Search Results for "hard"
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Showing 50 open source projects for "hard"
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Demo Series - Small Business Backup By VeeamWatch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
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VideoCaptioner
AI-powered tool for generating, optimizing, and translating subtitles
...It can also translate subtitles into other languages while preserving the original timing, making it suitable for multilingual video publishing and accessibility. In addition to generating subtitles, it supports editing, formatting, and embedding subtitles into videos as either hard or soft subtitles. -
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Middleware
Open-source DORA metrics platform for engineering teams
Bring more visibility to your engineering pipeline, get the right data & actionable insights to unclog bottlenecks, ensuring smooth software delivery. -
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PX4 Autopilot
PX4 Autopilot Software
...PX4 provides a standard to deliver drone hardware support and software stack, allowing an ecosystem to build and maintain hardware and software in a scalable way. Drone development is complicated, and how to get started can be daunting and hard to navigate. These tutorials and resources provide a walkthrough of the basics of PX4. PX4 is highly portable, OS-independent and supports Linux, NuttX and MacOS out of the box. The PX4 User Guide explains how to assemble supported vehicles and fly drones with PX4. See the forum and chat if you need help! -
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OpenHands
Open-source autonomous AI software engineer
Welcome to OpenHands (formerly OpenDevin), an open-source autonomous AI software engineer who is capable of executing complex engineering tasks and collaborating actively with users on software development projects. Use AI to tackle the toil in your backlog, so you can focus on what matters: hard problems, creative challenges, and over-engineering your dotfiles We believe agentic technology is too important to be controlled by a few corporations. So we're building all our agents in the open on GitHub, under the MIT license. Our agents can do anything a human developer can: they write code, run commands, and use the web. ... -
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
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5
AI Coding Dictionary
AI coding jargon, explained in plain English
...Its tone is intentionally direct and accessible, avoiding dense academic or vendor-heavy language. The project helps users name what is happening when prompts fail, context degrades, tools behave unexpectedly, or agent sessions become hard to manage. Its main value is turning AI coding jargon into practical vocabulary that developers can understand quickly and use in real work. -
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supervision
We write your reusable computer vision tools
We write your reusable computer vision tools. Whether you need to load your dataset from your hard drive, draw detections on an image or video, or count how many detections are in a zone. You can count on us. -
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HyperAgent
AI Browser Automation
...Built on top of Playwright, the framework allows developers to automate complex browser interactions using natural language commands rather than fragile selectors or hard-coded scripts. Instead of manually writing logic for clicking elements, extracting data, or navigating web pages, developers can instruct the agent in plain language and allow the AI layer to interpret and execute the task. This approach reduces the brittleness commonly associated with traditional automation scripts that break when the DOM structure changes. ... -
8
LangChain
⚡ Building applications with LLMs through composability ⚡
Large language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge. This library is aimed at assisting in the development of those types of applications. -
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Rubix ML
A high-level machine learning and deep learning library for PHP
...In addition, we provide tutorials and other educational content to help you get started using ML in your projects. Our intuitive interface is quick to grasp while hiding alot of power and complexity. Write less code and iterate faster leaving the hard stuff to us. Rubix ML utilizes a versatile modular architecture that is defined by a few key abstractions and their types and interfaces. Train models in a fraction of the time by installing the optional Tensor extension powered by C. Learners such as neural networks will automatically get a performance boost. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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NeuroMatch Academy (NMA)
NMA Computational Neuroscience course
NMA Computational Neuroscience course. We have curated a curriculum that spans most areas of computational neuroscience (a hard task in an increasingly big field!). We will expose you to both theoretical modeling and more data-driven analyses. The Neuro Video Series is a series of 12 videos that covers basic neuroscience concepts and neuroscience methods. These videos are completely optional and do not need to be watched in a fixed order so you can pick and choose which videos will help you brush up on your knowledge. ... -
11
PML
The easiest way to use deep metric learning in your application
...Anchor-positive pairs are formed by embeddings that share the same label, and anchor-negative pairs are formed by embeddings that have different labels. Loss functions can be customized using distances, reducers, and regularizers. In the diagram below, a miner finds the indices of hard pairs within a batch. These are used to index into the distance matrix, computed by the distance object. For this diagram, the loss function is pair-based, so it computes a loss per pair. -
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DeepXDE
A library for scientific machine learning & physics-informed learning
...Solving forward/inverse integro-differential equations (IDEs) [SIAM Rev.] fPINN: solving forward/inverse fractional PDEs (fPDEs) [SIAM J. Sci. Comput.] NN-arbitrary polynomial chaos (NN-aPC): solving forward/inverse stochastic PDEs (sPDEs) [J. Comput. Phys.] PINN with hard constraints (hPINN): solving inverse design/topology optimization [SIAM J. Sci. Comput.] Residual-based adaptive sampling [SIAM Rev., arXiv] Gradient-enhanced PINN (gPINN) [Comput. Methods Appl. Mech. Eng.] PINN with multi-scale Fourier features [Comput. Methods Appl. Mech. Eng.] -
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lightning AI
The most intuitive, flexible, way for researchers to build models
Build in days not months with the most intuitive, flexible framework for building models and Lightning Apps (ie: ML workflow templates) which "glue" together your favorite ML lifecycle tools. Build models and build/publish end-to-end ML workflows that "glue" your favorite tools together. Models are “easy”, the “glue” work is hard. Lightning Apps are community-built templates that stitch together your favorite ML lifecycle tools into cohesive ML workflows that can run on your laptop or any cluster. Find templates (Lightning Apps), modify them and publish your own. Lightning Apps can even be full standalone ML products! Run on your laptop for free! Download the code and type 'lightning run app'. ... -
14
img2obj
Codex plugin that turns attached object images into code-only
...It first checks whether the image is suitable, then creates an ObjectSculptSpec describing geometry, materials, hierarchy, pivots, sockets, and visual priorities. Reconstruction proceeds through blockout, form, look development, and interaction phases so details are added in a controlled order. The plugin supports hard-surface objects, organic forms, vegetation, fabrics, glass, hair, emissive surfaces, and decals. Generated models can include animation-ready parent-child relationships and detachable or articulated parts. Visual review compares browser renders with the source and requires important differences to be corrected before promotion. Outputs include a TypeScript Three.js factory, structured specifications, comparison evidence, optional procedural PBR maps, and review checkpoints. -
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Council of High Intelligence
18 AI personas deliberate your hardest decisions
Council of High Intelligence is an AI deliberation framework that lets multiple expert-style personas analyze hard decisions together. Instead of relying on one model response, it creates structured disagreement between different intellectual roles such as Socrates, Feynman, Kahneman, Torvalds, Aristotle, and others. The project supports multi-round reasoning, cross-examination, dissent quotas, novelty checks, and model diversity across different providers. -
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native-feel.skill
An Agent Skill for designing cross-platform desktop apps
...The project is useful when an agent is advising on desktop apps that need global shortcuts, system tray behavior, native windows, fast interaction, and polished platform conventions. Its main value is turning hard-won desktop architecture knowledge into reusable agent guidance. -
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Unity ML-Agents Toolkit
Unity machine learning agents toolkit
Train and embed intelligent agents by leveraging state-of-the-art deep learning technology. Creating responsive and intelligent virtual players and non-playable game characters is hard. Especially when the game is complex. To create intelligent behaviors, developers have had to resort to writing tons of code or using highly specialized tools. With Unity Machine Learning Agents (ML-Agents), you are no longer “coding” emergent behaviors, but rather teaching intelligent agents to “learn” through a combination of deep reinforcement learning and imitation learning. ... -
18
CyberPPT
A Codex Skill for generating high-density, editable PowerPoints
...Multiple quality gates inspect structure, visuals, overflow, spatial alignment, curves, and editable elements. Delivery includes the PPTX, rendered previews, manifests, and QA results, with failed hard gates blocking completion. -
19
eos
A lightweight 3D Morphable Face Model library in modern C++
eos is a lightweight 3D Morphable Face Model fitting library that provides basic functionality to use face models, as well as camera and shape fitting functionality. It's written in modern C++11/14. MorphableModel and PcaModel classes to represent 3DMMs, with basic operations like draw_sample(). Supports the Surrey Face Model (SFM), 4D Face Model (4DFM), Basel Face Model (BFM) 2009 and 2017, and the Liverpool-York Head Model (LYHM) out-of-the-box. -
20
NeuralForecast
Scalable and user friendly neural forecasting algorithms.
...There is a shared belief in Neural forecasting methods' capacity to improve forecasting pipeline's accuracy and efficiency. Unfortunately, available implementations and published research are yet to realize neural networks' potential. They are hard to use and continuously fail to improve over statistical methods while being computationally prohibitive. For this reason, we created NeuralForecast, a library favoring proven accurate and efficient models focusing on their usability. -
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diff2html
Pretty diff to html javascript library (diff2html)
...Each diff features a line-by-line and side-by-side preview of your changes. All the code changes are syntax highlighted using highlight.js, providing more readability. Similar lines are paired, allowing for easier change tracking. We work hard to make sure you can have your diffs in a simple and flexible way. The AI community building the future. Build, train and deploy state of the art models powered by the reference open source in natural language processing. Wrapper and helper adding syntax highlight, synchronized scroll, and other nice features. You can use it without syntax highlight or by passing your own implementation with the languages you prefer. ... -
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GitHub MCP Server
GitHub's official MCP Server
...It’s designed to run locally or remotely and then be attached to MCP-capable clients (for example, Copilot Chat) so an LLM can search code, open files, create branches, draft PRs, label or triage issues, and query metadata without hard-coding GitHub APIs. The server defines tools and resources with fine-grained scopes, leaning on GitHub’s auth to enforce least privilege and auditable access. It supports both stdio and HTTP transports, enabling IDE and headless integrations, and adopts common MCP behaviors like prompts, schemas, and tool definitions to keep agent calls predictable. ... -
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Rhino
On-device Speech-to-Intent engine powered by deep learning
...Measure adoption, learn, and iterate. Continuously re-design and re-train to optimize engagement. Building accurate, responsive, and private voice technology is difficult. We learned the hard way, so you don’t have to. Picovoice heavily invests in R&D to offer superior voice AI that surpasses even Big Tech in accuracy and efficiency. Picovoice researchers do not follow recent frameworks and techniques but build them. -
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ollama_manager_gui
A graphical manager for ollama that can manage your LLMs
...It can launch the LLM by clicking the link. it can launch multiple LLMs in separate windows. It can also remove an installed LLM. There is a confirmation dialog when removing or hard resetting an LLM. It can also install LLMs. Reset deletes all data for LLM of your choosing and automatically reinstalls that LLM of your choosing by redownloading. You can also install new LLMs by simply clicking the install button. warning... you can remove custom LLMs with this... Remember with great power comes greater responsibility! ... -
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CycleGAN
Software that can generate photos from paintings
CycleGAN — in its original form — is a landmark in deep learning for image-to-image translation without paired data. Rather than requiring matching image pairs between source and target domains (which are often hard or impossible to obtain), CycleGAN learns two mappings — one from domain A to B, and another back from B to A — along with a cycle-consistency loss that encourages the round-trip to reconstruct the original image. This innovation lets the model learn domain-to-domain translations like turning horses into zebras, changing seasons, or transforming photos into paintings, using only collections of images from each domain. ...
