Desktop AI Model Production System Using Local Resource Invocation

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Solution Overview

Problem

Current AI model production methods face challenges such as data privacy concerns, network dependence, lack of universality and expandability, high costs, and delayed updates due to cloud-based solutions, and limitations in data and hardware requirements for desktop and private cloud deployments.

Innovation Solution

A desktop AI model production system utilizing a cross-platform framework with a user interface layer, API layer, and stand-alone engine layer that allows for local resource-based model service invocation, enabling flexible data processing, training, optimization, and deployment across different operating systems, and supporting various model services without the need for extensive hardware or network connectivity.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If cloud-based AI model production is used, then model production capability is improved, but data privacy is compromised and network dependence increases

Engineering Contradiction:

Improvemodel production capabilityVSAvoiddata privacy risk

Core Design Contradiction:

ProductivityVSObject-affected harmful factors

Solution Approach 1:

The patent extracts the AI model production capability from cloud-based environments and embeds it into a local desktop system. The core engine layer containing model training, optimization, and deployment functions is packaged as a standalone executable that runs locally on user devices, eliminating the need for cloud connectivity while maintaining full model production capability.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent introduces a cross-platform framework as an intermediary layer between the user interface and the core engine. This framework enables the system to run locally on different operating systems without requiring cloud infrastructure, serving as a mediator that brings cloud-equivalent functionality to the local environment while preserving data privacy.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If cloud-based AI model production is used, then model production capability is improved, but network dependence increases

Engineering Contradiction:

Improvemodel production capabilityVSAvoidnetwork independence

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system extracts all network-dependent functionalities from the model production process and consolidates them into local components. The desktop AI system performs data processing, model training, optimization, and deployment entirely offline, making the system reliable without network connectivity.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The local desktop system is designed to be self-sufficient, with all model production operations executed locally without requiring external network services. The system manages its own resources, processes data locally, and deploys models independently, eliminating network dependence while maintaining productivity.

Inventive Principle:

Principle #25Self-service

3Object-affected harmful factors

If desktop AI system is used, then data privacy is protected, but hardware requirements and system complexity increase

Engineering Contradiction:

Improvedata privacy protectionVSAvoidsystem complexity

Core Design Contradiction:

Object-affected harmful factorsVSDevice complexity

Solution Approach 1:

The patent segments the AI system into three distinct layers: user interface layer, core engine layer, and cross-platform framework. This modular architecture separates concerns, making the system easier to manage and deploy despite its capabilities. Each layer is independently packaged and can be updated separately, reducing the complexity burden of having full model production capability locally.

Inventive Principle:

Principle #1Segmentation

4Speed

If cloud-based solutions are used, then update speed is improved, but data privacy and control are compromised

Engineering Contradiction:

Improveupdate speedVSAvoiddata privacy risk

Core Design Contradiction:

SpeedVSObject-affected harmful factors

Solution Approach 1:

The local desktop system enables organizations to manage their own model updates independently. Users can download updated model versions or optimization algorithms from official sources and deploy them locally without requiring cloud connectivity for each update operation. This self-service update mechanism maintains data privacy while providing timely model improvements.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12182546B2Method and system for model production

Publication Date: 2024.12.31 BEIJING BAIDU NETCOM SCI & TECH CO LTD

AI summary

A method for model production includes acquiring a related operation for model production from a user interface layer of a model production system, and determining a software platform of the model production system; acquiring a model service corresponding to the related operation by invoking an application programming interface (API) corresponding to the related operation, wherein the API is located between the user interface layer and other layer in the model production system; performing the model service by invoking local resources of the software platform with a tool of the software platform adapted to the model service, to generate a target model; and applying the target model in a target usage scene.