🤔Problem Statement

Current State of AI: Key Challenges

Centralization

• AI systems currently depend on centralized data storage solutions that create:

• High vulnerability to system-wide failures

• Increased risk of massive data breaches

• Single points of failure that can disrupt entire operations

• Attractive targets for cyber attacks

• Greater exposure to security threats

Data Privacy

• Organizations struggle with data protection and transparency:

• Complex compliance requirements with GDPR and other regulations

• Difficulty maintaining clear data usage transparency

• Limited user control over personal data

• Challenges in tracking how data is processed and used

• Balancing data access needs with privacy protection

Scalability Issues

• Current centralized systems face growing performance challenges:

• Inability to efficiently handle increasing data volumes

• Significant processing slowdowns with larger datasets

• Rising operational costs for data management

• Performance bottlenecks in data processing

• Expensive infrastructure scaling requirements

Limited Access

• Smaller organizations face significant barriers:

• Restricted access to high-quality training data

• Limited availability of advanced AI tools

• High cost barriers to entry

• Reduced ability to innovate independently

• Concentration of resources among large players

Impact

• These challenges result in:

• Reduced innovation in the AI field

• Limited diversity in AI development

• Increased costs for AI implementation

• Higher barriers to entry for new players

• Slower advancement of AI technology