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What is SigmaXL?

SigmaXL was designed from the outset to be a cost-effective, robust, and user-friendly tool that empowers users to assess, analyze, and enhance their service, transactional, and manufacturing operations. This versatile software can either be integrated as an add-in for Microsoft Excel or utilized for Lean Six Sigma training purposes. The latest version, 9, offers sophisticated features such as advanced control charts and time series forecasting. Among its many capabilities, SigmaXL provides automatic removal of extreme Variance Inflation Factor (VIF) and collinear terms, complete with an alias or removal report. Users can define interactions and quadratic orders, accommodating all interactions and up to three-way interactions. It also supports ANOVA Type I and/or III Sum-of-Squares, along with Pareto analysis of percent contributions and standardized effects. Additionally, it calculates Lenth Pseudo Standard Error in saturated models, both orthogonal and non-orthogonal, while offering options for Monte Carlo P-Values or Student T P values. Moreover, SigmaXL includes White robust standard errors to address non-constant variance, ensuring reliability in statistical analyses. With such a comprehensive suite of features, SigmaXL stands out as an essential tool for professionals aiming to optimize their processes effectively.

What is PanGu-Σ?

Recent advancements in natural language processing, understanding, and generation have largely stemmed from the evolution of large language models. This study introduces a system that utilizes Ascend 910 AI processors alongside the MindSpore framework to train a language model that surpasses one trillion parameters, achieving a total of 1.085 trillion, designated as PanGu-{\Sigma}. This model builds upon the foundation laid by PanGu-{\alpha} by transforming the traditional dense Transformer architecture into a sparse configuration via a technique called Random Routed Experts (RRE). By leveraging an extensive dataset comprising 329 billion tokens, the model was successfully trained with a method known as Expert Computation and Storage Separation (ECSS), which led to an impressive 6.3-fold increase in training throughput through the application of heterogeneous computing. Experimental results revealed that PanGu-{\Sigma} sets a new standard in zero-shot learning for various downstream tasks in Chinese NLP, highlighting its significant potential for progressing the field. This breakthrough not only represents a considerable enhancement in the capabilities of language models but also underscores the importance of creative training methodologies and structural innovations in shaping future developments. As such, this research paves the way for further exploration into improving language model efficiency and effectiveness.

Media

Media

No images available

Integrations Supported

PanGu Chat

Integrations Supported

PanGu Chat

API Availability

Has API

API Availability

Has API

Pricing Information

$249.00/one-time/user
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

SigmaXL

Date Founded

1998

Company Location

Canada

Company Website

www.sigmaxl.com

Company Facts

Organization Name

Huawei

Date Founded

1987

Company Location

China

Company Website

huawei.com

Categories and Features

SPC

Corrective Actions (CAPA)
Data Entry
Data Linking
Data Management
Excel Loader
Job Management
OPC Data Collection
Performance Metrics
Point-of-Production Analysis
Real Time Data Collection
Regulatory Compliance

Categories and Features

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