Product Descriptions
Singularity is a software platform developed in collaboration with customers, seamlessly integrated into the production chain to effectively solve challenges on the production site. It offers flexible and user-friendly experiences through high-level and low-level APIs, and uses proprietary algorithms to precisely handle complex AI and optimization problems in quantum and quantum-inspired computing.
Unleashing the Potential of Singularity
Powerful: Production-Ready
From on-premises to customer VPC integration,
enjoy a user-friendly, customizable interface and
flexible deployment options.
Deployable: Powerful Core Technology
Use specialized algorithms for interpretable machine learning, deep learning, and optimization.
This includes proprietary routines that surpass commercial models.
Intuitive: Customer-Centric
Experience proven effects in various real-world use cases,
explore sections like "User", "AI",
"Green Impact" and more.
Faster, Cheaper, and More Efficient AI
The environment of deep learning is undergoing a significant change due to the rapid increase in computational costs. The recent learning cost of large language models (LLM) has reached $100 million, and this cost is increasing by two times every 10 months. It is expected that in order to properly train AI models under the condition of sufficient learning data, there is a need for a paradigm shift in technology.
Singularity leverages tensor networks to innovate this scenario. Our tensorized models demonstrate accelerated learning, reduced data requirements, and reduced power consumption. Achieving over 1000x acceleration, they revolutionize high-power applications like machine vision and large language models.
This makes tensorized AI essential for edge technology, playing a crucial role in autonomous driving. Notably, Multiverse Computing was recognized as one of the top 100 AI companies in the world by CB Insights in 2023.
Explainable Machine Learning
A pervasive issue in the AI domain is the lack of transparency in many machine learning (ML) models. Often, these models operate as enigmatic black boxes with little relevance to industrial applications.
Singularity provides clarity by answering key questions:
- To what extent can we trust our predictions?
- What is the rationale behind specific decisions?
- How do changes in circumstances affect the predictions?
- To what extent can we trust our predictions?
- What is the rationale behind specific decisions?
- How do changes in circumstances affect the predictions?
The importance of these answers cannot be overstated, especially in mission-critical applications where transparency is essential.
By ensuring explainable machine learning, Singularity enables industries to trust and effectively leverage AI.
Faster, More Accurate Optimization
Optimization problems are at the core of various sectors, yet solving them is often challenging. These challenges can lead to inefficiencies across industrial and financial operations. In the green energy sector in particular, more precise and rapid optimization solutions for power distribution are key to driving change.
Singularity adopts an innovative approach that leverages hidden data structures to converge faster than traditional algorithms.
This disruptive potential has far-reaching implications, especially in time-sensitive optimization problems involving numerous variables.
Singularity by Multiverse Computing Solutions
Finance
Deep Pricing
Use deep learning models trained with quantum inspired and other cutting-edge methods to obtain parametric tools for exotic derivative contracts, such as the fair value, sensitivity, and other indicators.
Life Science
Molecular Simulation
Use tensor network algorithms to find the ground state energy of a given molecule or quantum Hamiltonians for various physical systems, such as spin, boson, and fermion systems.
Finance
Fair Pricing
Use ultra-fast quantum inspired methods to evaluate the fair price of an asset portfolio based on given market information and trends.
Life Science
Predicting Player Injuries
Use quantum machine learning to predict the likelihood of short-term injuries based on training volume, game time, and rest.
Finance
Index Tracking
Determine the optimal portfolio allocation to track the performance of financial indices while limiting the number of managed assets.
Life Science
Protein Design
Obtain the 3D protein structure for a given amino acid sequence.
Finance
Portfolio Optimization
Use Python and Excel packages to obtain the optimal portfolio allocation that maximizes returns while minimizing risk, while adhering to the investor's customized preferences and customizable constraints.
Finance
Trading
Use a quantum machine learning model trained on past FX trends to apply it in real-time to obtain real-time intraday trading signals.