Reinforcement Learning Dual DQN on LabVIEW with SOTA











>> YOUR LINK HERE: ___ http://youtube.com/watch?v=xtnZkJABG1E

Taking advantage of the big advantage of LabVIEW compared to classic syntactic languages, namely the rapid implementation of agents by integrating the model into an efficient and adapted software architecture, we have decided to develop a set of new generation modules and tools for LabVIEW focused on robotics, AI, and automation. • We're preparing the release of new generations toolkits for the LabVIEW ecosystem, here's a glimpse of what awaits you in the coming weeks: • ๐—™๐˜‚๐—น๐—น ๐—ฐ๐—ผ๐—บ๐—ฝ๐—ฎ๐˜๐—ถ๐—ฏ๐—ถ๐—น๐—ถ๐˜๐˜† ๐˜„๐—ถ๐˜๐—ต ๐—ฎ๐—น๐—น ๐—ฒ๐˜…๐—ถ๐˜€๐˜๐—ถ๐—ป๐—ด ๐—ณ๐—ฟ๐—ฎ๐—บ๐—ฒ๐˜„๐—ผ๐—ฟ๐—ธ๐˜€: Keras, TensorFlow, PyTorch, ONNX. • ๐—ฆ๐˜๐˜‚๐—ป๐—ป๐—ถ๐—ป๐—ด ๐—ฝ๐—ฒ๐—ฟ๐—ณ๐—ผ๐—ฟ๐—บ๐—ฎ๐—ป๐—ฐ๐—ฒ: HAIBAL 2 will be 50 times faster than the first HAIBAL generation and 20% faster than PyTorch. • ๐Ÿฏ๐Ÿฎ ๐—ฎ๐—ป๐—ฑ ๐Ÿฒ๐Ÿฐ-๐—ฏ๐—ถ๐˜ ๐˜€๐˜‚๐—ฝ๐—ฝ๐—ผ๐—ฟ๐˜: Deployment on 32-bit systems with limited functionality. • ๐—›๐—ฎ๐—ฟ๐—ฑ๐˜„๐—ฎ๐—ฟ๐—ฒ ๐˜€๐˜‚๐—ฝ๐—ฝ๐—ผ๐—ฟ๐˜: Support for CUDA, TensorRT for NVIDIA, Rocm for AMD, OneAPI for Intel. • ๐— ๐—ฎ๐˜…๐—ถ๐—บ๐˜‚๐—บ ๐—บ๐—ผ๐—ฑ๐˜‚๐—น๐—ฎ๐—ฟ๐—ถ๐˜๐˜†: Define your own layers and loss functions. • ๐—š๐—ฟ๐—ฎ๐—ฝ๐—ต ๐—ก๐—ฒ๐˜‚๐—ฟ๐—ฎ๐—น ๐—ก๐—ฒ๐˜๐˜„๐—ผ๐—ฟ๐—ธ๐˜€: Complete and advanced integration. • ๐—”๐—ป๐—ป๐—ผ๐˜๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐˜๐—ผ๐—ผ๐—น๐˜€: An annotator as efficient as Roboflow, integrated into our software suite. • ๐— ๐—ผ๐—ฑ๐—ฒ๐—น ๐˜ƒ๐—ถ๐˜€๐˜‚๐—ฎ๐—น๐—ถ๐˜‡๐—ฎ๐˜๐—ถ๐—ผ๐—ป: Utilizing Netron for graphical model summaries. • ๐—š๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐˜ƒ๐—ฒ ๐—”๐—œ: Complete library for execution, fine-tuning, and RAG setup for ๐—Ÿ๐—น๐—ฎ๐—บ๐—ฎ ๐Ÿฏ and ๐—ฃ๐—ต๐—ถ ๐Ÿฏ models, among others. • For Generative AI, we will support execution, fine-tuning, and RAG setups locally (not in the cloud), ensuring efficient and secure operations directly on your machines. • ๐‘๐ž๐ข๐ง๐Ÿ๐จ๐ซ๐œ๐ž๐ฆ๐ž๐ง๐ญ ๐‹๐ž๐š๐ซ๐ง๐ข๐ง๐  is finally here! We are introducing a wide range of algorithms including DPG, DQN, DDQN, DDQG, Dual DQN, Dual DDQN, PPO, A2C, A3C, SAC, and TD3, with more to follow in subsequent updates. • All this will be possible with the arrival of SOTA, our new tool for a one-click installation, with configuration guaranteed in less than 3 minutes. • ๐—ฆ๐—ฒ๐—ฟ๐˜ƒ๐—ฒ๐—ฟ ๐—ถ๐—ป๐—ณ๐—ฟ๐—ฎ๐˜€๐˜๐—ฟ๐˜‚๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ: Our new server infrastructure for professional online license management is finally here! Additionally, we are excited about the introduction of the Graiphic Cloud (more details to come). This will enable the sharing of models and environments for Reinforcement Learning. Imagine installing and testing games like Mario, Doom, or Atari in under 2 minutes directly within LabVIEW. • Simultaneously, we are launching a comprehensive ๐—ฎ๐—ป๐—ป๐—ผ๐˜๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐˜๐—ผ๐—ผ๐—น ๐—ณ๐—ผ๐—ฟ ๐—ฐ๐—ผ๐—บ๐—ฝ๐˜‚๐˜๐—ฒ๐—ฟ ๐˜ƒ๐—ถ๐˜€๐—ถ๐—ผ๐—ป like Roboflow. This tool, integrated within the SOTA environment, will allow for image data processing and the fine-tuning of computer vision models for object classification or segmentation. • In summary, we have a lot of work ahead and we are targeting a release for July. • Alright, that's all for now. Back to work to make this happen! And by the way, NI CONNECT was amazing! Incredible announcements, you guys impress us! • Stay tuned and follow us on LinkedIn for the latest updates and news! Follow us on LinkedIn   / graiphic  

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