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Spend just 1 minute daily to get comprehensive updates on AI technology developments, industry trends, and market insights.

The content includes but is not limited to cutting-edge AI news, AI tools, AI painting, open-source projects, and learning tutorials.

Stay tuned to AI Daily for the latest in AI trends. For important information, detailed posts will be made separately.

Here is the latest AI information for July 6.

Cutting-edge News ​

1. Kuaishou Kuaishou AI web version and new features launched, free trial!

Provides text-to-image and text-to-video (up to 3 minutes) functions, with video editing features coming soon.

Key point: All features are free for a limited time, AI video requires application. Hurry up and try it~

Experience link: https://klingai.kuaishou.com/

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2. Kuaishou also open-sourced its text-to-image model Kolors today.

Trained on billions of image-text pairs, it supports bilingual prompts in both Chinese and English, with a competitive edge in understanding Chinese-specific content.

GitHub: https://github.com/Kwai-Kolors/Kolors

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3. Stability AI updated the open-source license for SD3!

As long as annual revenue does not exceed $1 million, Stability AI models can be used for free for research and commercial purposes.

Announcement: https://stability.ai/news/license-update

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Cutting-edge Technology ​

1. Alibaba's Tongyi team open-sourced the speech recognition model and speech synthesis model FunAudioLLM.

They are:

  • SenseVoice: Speech recognition model (ASR)
  • CosyVoice: Speech synthesis model (TTS)

Both models are of very high quality. SenseVoice outperforms Whisper in terms of speed and accuracy for Mandarin and Cantonese recognition.

Detailed introduction: https://fun-audio-llm.github.io/

CosyVoice experience: https://www.modelscope.cn/studios/iic/CosyVoice-300M

SenseVoice experience: https://www.modelscope.cn/studios/iic/SenseVoice

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Open-source Projects ​

1. A powerful framework for building multi-agent systems: llama-agents.

Aims to simplify the process of building, iterating, and deploying multi-agent AI systems, providing strong support for creating various AI application scenarios.

Easily develop complex Q&A systems, collaborative AI assistants, and distributed AI systems.

GitHub: https://github.com/run-llama/llama-agents

Detailed introduction: https://www.llamaindex.ai/blog/introducing-llama-agents-a-powerful-framework-for-building-production-multi-agent-ai-systems

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Learning Books ​

1. An open-source book from MIT: "Understanding Deep Learning".

Covers various aspects of deep learning from basics to advanced topics, such as basic concepts, supervised learning, reinforcement learning, linear regression, neural networks, diffusion models, and more.

Very comprehensive content, with PPTs and notes for each chapter, as well as 68 Python exercise demos for practice.

GitHub: https://github.com/udlbook/udlbook

Through the following link, you can easily download the book PDF, PPTs, and practice demos.

Link: https://udlbook.github.io/udlbook/

Understanding Deep Learning