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What is Turing?

Turing streamlines and optimizes the creation of consumer packaged goods (CPG) by providing intelligent guidance, eliminating the need for cumbersome manual analyses. This allows teams to transition rapidly from concept to production using one cohesive platform. Many companies squander substantial resources on the relentless gathering and integration of data to formulate accurate models. In contrast, Turing's sophisticated algorithms require significantly less data than conventional machine learning or AI approaches. As a result, teams no longer face the lengthy process of data aggregation. Turing empowers research and development teams to combine data from various systems that typically do not work together, creating a unified platform. By leveraging Turing’s AI, organizations can discover insights and connections that were previously locked away in separate data silos, facilitating the rapid development of high-quality prototypes. With Turing, collaboration becomes effortless across all stages of product development, from the initial idea to the market launch, all within one integrated system. Real-time, data-driven decisions regarding products, packaging, or processes can be made, circumventing the slow and inefficient cycles of physical experimentation. This revolutionary method of product development enhances efficiency and saves time, leading to quicker market entry and superior results. As a result, Turing not only transforms the product development landscape but also positions businesses for greater success in a competitive marketplace.

What is MPCPy?

MPCPy is a Python-based library specifically created to facilitate the testing and implementation of occupant-integrated model predictive control (MPC) in building systems. This innovative tool focuses on utilizing data-driven, simplified physical or statistical models to predict the performance of buildings and improve control methodologies. It consists of four key modules that offer object classes for tasks such as data importation, engagement with either real or simulated systems, estimation and validation of data-driven models, and optimization of control inputs. While MPCPy acts as a comprehensive integration platform, it relies on a variety of free, open-source third-party software for executing models, conducting simulations, implementing parameter estimation techniques, and optimizing solvers. This includes Python libraries for scripting and data manipulation, as well as specialized software solutions designed for specific functions. Importantly, the tasks involving modeling and optimization of physical systems are currently based on the requirements of the Modelica language, which significantly enhances the package's flexibility and capabilities. Overall, MPCPy empowers users to harness sophisticated modeling methods within a dynamic and cooperative environment, ultimately fostering improved building system performance. Furthermore, it opens up opportunities for researchers and practitioners alike to experiment with cutting-edge control strategies tailored to real-world scenarios.

Media

Media

Integrations Supported

Claude for Financial Services
NVIDIA Quadro Virtual Workstation

Integrations Supported

Python
Ubuntu

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Turing

Company Location

United States

Company Website

www.turingsaas.com/platform-overview

Company Facts

Organization Name

MPCPy

Company Location

United States

Company Website

github.com/lbl-srg/MPCPy

Categories and Features

CPG

Not specified

Product Design

Not specified

Categories and Features

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