The shift towards on-device artificial intelligence is driven by the need for enhanced speed and privacy, particularly for sensitive information such as health and financial data. Developers are increasingly moving AI processing from large corporate data centers to personal devices like smartphones and laptops, which can reduce costs and allow for functionality without an internet connection.
Requests sent to AI systems, such as prompts for Claude AI by Anthropic, involve complex processing that typically occurs in cloud-based data centers. However, tasks requiring quick responses, like obstacle detection, highlight the necessity for faster processing. This is where edge computing becomes crucial, as it enables data handling closer to the user.
Professor Mahadev Satyanarayanan from Carnegie Mellon University has extensively studied edge computing, which focuses on local data processing to enhance efficiency. The evolution of hardware and AI models will significantly influence user experience in future technologies.