[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-9771":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":16,"stars7d":17,"stars30d":18,"stars90d":16,"forks30d":16,"starsTrendScore":17,"compositeScore":19,"rankGlobal":10,"rankLanguage":10,"license":20,"archived":21,"fork":21,"defaultBranch":22,"hasWiki":21,"hasPages":23,"topics":24,"createdAt":10,"pushedAt":10,"updatedAt":29,"readmeContent":30,"aiSummary":31,"trendingCount":16,"starSnapshotCount":16,"syncStatus":32,"lastSyncTime":33,"discoverSource":34},9771,"nupic-legacy","numenta\u002Fnupic-legacy","numenta","Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.","http:\u002F\u002Fnumenta.org\u002F",null,"Python",6350,1537,611,455,0,3,4,40.56,"MIT License",false,"master",true,[25,26,27,28],"artificial-intelligence","hierarchical-temporal-memory","machine-intelligence","neocortex","2026-06-12 02:02:12","# \u003Cimg src=\"http:\u002F\u002Fnumenta.org\u002F87b23beb8a4b7dea7d88099bfb28d182.svg\" alt=\"NuPIC Logo\" width=100\u002F> NuPIC\n\nAs of September 2023 this repository contains code from legacy Hierarchical Temporal Memory (HTM) Numenta projects that have been in maintenance mode for several years.\n\n## Numenta Platform for Intelligent Computing\n\nThe Numenta Platform for Intelligent Computing (**NuPIC**) is a machine intelligence platform that implements the [HTM learning algorithms](https:\u002F\u002Fnumenta.com\u002Fresources\u002Fpapers-videos-and-more\u002F). HTM is a detailed computational theory of the neocortex. At the core of HTM are time-based continuous learning algorithms that store and recall spatial and temporal patterns. NuPIC is suited to a variety of problems, particularly anomaly detection and prediction of streaming data sources. For more information, see [numenta.org](http:\u002F\u002Fnumenta.org) or the [NuPIC Forum](https:\u002F\u002Fdiscourse.numenta.org\u002Fc\u002Fnupic).\n\nFor usage guides, quick starts, and API documentation, see \u003Chttp:\u002F\u002Fnupic.docs.numenta.org\u002F>.\n\n## This project is in Maintenance Mode\n\nWe plan to do minor releases only, and limit changes in NuPIC and NuPIC Core to:\n\n- Fixing critical bugs.\n- Features needed to support ongoing research.\n\n## Installing NuPIC\n\nNuPIC binaries are available for:\n\n- Linux x86 64bit\n- OS X 10.9\n- OS X 10.10\n- Windows 64bit\n\n### Dependencies\n\nThe following dependencies are required to install NuPIC on all operating systems.\n\n- [Python 2.7](https:\u002F\u002Fwww.python.org\u002F)\n- [pip](https:\u002F\u002Fpip.pypa.io\u002Fen\u002Fstable\u002Finstalling\u002F)>=8.1.2\n- [setuptools](https:\u002F\u002Fsetuptools.readthedocs.io)>=25.2.0\n- [wheel](http:\u002F\u002Fpythonwheels.com)>=0.29.0\n- [numpy](http:\u002F\u002Fwww.numpy.org\u002F)\n- C++ 11 compiler like [gcc](https:\u002F\u002Fgcc.gnu.org\u002F) (4.8+) or [clang](http:\u002F\u002Fclang.llvm.org\u002F)\n\nAdditional OS X requirements:\n\n- [Xcode command line tools](https:\u002F\u002Fdeveloper.apple.com\u002Flibrary\u002Fios\u002Ftechnotes\u002Ftn2339\u002F_index.html)\n\n### Install\n\nRun the following to install NuPIC:\n\n    pip install nupic\n\n### Test\n\n    # From the root of the repo:\n    py.test tests\u002Funit\n\n### _Having problems?_\n\n- You may need to use the `--user` flag for the commands above to install in a non-system location (depends on your environment). Alternatively, you can execute the `pip` commands with `sudo` (not recommended).\n- You may need to add the `--use-wheel` option if you have an older pip version (wheels are now the default binary package format for pip).\n\nFor any other installation issues, please see our [search our forums](https:\u002F\u002Fdiscourse.numenta.org\u002Fsearch?q=tag%3Ainstallation%20category%3A10) (post questions there). You can report bugs at https:\u002F\u002Fgithub.com\u002Fnumenta\u002Fnupic\u002Fissues.\n\nLive Community Chat: [![Gitter](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fgitter-join_chat-blue.svg?style=flat)](https:\u002F\u002Fgitter.im\u002Fnumenta\u002Fpublic?utm_source=badge)\n\n### Installing NuPIC From Source\n\nTo install from local source code, run from the repository root:\n\n    pip install .\n\nUse the optional `-e` argument for a developer install.\n\nIf you want to build the dependent `nupic.bindings` from source, you should build and install from [`nupic.core`](https:\u002F\u002Fgithub.com\u002Fnumenta\u002Fnupic.core) prior to installing nupic (since a PyPI release will be installed if `nupic.bindings` isn't yet installed).\n\n- Build:\n[![Build Status](https:\u002F\u002Ftravis-ci.org\u002Fnumenta\u002Fnupic.png?branch=master)](https:\u002F\u002Ftravis-ci.org\u002Fnumenta\u002Fnupic)\n[![AppVeyor Status](https:\u002F\u002Fci.appveyor.com\u002Fapi\u002Fprojects\u002Fstatus\u002F4toemh0qtr21mk6b\u002Fbranch\u002Fmaster?svg=true)](https:\u002F\u002Fci.appveyor.com\u002Fproject\u002Fnumenta-ci\u002Fnupic\u002Fbranch\u002Fmaster)\n[![CircleCI](https:\u002F\u002Fcircleci.com\u002Fgh\u002Fnumenta\u002Fnupic.svg?style=svg)](https:\u002F\u002Fcircleci.com\u002Fgh\u002Fnumenta\u002Fnupic)\n- To cite this codebase: [![DOI](https:\u002F\u002Fzenodo.org\u002Fbadge\u002F19461\u002Fnumenta\u002Fnupic.svg)](https:\u002F\u002Fzenodo.org\u002Fbadge\u002Flatestdoi\u002F19461\u002Fnumenta\u002Fnupic)\n","Numenta Platform for Intelligent Computing (NuPIC) 是一个基于层级时间记忆（HTM）理论的机器智能平台，该理论严格基于大脑新皮层的神经科学研究。NuPIC 的核心功能包括实现 HTM 学习算法，这些算法能够存储和回忆空间与时间模式，特别适用于异常检测和流数据预测等场景。项目采用 Python 语言编写，支持 Linux、OS X 和 Windows 系统，并依赖于 Python 2.7 及其他相关库。尽管目前处于维护模式，但 NuPIC 仍然为需要连续学习能力和处理复杂时序数据的应用提供了强大的工具。",2,"2026-06-11 03:24:40","top_topic"]