Empowering Solutions
Singularity
Our collaborative approach with customers drives the development of Singularity, our purpose-built software platform, integrates seamlessly into industrial value chains and addresses production challenges effectively.
Singularity features diverse high and low-level APIs for a flexible, user-friendly experience. Its core harnesses sophisticated proprietary algorithms, combining quantum and quantum-inspired computing to effectively address complex AI and optimization challenges with precision.
Witness Singularity in Action
Using Singularity in...
Production Ready
Enjoy tailored interfaces for user-friendliness and flexible deployment choices, from on-premises to customer VPC integration.
Powerful Core Technology
Leverage specialized algorithms for interpretable Machine Learning, deep learning, and optimization, including quantum-powered proprietary routines that outperform commercial models.
Customer-Centric
Experience demonstrated effectiveness across diverse real use-cases, while diving deeper into sections like "Users," "AI," and "Green Impact" for additional insights.
Faster, Cheaper, More Efficient AI
Revolutionizing Deep Learning Costs with Tensor Networks
The landscape of deep learning is undergoing a seismic shift, marked by escalating computational costs. Recent rounds of training for Large Language Models (LLMs) reached staggering costs of $100M, with this expense doubling every 10 months. Projections point to the necessity of a technological paradigm shift to continue adequately training AI models, contingent upon having sufficient training data.
Empowering Accelerated Training with Tensorized AI
Singularity leverages Tensor Networks to revolutionize this scenario. Our tensorized models showcase accelerated training, decreased data requirements, and reduced power consumption. Achieving accelerations exceeding 1000x, this innovation disrupts high-power applications such as machine vision and Large Language Models. It's a game-changer for technologies at the edge, rendering tensorized AI indispensable for autonomous vehicles. Notably, Multiverse Computing is recognized as one of the top 100 most promising AI companies globally in 2023 by CB Insights.
Interpretable ML
Unveiling Clarity: Addressing AI's Opacity Challenge
A pervasive challenge in the AI landscape is the opacity of many machine learning (ML) models. Often, these models function as enigmatic black boxes, lacking industrial relevance in numerous contexts. Singularity steps in to provide clarity by addressing crucial questions: What is the confidence level in our predictions? What underpins a particular decision? How does a change in circumstances impact predictions?
Empowering Transparency in Mission-Critical Applications
The significance of these answers cannot be overstated, particularly in mission-critical applications where transparency is essential. Singularity's commitment to interpretable ML empowers industries to leverage AI with confidence.
Faster, More Accurate Optimization
Navigating Complex Optimization Challenges
Optimization quandaries underscore the heart of various sectors, yet solving them often proves elusive. These challenges translate into inefficiencies across industrial and financial operations. The predicament is especially poignant in the realm of Green Energy, where a transition hinges on more precise and swifter optimization solutions for electrical distribution.
Revolutionizing Optimization with Concealed Data Structures
Singularity takes a revolutionary approach, harnessing concealed data structures to converge quicker than prevailing algorithms. This disruptive potential has far-reaching implications, especially in time-sensitive optimization problems involving numerous variables.
Under the hood
Quantum Methods
In-House Quantum Algorithms
Multiverse Computing develops proprietary algorithms that utilize current quantum platforms, particularly for complex optimization tasks and interpretable machine learning.
Hardware-Agnostic Approach
Recognizing the diversity of quantum hardware platforms (superconducting, photonic, neutral atoms, ion traps, etc.), Multiverse Computing remains hardware-agnostic. Major quantum hardware manufacturers have partnered with Multiverse Computing.
Strategic Deployment of Quantum Solutions
While long-term quantum computing power is promising, its immediate application is limited. Multiverse Computing emphasizes the importance of strategically deploying quantum solutions for tangible economic value, avoiding purely exploratory applications.
Expertise in Quantum Solution Deployment
Multiverse Computing possesses the expertise to guide the deployment of quantum solutions effectively, ensuring they outperform current alternatives and offer real value to customers.
Quantum-Inspired Methods Tensor Networks
Classical Quantum-Inspired Approaches
Quantum-inspired methods, such as Tensor Networks, are employed on non-quantum computers (FPGAs, laptops, Supercomputers). These methods are designed based on insights from how quantum computers manipulate information.
Diverse Quantum-Inspired Approaches
Various families of quantum-inspired computing exist, including Tensor Networks, Digital Annealing, Parallel Tempering, Population Annealing, and Quantum-Inspired Monte Carlo.
Power of Tensor Networks
Multiverse Computing employs Tensor Networks as the most powerful, rapid, and challenging-to-implement quantum-inspired approach. Not to be confused with Tensor Flow, Tensor Networks are renowned as the world's fastest classical algorithms.
Role in Quantum Supremacy Validation
Tensor Networks serve as a benchmark for assessing quantum supremacy. They are pivotal in determining if a quantum computer has achieved superior computational capabilities over classical computers.
Accelerating AI and Optimization
Multiverse Computing leverages Tensor Networks to significantly accelerate AI and optimization tasks, achieving more than a 1000-fold speedup.
Versatile Deployment
Tensor Networks excel in scenarios without cloud connectivity, such as factories, satellites, and defense battlefields.
CSO Expertise
Multiverse Computing's Chief Science Officer (CSO) is a founding figure in the realm of Tensor Networks. Mastery in these methods is rare, and Multiverse Computing is well-equipped to provide both success stories and lessons from challenges encountered in this field.