to be a shared conceptual understanding of: - History (episodic memory): what has been done, why, and what was decided and learned along the way. - Reality (world model): what the…
Apr 2026 · github.com · its alternatives →
- 17
Local, gradient-free neuro-symbolic memory engine combining Hyperdimensional Computing (HDC/VSA), Hebbian plasticity, and graph triples for offline AI. - roandejager/Hillock
Aug 2026 · github.com · its alternatives →
- 18
I’ve been working on a browser-based evolutionary simulation as a personal experiment. Organisms adapt to environmental pressure over time, and there are no explicit goals or scoring, the system is open-ended and runs continuously. I built this mainly to challenge myself and to explore how to surface simulation behavior and statistics in a way that stays readable rather than overwhelming. As a side effect, it’s also something my kids enjoys watching run. Curious what resonates and what doesn’t, and happy to answer questions about the design or tradeoffs.
Jan 2026 · soupof.life · its alternatives →
- 19
Hey HN! I built Memoripy, a memory layer for AI that adds short-term, long-term, and semantic memory capabilities to enhance LLM applications. It helps AI systems retain and prioritize past interactions, adapt over time, and respond with greater context and personalization. Memoripy uses semantic clustering to retrieve relevant memories, along with adaptive memory decay and reinforcement, so interactions stay fresh and context-aware. It’s designed for easy integration with OpenAI, Ollama, and other platforms—giving your AI applications dynamic memory management with minimal setup. Would love…
2024 · github.com · its alternatives →
- 20
Hi HN. Live-Memory is an open-source Claude Code plugin / MCP server that serves as an always up-to-date memory of your codebase. It uses a separate, low-cost, large-context-window model to distill your repo's organization, conventions and general structure. It observes the primary agent's activity and builds an understanding of your repo passively over time. This way, when you start a new Claude Code session, your primary agent queries Live-Memory via one read-only ask_live_memory tool and bootstraps its understanding of the codebase for the particular task at hand, instead of…
Jul 2026 · github.com · its alternatives →
- 21YP
It's an biological inspired decay system for our memories with extended support of temporal reasoning. Created a CLI command to infer knowledge from the context stored in memory system without any token utilization or llm call. It comes with a memory dashboard to monitor and manage your memories it can be extended as audit trail for agents as well !
May 2026 · its alternatives →
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- 23ZL
Zep is a long-term memory store designed for conversational AI applications built using modern LLMs. It handles the storage, summarization, embedding, indexing, and enrichment of chat histories, and offers developers a simple, low-latency API to this data. Chat history storage is an infrastructure challenge all developers and enterprises face as they look to move from prototypes to deploying conversational AI applications that provide rich and intimate experiences to users. Key features include long-term memory persistence, auto-summarization, vector search, auto-token counting, and Python…
2023 · its alternatives →
- 24
RLLama▲11Empowering LLMs with Memory-Augmented Reinforcement Learning
2025 · github.com · its alternatives →
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