SmartTensors AI Software for Big Data Analysis

Your data tells a story that contains clues to future outcomes.

Big-data contains countless stories, but extracting the stories to make future forecasts is challenging for a few reasons. First, traditional data-analysis software uses machine learning capabilities. Also known as supervised learning, this type of ML requires highly structured and labeled data. Data structuring is costly and time consuming.  Supervised learning limits predictive analysis because humans are limited in our ability to capture and organize data in a way that tells the broadest story. 

SmartTensors AI is an unsupervised learning platform that does not require human guidance or labeled data. Instead, SmartTensors can extract, sort, and analyze all-types of data from multiple data sources. It can also make interpretations and give users simple explanations backed by verified data.

Neural networks enhance data-exploration.

SmartTensors AI uses neural networks and tensor technologies to sift through vast amounts of different data. It discovers patterns, trends, and anomalies that humans might miss and that traditional models might not train to find.

SmartTensors is unique because it can find useful correlations, and also negate irrelevant information. LANL researchers explain that SmartTensors is a ground breaking unsupervised machine learning tool based on non-negative tensor factorization. The tools extract easy to explain latent features and analyze large dynamic networks.

 “Extracting the important hidden features in the data helps create a simplified structure that represent, compress, and interpret entire data sets.” said Boian Alexandrov, a Los Alamos Scientist.

SmartTensors AI key features:

• Unsupervised learning: Discover hidden insights without the need for labeled data.
• High-visual data compression: Turn complex data into clear, actionable visuals.
• Explainable AI (XAI): Understand your results in plain language, making informed decisions easier.
• Natural Language Processing (NLP): Interact with your data naturally, asking questions and getting answers.
• Versatile software suite: SmartTensors is written in Julia, Python, and C++, and operates on CPUs, GPUs, supercomputers, and personal laptops.

What are neural networks? 

Neural networks are a powerful tool for unsupervised learning because they can learn complex patterns and relationships within data without requiring explicit labels or supervision. They can handle large, unstructured datasets, which are common in many real-world applications.

Key roles of neural networks in unsupervised learning:

• Feature extraction: Neural networks can automatically learn to extract meaningful features from raw data, which can then be used for further analysis or tasks like clustering or dimensionality reduction.
• Pattern recognition: They can identify patterns and structures within data that may not be obvious to humans, allowing for the discovery of hidden relationships and insights.
• Generative modeling: Neural networks can be used to generate new data that is similar to the original training data, which can be useful for tasks like data augmentation or anomaly detection.

Tensors gather, compress, and simplify big data sets. 

• In simple terms, a tensor is a mathematical tool used to represent and manipulate complex data. It can handle multidimensional information, making it ideal for tasks like analyzing images, videos, and scientific data.

Tensor Networks and Artificial Intelligence:

• Tensor networks are a powerful technique in artificial intelligence that can find patterns and relationships within large, complex datasets.
• SmartTensors is based on non-negative tensor factorization which extracts, compresses, and explains latent features in large dynamic networks. 

By breaking down data into smaller, interconnected components, tensors can:

• Identify relationships: Discover connections between different elements of the data.
• Detect anomalies: Find unusual or unexpected patterns that may indicate problems or opportunities.
• Make predictions: Forecast future trends or outcomes based on past data.
• Understand underlying processes: Gain insights into the fundamental mechanisms driving the data.
•  Simplify complex data: Reduce the dimensionality of data while preserving essential information.

SmartTensors software filters out irrelevant information.

The human brain is incredibly efficient at processing information. It can quickly prioritize what’s important and discard what’s not. For example, when deciding what to eat, our brain focuses on food options rather than irrelevant details like the color of the sky. This ability to filter out noise is essential for making timely and accurate decisions.

Neural networks work in a similar way. By organizing data into specific categories, neural networks can efficiently locate relevant information and ignore the rest. This helps them make predictions and solve complex problems.

SmartTensors classifies anomalies.

Unlike traditional AI systems that can confidently make incorrect predictions, SmartTensors designers created it to be transparent. When it encounters information that it’s unsure about, it will flag it as “unknown.”  Users can manually review and make informed decisions, rather than relying solely on the AI's output.

SmartTensors AI incorporates powerful data-compression features to reduce file sizes by eliminating redundancy and using efficient encoding techniques. This makes storage and transmission more efficient. 

• Explainable AI (XAI) helps in regulated industries.
• Explainable AI can help improve user experience.
• Explainable learning can help improve existing models. 

• Healthcare predictions
• Financial forecasts
• Insurance analysis
• Supply chain management
• Energy grid improvement
• Market Research