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Oasis by Decart-AI驱动的互动开放世界平台

Oasis by Decart是一个实时生成开放世界环境的AI互动平台,为沉浸式游戏体验提供支持。用户可以创建账号后,探索和互动动态生成的虚拟世界。

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Oasis by Decart是一个实时生成开放世界环境的AI互动平台,为沉浸式游戏体验提供支持。用户可以创建账号后,探索和互动动态生成的虚拟世界。

Oasis by Decart的特点:

  • 1. 实时生成虚拟环境
  • 2. 沉浸式游戏体验
  • 3. 动态适应玩家选择的故事情节
  • 4. 广阔的自定义空间

Oasis by Decart的功能:

  • 1. 创建账号后探索虚拟世界
  • 2. 像Minecraft一样定制和探索广阔的虚拟环境
  • 3. 参与根据玩家选择变化的独特故事体验

相关导航

name: “Implicit Object Tracking and Shape Reconstruction” description: “Online Adaptation for Implicit Object Tracking and Shape Reconstruction in the Wild” url: “github.com/jianglongye/implicit-tracking” features:   – “Implicit object tracking”   – “Shape reconstruction in dynamic environments” usage:   – “Real-time object tracking in videos”   – “Reconstructing 3D shapes from 2D images”  name: “Tracr” description: “Compiled Transformers as a Laboratory for Interpretability” url: “github.com/deepmind/tracr” features:   – “Transformers compilation for enhanced interpretability”   – “Experimental framework for AI model analysis” usage:   – “Analyzing transformer models’ behavior”   – “Testing interpretability of AI systems”  name: “VALL-E” description: “Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers” url: “github.com/enhuiz/vall-e” features:   – “Zero-shot text-to-speech synthesis”   – “High-quality voice generation from text” usage:   – “Generating speech from written content”   – “Creating voiceovers for videos”  name: “FLYP” description: “Finetune like you pretrain: Improved finetuning of zero-shot vision models” url: “github.com/locuslab/FLYP” features:   – “Improved finetuning techniques for vision models”   – “Zero-shot learning capabilities” usage:   – “Applying pre-trained models to new tasks”   – “Enhancing performance on vision-related applications”-改进的零-shot视觉模型微调
name: “Implicit Object Tracking and Shape Reconstruction” description: “Online Adaptation for Implicit Object Tracking and Shape Reconstruction in the Wild” url: “github.com/jianglongye/implicit-tracking” features:   – “Implicit object tracking”   – “Shape reconstruction in dynamic environments” usage:   – “Real-time object tracking in videos”   – “Reconstructing 3D shapes from 2D images”  name: “Tracr” description: “Compiled Transformers as a Laboratory for Interpretability” url: “github.com/deepmind/tracr” features:   – “Transformers compilation for enhanced interpretability”   – “Experimental framework for AI model analysis” usage:   – “Analyzing transformer models’ behavior”   – “Testing interpretability of AI systems”  name: “VALL-E” description: “Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers” url: “github.com/enhuiz/vall-e” features:   – “Zero-shot text-to-speech synthesis”   – “High-quality voice generation from text” usage:   – “Generating speech from written content”   – “Creating voiceovers for videos”  name: “FLYP” description: “Finetune like you pretrain: Improved finetuning of zero-shot vision models” url: “github.com/locuslab/FLYP” features:   – “Improved finetuning techniques for vision models”   – “Zero-shot learning capabilities” usage:   – “Applying pre-trained models to new tasks”   – “Enhancing performance on vision-related applications”-改进的零-shot视觉模型微调
Nname: “Implicit Object Tracking and Shape Reconstruction” description: “Online Adaptation for Implicit Object Tracking and Shape Reconstruction in the Wild” url: “github.com/jianglongye/implicit-tracking” features: – “Implicit object tracking” – “Shape reconstruction in dynamic environments” usage: – “Real-time object tracking in videos” – “Reconstructing 3D shapes from 2D images” name: “Tracr” description: “Compiled Transformers as a Laboratory for Interpretability” url: “github.com/deepmind/tracr” features: – “Transformers compilation for enhanced interpretability” – “Experimental framework for AI model analysis” usage: – “Analyzing transformer models’ behavior” – “Testing interpretability of AI systems” name: “VALL-E” description: “Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers” url: “github.com/enhuiz/vall-e” features: – “Zero-shot text-to-speech synthesis” – “High-quality voice generation from text” usage: – “Generating speech from written content” – “Creating voiceovers for videos” name: “FLYP” description: “Finetune like you pretrain: Improved finetuning of zero-shot vision models” url: “github.com/locuslab/FLYP” features: – “Improved finetuning techniques for vision models” – “Zero-shot learning capabilities” usage: – “Applying pre-trained models to new tasks” – “Enhancing performance on vision-related applications”-改进的零-shot视觉模型微调

通过改进的微调技术,提升零-shot视觉模型的性能,适用于将预训练模型应用于新任务。

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