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What is Timestral?

Timestral is a comprehensive suite of time-series foundation models accompanied by a Python inference toolkit, specifically designed to enable the creation of multivariate probabilistic forecasts derived from historical data sequences. It offers four distinct model sizes, including 5M, 28M, 123M, and 209M parameters, each capable of managing past-only, known-future, and categorical covariates, while providing quantile forecasts that can accommodate context windows of up to 32,768 time steps. Users can conveniently load pretrained weights from the Hugging Face Hub or from their local files, allowing for inference on both CPU and GPU setups. These forecasts can be integrated effortlessly into a wide array of applications, such as monitoring systems, capacity planning, energy management, supply chain logistics, financial risk analysis, and maintenance operations. Additionally, Timestral boasts zero-shot forecasting capabilities and can be customized to specific domain data using the Mistral Forge, further enhancing its versatility. This toolkit primarily targets data scientists, machine learning engineers, and collaborative teams eager to devise effective forecasting solutions; its repository code is available under the Apache 2.0 license, while the model weights are managed by a distinct Modified MIT license. With its robust and comprehensive features, Timestral is set to considerably improve the precision and effectiveness of predictive analytics across various sectors, ensuring that users can make informed decisions based on reliable forecasts. As industries increasingly rely on data-driven insights, Timestral stands out as an essential resource for achieving superior forecasting outcomes.

What is Covariant?

Revolutionize your warehouse operations and meet scalability challenges with state-of-the-art robotic automation, pioneered by leading AI experts across the globe. The Covariant Brain, which has learned from countless selections in a variety of warehouse environments, empowers robots to autonomously and adeptly pick nearly any SKU or product right from the outset. Furthermore, Covariant's AI-driven Robotic Putwall enhances this capability by automatically sorting items from mixed-SKU containers, effectively addressing labor shortages while increasing overall productivity. Each solution is meticulously tailored to fit seamlessly with your existing floor layout, systems, and workflows both upstream and downstream. Moreover, the fleet learning feature enables each robot to gain insights from the shared experiences of interconnected robots operating in warehouses around the world. Consequently, once deployed, Covariant robots are primed to handle nearly any SKU or item, regardless of its dimensions or packaging type. This innovative technology not only simplifies operations but also leads to remarkable improvements in efficiency and productivity within your warehouse setting. As a result, businesses can expect to see a significant return on investment as they embrace these advancements.

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Media

Integrations Supported

Mistral Forge

Integrations Supported

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Version

Pricing Information

Pricing not provided

Supported Platforms

On-Prem

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Online Training

Company Facts

Organization Name

Mistral AI

Date Founded

2023

Company Location

France

Company Website

github.com/mistralai/timestral

Company Facts

Organization Name

Covariant

Date Founded

2017

Company Location

United States

Company Website

covariant.ai/

Categories and Features

AI Models

Not specified

Categories and Features

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