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  • 1
    Concurrent vision processing system; Toolkit for easy implementation of software concurrent vision processing sub-system. Aimed at robotic applications w/best effort realtime. System includes: capture,processing and displaying.
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  • 2
    The PSU Mars Rover Software System is a collection of modules connected via shared memory space which allow the operation of various sub-systems to control the rover in all of its tasks; especially navigation.
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  • 3
    A correlation detector that uses common sens. It can be used to derive information from log files for instance. It searches for the trigger and initial conditions of a user defined event. A sub-module of this project (called upamaana) can also be used as
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  • 4
    Kimi K2.6

    Kimi K2.6

    Multimodal agent model for coding, orchestration, and autonomy

    ...Beyond coding, it can transform prompts and visual inputs into production-ready interfaces and lightweight full-stack outputs with structured layouts, interactivity, and polished visual detail. One of its most distinctive capabilities is horizontal agent scaling, supporting up to 300 sub-agents and 4,000 coordinated steps in a single run, which enables parallel task decomposition and end-to-end completion of outputs such as documents, websites, and spreadsheets. Architecturally, it uses a 1T-parameter Mixture-of-Experts design with 32B activated parameters, a MoonViT vision encoder, and a 256K context window.
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    Go from Code to Production URL in Seconds

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  • 5
    Nemotron 3.5 Lightning

    Nemotron 3.5 Lightning

    Efficient 30B MoE model for long-running agents and local inference

    NVIDIA Nemotron 3.5 Lightning 30B-A3B NVFP4 is an open large language model optimized for efficient autonomous agents, sub-agent deployments, and local inference. It uses a hybrid Mixture-of-Experts architecture combining Mamba-2, MoE, and selected attention layers, with 30B total parameters but only 3B active during inference. The model supports context windows up to 1 million tokens, enabling long-running workflows and large-context reasoning. Its NVFP4 quantization reduces deployment requirements while targeting NVIDIA hardware ranging from DGX Spark and RTX 5090 systems to H100, H200, and GB200 accelerators. ...
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  • 6
    VaultGemma

    VaultGemma

    VaultGemma: 1B DP-trained Gemma variant for private NLP tasks

    VaultGemma is a sub-1B parameter variant of Google’s Gemma family that is pre-trained from scratch with Differential Privacy (DP), providing mathematically backed guarantees that its outputs do not reveal information about any single training example. Using DP-SGD with a privacy budget across a large English-language corpus (web documents, code, mathematics), it prioritizes privacy over raw utility.
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