AI Playground 2.0 With Support for Intel Arc B-Series GPUs

We are happy to announce the release of AI Playground 2.0 alpha early preview, now available for download with support for Intel® Arc™ B Series GPUs. This release expands on AI Playground with support for more model formats, increased capabilities, and greater user control for next level content creation using advanced Generative AI workloads, all powered by Intel® Arc™ Graphics.

Download AI Playground: more about downloading and installing AI Playground at this website. Currently this release is in alpha stage. Check the download website for latest updates.

新版人工智能游乐场 2.0

AI Playground 提供了一系列新的解决方案，每种解决方案都扩展了 AI Playground 的功能，并以其模块化架构为基础，在不同版本之间提供价值和功能。

工作流程

在图像生成方面，我们在图像设置中添加了工作流程模式选项。该功能通过整合 ComfyUI 作为图像生成的替代后端引擎来提供图像生成工作流。使用工作流程模式，您可以选择运行已提交到 AI Playground 项目的预定义工作流程。在启动时，我们提供了以下工作流程，让您可以使用更高级别的制作功能和高级图像生成模式

Flux.1-Schnell： 提供了两个使用黑森林实验室 Flux.1-Schnell 模型的工作流程。该模型因其输出质量高、及时性强和支持图像中的文字而广受欢迎，并享有盛誉。 使用该工作流程，您可以指定对象的位置、颜色和纹理，以及最终图像中应出现的单词和短语。我们提供了两种工作流程，一种是中等质量的，另一种是高质量的。高质量版本使用了更高精度的模型，与中等质量的工作流程相比，它可能会带来更高质量的输出，以及文字的粘着性和准确性。

线路转照片 HD： 有两种工作流程可用于控制图像的输出，即图像预视觉化和风格化。 该工作流程允许你通过参考图像的结构和形式来控制图像的外观。其用途是将简单的线条艺术、设计线框或建筑图纸预视觉化为完全实现的摄影图像，通过文本提示，您可以定义图像中的位置、天气、时间和其他元素，同时保留原始图像的结构和组成。 提供两种工作流程。两者都使用 SDXL JuggenautXL 模型来处理高清图像，并使用 Canny ControlNet 模型通过参考图像的结构来控制输出。其中一个还包括一个快速 LCM 模型，类似于默认图像生成中的快速按钮选项。

换脸: 通过该工作流程，您可以使用参考图像样本的相似度来控制文本生成图像的相似度。 只需上传一张参考图像 (所有图像保留在本地电脑中)，输入描述输出图像的提示，然后生成。 最终生成的图像将以您的提示为指导，但与原始图像十分相似。

Workflow Synch: The workflow synch button allows you to download updated or new workflows that have been committed to the public AI Playground repository. These can provide  new capabilities and features between releases. 

ComfyUI Editor: For users interested in diving into ComfyUI workflows, or those already familiar with ComfyUI, we’ve provided direct access to its workflow editor, allowing users to edit or create workflows for use either directly from ComfyUI or in AI Playground. We encourage and welcome the community created workflows submitted and shared to AI Playground via Pull Requests to our project.

GGUF Support

For the Answer section we’ve added an experimental back-end option, using Llama.cpp with GGUF support. This allows users to run GGUF models directly in AI Playground expanding access to models in this format.  When selected, supported GGUF models are pre-populated in the model list. Note this feature has limited features – Retrieval-Augmented Generation (RAG) not currently supported in the alpha release.

Additionally, we’ve included a new Add Model feature.  This allows you to insert HuggingFace Model IDs and specific model paths. After adding these models will appear in your model selector, and download them for use, on first run

Runtime Installer

We’ve updated the installation process, to help make it more reliable, expandable and to assist troubleshooting installation issues.

Installation Manager:  We’ve included an installation manager, allow users to manage the installation state of various pieces of the application. If any portion is missing or needs fixing, it can be reinstalled using the installation manager.

Single Installer: New to 2.0 is a single installer binary, able to install on all supported hardware including: Intel Core Ultra-H Series 1, Intel Core Ultra Series 2, and Intel Arc Series A and B Series GPUs with 8GB+ of vRAM. Note: as an alpha preview, all systems environments may not be fully tested and functional, back up any previous installs before using.

Backend Restart: We’ve conveniently provided backend end restart buttons for each core component via the Backend Installation Manager, in the Basic Settings of AI Playground.  Restarting these backends may improve or restore performance without having to restart AI Playground

UI/UX

Themes: With AI Playground 2.0 we’ve added a new Intel Arc theme and provided a means to dress up your AI Playground experience with any of our themes: the original Dark theme, Intel Core Ultra theme, or the new Intel Arc theme.

Resolution scale:  Resolution settings can be tricky with Generative AI, because you often need to know what resolutions the model supports.  We’ve made this easy with flexibility by adding a resolution scale feature to the Aspect Ratio tool. Now you can set the resolution scale in Megapixels (1 million pixels). And we’ve provided guardrails by setting defaults and boundaries on the resolution you can pick for each image generation mode.  Resolution can be freely set using Manual mode.

All Generative AI Features