Generative AI is poised to revolutionize our daily lives, transforming how we live, play, work, and innovate. However, the journey to fully unlocking the potential of the world’s datasets through generative AI is fraught with significant technical challenges.
MediaTek stands at the forefront, addressing these obstacles head-on with cutting-edge solutions.
In this infographic, discover how MediaTek is leading the charge in overcoming the hurdles of generative AI. From reducing computational resource demands and power consumption to solving connectivity and latency issues, and ensuring robust data privacy, MediaTek’s advancements are pivotal. Central to these solutions is the adoption of edge processing, leveraging MediaTek’s Neural Processing Units (NPUs) specifically designed for generative AI applications.
1. Massive Computational Resources
Creating original content from vast data repositories demands immense computing power. For example, the development of OpenAI’s ChatGPT-3 reportedly consumed an astonishing 800 petaflops, highlighting a significant barrier to the widespread adoption of generative AI.
MediaTek’s Solution: Rather than depending on resource-intensive server-grade Large Language Models (LLMs) for every query, MediaTek proposes optimizing LLMs for smartphones. By employing smaller, more efficient models (such as 7B/8B) capable of handling common user requests, computational needs are drastically reduced. This approach is projected to use only a fraction of the energy required to operate a ChatGPT-3-like application, making generative AI more accessible and sustainable.
2. Power Consumption
The energy demands of generative AI are substantial, presenting a considerable barrier to its development and deployment.
MediaTek’s Solution: Utilizing generative AI on smartphones, particularly those powered by MediaTek’s 7th Generation NPU, offers a more energy-efficient and sustainable alternative. These advanced chips deliver significant energy savings and remarkable speed enhancements, with power efficiency 27 times greater than a typical CPU and 15 times greater than a typical GPU.
3. Connectivity and Latency
Real-time generative AI applications, such as virtual assistants or video game characters, often encounter connectivity and latency issues, which can cause lag or disrupt the user experience entirely.
MediaTek’s Solution: MediaTek envisions a future where more generative AI applications are processed directly on the device, reducing reliance on cloud services and the inconsistencies of internet connectivity. This approach not only enhances user experience but also ensures smoother and more reliable AI interactions.
4. Data Privacy
When generative AI models are hosted in the cloud, user content may be accessible to service providers. Users might unknowingly upload sensitive personal data, like medical information, or corporate data, such as proprietary datasets.
MediaTek’s Solution: MediaTek’s edge AI technology prioritizes data privacy by keeping sensitive information on the device. This eliminates the need to upload data to cloud services, significantly reducing the risk of unauthorized access and ensuring that personal and corporate data remain secure.
By addressing these critical challenges with innovative solutions such as MediaTek’s NPUs and edge computing, we can accelerate the development and adoption of generative AI. MediaTek’s efforts ensure sustainability, efficiency, and robust data security, unlocking the full potential of generative AI for a transformative future.
