Perplexity Computer to Introduce Task Splitting Between Local and Cloud AI Models
Perplexity Computer adding ability to split tasks between local and cloud models

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Perplexity is set to enhance its AI system, Perplexity Computer, with a new feature that allows for the automatic splitting of tasks between local and cloud-based AI models. This hybrid approach aims to manage sensitive data securely while leveraging powerful server capabilities as needed.
- 01The new feature will enable Perplexity Computer to switch between local AI models and more powerful server-based models.
- 02This hybrid approach is designed for tasks involving sensitive data, such as financial records and health information.
- 03The compact model will run locally to determine when to keep data on-device, while more demanding tasks will utilize server capabilities.
- 04Unlike existing tools that require users to choose between local or cloud processing upfront, this system will automatically manage tasks on a case-by-case basis.
- 05The hybrid AI orchestration feature is expected to be available in July.
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Perplexity has unveiled a significant upcoming feature for its AI system, Perplexity Computer, which will allow users to split tasks between local and cloud-based AI models. This innovative hybrid approach aims to combine the security of local processing with the power of server-based AI for various tasks. The feature is particularly beneficial for handling sensitive information, such as financial records and health data, by ensuring that such data is processed locally when necessary. The compact model running on the device will intelligently determine when to keep data local, while more complex tasks will leverage the capabilities of server-based models. Unlike traditional systems that require users to make a choice between local or cloud processing beforehand, Perplexity Computer will manage this automatically, optimizing performance based on the specific requirements of each task. This hybrid AI orchestration feature is anticipated to be rolled out in July, marking a significant advancement in AI task management.
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The introduction of this feature could significantly enhance data security for users handling sensitive information.
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