The development of multimodal AI assistants is on the rise, leveraging Large Language Models (LLMs) for understanding visual and written directions. While current models focus on image-text data, a study from Peking University and Kuaishou Technology introduces Video-LaVIT, a novel method for pretraining LLMs to understand and generate video content more effectively. This promising approach outperforms existing methods in various tasks.
“`html
Introducing Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization
There has been a recent surge in the development of general-purpose multimodal AI assistants capable of following visual and written directions, thanks to the success of Large Language Models (LLMs). These AI assistants demonstrate immense potential for effectively understanding and creating visual content. However, adaptation for video modality is underexplored in these multimodal LLMs.
Practical Solutions and Value:
A new study by Peking University and Kuaishou Technology has investigated a time-saving video representation that breaks down video into keyframes and temporal motions, overcoming the shortcomings of video-language pretraining. This approach has led to the introduction of Video-LaVIT (Language-VIsion Transformer), a novel multimodal pretraining method that equips LLMs to understand and produce video material within a cohesive framework.
Video-LaVIT has two main components to manage video modalities: a tokenizer and a detokenizer. By employing an established image tokenizer to process the keyframes, the video tokenizer attempts to convert the continuous video data into a sequence of compact discrete tokens. This greatly improves LLMs’ capacity to understand complex video actions by capturing the time-varying contextual information in retrieved motion vectors.
Results from extensive quantitative and qualitative tests show that Video-LaVIT outperforms the competition in various tasks, including text-to-video and picture-to-video production, video and image understanding, and more.
Evolve Your Company with AI
If you want to evolve your company with AI, stay competitive, and use AI to your advantage, consider implementing Video-LaVIT. AI can redefine your way of work by automating customer engagement, managing interactions across all customer journey stages, and redefining your sales processes.
Practical AI Solution: AI Sales Bot
Consider the AI Sales Bot from itinai.com/aisalesbot designed to automate customer engagement 24/7 and manage interactions across all customer journey stages.
AI Implementation Tips:
- Identify Automation Opportunities: Locate key customer interaction points that can benefit from AI.
- Define KPIs: Ensure your AI endeavors have measurable impacts on business outcomes.
- Select an AI Solution: Choose tools that align with your needs and provide customization.
- Implement Gradually: Start with a pilot, gather data, and expand AI usage judiciously.
For AI KPI management advice, connect with us at hello@itinai.com. And for continuous insights into leveraging AI, stay tuned on our Telegram t.me/itinainews or Twitter @itinaicom.
“`
