Instontech
Application

Generative AI and Optimization Algorithms

InstonTech's TRNG provides the randomness required for creating high-quality, diverse data sets, essential for training and enhancing AI models. For optimization algorithms, which often rely on stochastic processes and random sampling, our VC-MRAM based TRNG delivers the high-quality randomness needed to improve algorithm performance and accuracy. Its high-speed and low-energy characteristics ensure efficient operation in demanding AI environments.


InstonTech's TRNG provides the randomness required for creating high-quality, diverse data sets, essential for training and enhancing AI models. For optimization algorithms, which often rely on stochastic processes and random sampling, our VC-MRAM based TRNG delivers the high-quality randomness needed to improve algorithm performance and accuracy. Its high-speed and low-energy characteristics ensure efficient operation in demanding AI environments.


Core Advantages:
High Speed: Enables rapid generation of random numbers, facilitating efficient and real-time data generation for AI training.
Low Energy: Minimizes power consumption, crucial for high-performance AI systems running complex models.
High Throughput: Supports the generation of large volumes of random data with up to 400 Mbps, essential for generative AI Tasks and optimization algorithms.