How do they update AI models?

Updating AI models involves several steps, often tailored to the specific needs of the model and its application. Here are key aspects based on expert discussions:

1. Model Fine-Tuning and Versioning: Models may be fine-tuned or upgraded to enhance performance and address specific tasks better. For example, Stability AI upgraded its video model to SVD 1.1, enhancing motion and consistency in videos. This model updates involve optimizing existing frameworks to generate more consistent and photorealistic effects 1.

2. Introducing New Features: Major updates often include introducing new capabilities or integrating the model with additional services. For instance, Google has continuously updated its AI models, adding new features like advanced reasoning tasks, multilingual proficiency, and embedding AI capabilities into broader product ranges, such as spreadsheet tools, email, and document processing 2.

3. Access and Deployment: Updates may also relate to how models are accessed and deployed by users. For example, the availability of models could be widened, or access might be streamlined to involve less wait time or ease of integration with other technologies 3.

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     1

     Upgraded AI Video Model

     00:02:37
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     2

     Google's AI Updates

     00:02:39
     
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     3

     LLM Updates

     00:03:08
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     4

     AI Regulation Update

     00:46:50
     

4. Regulatory Compliance: Updates can be regulatory-driven, requiring model builders to disclose details about training methods or conform to new privacy standards, affecting how models are updated and maintained 4.

These updates generally aim to improve the efficacy, efficiency, and compliance of AI models with ongoing technological and regulatory changes.