Why should we use Hybrid AI?

Hybrid AI is transforming the AI landscape and enabling businesses of all sizes to leverage AI's power through various ways:

Combining Cloud and Edge Processing

Hybrid AI systems that leverage both cloud and edge processing are making AI more accessible and efficient. This approach allows organizations to:

• Process AI tasks on edge devices, enabling data privacy and protection.
• Use confidential data without worries, as it is processed locally.
• Utilize cloud resources for more complex computations and model training.
• Opt to use the cloud to process AI tasks instead- especially when they require the additional computing power for more complex outputs, this however does risk data privacy as the data is shared to a cloud server.
• Optimize costs by balancing workloads between edge devices and cloud infrastructure.

This flexibility enables smaller organizations to implement AI solutions without investing heavily in expensive hardware or infrastructure.

Cost-Effective AI Implementation

Hybrid AI approaches are making AI implementation more cost-effective:

• By leveraging edge processing, organizations can reduce data transmission costs and cloud computing expenses.
• This makes AI adoption feasible for smaller companies with limited budgets.
• Win-win: Edge processing also enables companies to be more sustainable, as cloud computing requires a chunk of energy and water (via the data centres)
• Processing can be split between the edge and cloud, depending on the user's needs.

Evolving AI Ecosystem

The trend towards hybrid AI and democratization is creating a more diverse and innovative AI ecosystem:

• It's shifting the focus from building ever more sophisticated ML models to improving data quality and accessibility.
• This change is enabling a wider range of organizations to participate in and benefit from AI advancements.

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Hybrid AI approaches combine cloud and edge processing, offering user-friendly platforms, automating complex tasks, and making advanced analytics accessible, and enabling users to keep their data private when necessary through edge processing.

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Here at Opilot, we want to enable people and companies to take back control of their data and their AI models. People should be able to use AI models that align with their needs, culture and values. If this resonates with you, please feel free to try Opilot, your seamless and secure copilot Here.

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