Search Results for "matter"
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12 projects for "matter" with 2 filters applied:
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Happy Coder
Mobile and Web client for Codex and Claude Code, with realtime voice
Happy is an open-source, cross-platform mobile and web client designed to bring powerful AI coding agents such as Claude Code and Codex to your fingertips no matter where you are. At its core, Happy wraps existing AI coding tools with a unified interface, providing real-time voice interactions, encrypted communication, and seamless device switching between desktop and mobile. You can start a coding session locally through the Happy CLI or connect from a phone or browser, allowing developers to inspect, interact with, and guide the AI as it generates, tests, or explains code. ... -
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MimiClaw
Run OpenClaw on a $5 chip
...Even though it’s running on minimal hardware, MimiClaw maintains local memory that persists across power cycles, enabling context continuity over time without relying on cloud services. Its architecture emphasizes privacy, low power, and portability, ideal for personal or hobbyist use cases where privacy and local control matter. -
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DFlash
Block Diffusion for Ultra-Fast Speculative Decoding
...This approach has been shown to deliver lossless acceleration on models like Qwen3-8B by combining block diffusion techniques with efficient batching, making it ideal for applications where latency and cost matter. The project includes support for multiple draft models, example integration code, and scripts to benchmark performance, and it is structured to work with popular model serving stacks like SGLang and the Hugging Face Transformers ecosystem. -
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agents.md
A simple, open format for guiding coding agents
openai/agents.md is a repository whose primary file is AGENTS.md, a proposed open, lightweight convention (i.e. Markdown file) for guiding coding agents in software repositories. The idea is that AGENTS.md acts as a “README for agents”: a predictable, structured place where humans can put instructions, conventions, build/test commands, environment setup, and other guidance that generative agents (e.g. code-writing, code-assisting tools) should consult when operating in the repo. Instead of... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Dia2
TTS model capable of streaming conversational audio in realtime
...It currently focuses on English generation and supports up to two minutes of generated audio. Its main value is enabling low-latency, dialogue-oriented TTS workflows where timing, turn-taking, and natural conversation matter. -
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WorldGen
Generate Any 3D Scene in Seconds
WorldGen is an AI model and library that can generate full 3D scenes in a matter of seconds from either text prompts or reference images. It is designed to create interactive environments suitable for games, simulations, robotics research, and virtual reality, rather than just static 3D assets. The core idea is that you describe a world in natural language and WorldGen produces a navigable 3D scene that you can freely explore in 360 degrees, with loop closure so that the space remains consistent as you move around. ... -
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Vedana
Open source multi-agent RAG over a knowledge graph
...It also includes JIMS, a framework for persistent conversational agents with typed events and pluggable pipelines. Overall, Vedana is useful for teams that need reliable answers from real data, especially when relationships, counts, rules, and source-backed reasoning matter. -
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TokenSpeed
TokenSpeed is a speed-of-light LLM inference engine
...It aims to combine TensorRT-LLM-level speed with vLLM-level usability, making it relevant for teams that need fast generation without sacrificing developer ergonomics. The project is focused on the specific needs of agentic systems, where latency, throughput, and efficient scheduling matter across many short or tool-heavy requests. It builds on ideas and components from the broader open-source inference ecosystem while presenting its own execution stack. TokenSpeed is useful for developers building local or server-side LLM infrastructure for agents, coding systems, and high-volume AI applications. Its main value is providing an inference layer optimized for fast token generation under practical agent workloads. -
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Trail of Bits Skills Marketplace
Trail of Bits Claude Code skills for security research, vulnerability
Trail of Bits Skills Marketplace is a specialized Claude Code skills marketplace built by the security research firm Trail of Bits that focuses on enhancing AI-assisted workflows for vulnerability discovery, testing, and secure development. The repository groups a set of plug-in skills tailored toward static analysis, code auditing, secure defaults detection, and other practices that matter in software security. Users can easily add the marketplace to a Claude Code environment, browse available plugins, and install specific skills for tasks like automatic Semgrep rule creation, entry-point analysis in smart contracts, or insecure defaults detection. This project leverages the agent skills architecture to let AI assistants take on detailed, repeatable security procedures that are typically manual, such as parsing Burp Suite projects or conducting variant analysis across codebases. -
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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JEPA
PyTorch code and models for V-JEPA self-supervised learning from video
...The repository provides training recipes, data pipelines, and evaluation utilities for image JEPA variants and often includes ablations that illuminate which masking and architectural choices matter. Because the objective is non-autoregressive and operates in embedding space, JEPA tends to be compute-efficient and stable at scale. The approach has become a strong alternative to contrastive or pixel-reconstruction methods for representation learning. -
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DeiT (Data-efficient Image Transformers)
Official DeiT repository
...Training involves carefully tuned augmentations, regularization, and optimization schedules to stabilize learning and improve sample efficiency. The repo offers pretrained checkpoints, reference scripts, and ablation studies that clarify which ingredients matter most for data-efficient ViT training. -
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FastViT
This repository contains the official implementation of research
FastViT is an efficient vision backbone family that blends convolutional inductive biases with transformer capacity to deliver strong accuracy at mobile and real-time inference budgets. Its design pursues a favorable latency-accuracy Pareto curve, targeting edge devices and server scenarios where throughput and tail latency matter. The models use lightweight attention and carefully engineered blocks to minimize token mixing costs while preserving representation power. Training and inference recipes highlight straightforward integration into common vision tasks such as classification, detection, and segmentation. The codebase provides reference implementations and checkpoints that make it easy to evaluate or fine-tune on downstream datasets. ...
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