Self-certifying QRNGs for
AI & Machine Learning
Verifiably high-quality random numbers are essential for stochastic modelling techniques like Monte Carlo simulations, which are critical for training algorithms, optimising models, and driving breakthroughs in data-driven decision-making.
Current RNG solutions used in AI & Machine Learning
Quantum Dice's DISC™ protected QRNG
- High speed, but at the detriment of randomness quality
- High speeds of up to 7.5 Gbps
- Exhibit patterns and biases over time
- Negligible bias
- Pseudo-randomness
- Continuous randomness verification for quantum assurance
Application areas
Where are QRNGs used in AI & machine learning?
QRNGs for enhanced simulations
Providing reliably high-quality random numbers to enhance stochastic modelling and statistical simulations, such as Monte Carlo simulations.
Quantum Entropy Solution THE BENEFITS
Simulations
Improved accuracy
More accurate estimates and predictions means organisations can make better-informed decisions.
SHORTER SIMULATION TIME
A substantial reduction in computing steps leads to cost, time and energy savings.
Testimonials
“HSBC has been exploring how quantum technologies could impact real business applications today. We are working with Quantum Dice to address whether quantum random number generators can enhance Monte Carlo simulations. These are important tasks in financial services with applications such as computing risk analytics and pricing complex derivatives. Our joint work with Quantum Dice started under an Innovate UK grant, and we are now pleased to move forward with a planned commercial PoC.”
Philip Intallura, Global Head of Quantum Technologies at HSBC
Solutions for AI & machine learning
