Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Yeastar P-Series PBX System Reviews & Ratings
    116 Ratings
    Company Website
  • RaimaDB Reviews & Ratings
    12 Ratings
    Company Website
  • Kantata Reviews & Ratings
    2,277 Ratings
    Company Website
  • Gemini Enterprise Agent Platform Reviews & Ratings
    999 Ratings
    Company Website
  • SKU Science Reviews & Ratings
    16 Ratings
    Company Website
  • InEight Reviews & Ratings
    136 Ratings
    Company Website
  • OptiSigns Reviews & Ratings
    8,262 Ratings
    Company Website
  • CompanyCam Reviews & Ratings
    5,585 Ratings
    Company Website
  • Runn Reviews & Ratings
    37 Ratings
    Company Website
  • Martus Reviews & Ratings
    160 Ratings
    Company Website

What is TimesFM-3?

TimesFM-3 is an innovative foundation model for time series analysis, distinguished by its capability to deliver highly accurate multivariate forecasts with a single forward pass. With a substantial framework of 330 million parameters, this model has been pre-trained on an extensive dataset comprising both real-world and synthetic time series information, accumulating over 1 trillion time points, which significantly bolsters its effectiveness and zero-shot generalization compared to its predecessors. It excels at simultaneously forecasting multiple coevolving time series while effectively recognizing dependencies that enhance predictive accuracy without necessitating task-specific fine-tuning. Additionally, it is designed to handle various forecasting objectives, including point and quantile predictions, and takes into account both historical covariates and dynamic covariates related to future scenarios, such as planned promotions, holidays, or shifts in weather. Employing a decoder-only transformer architecture, TimesFM-3 adeptly processes sequential data in chunks of 32 time steps, utilizing alternating causal temporal attention and full variate attention to seamlessly weave together patterns across time and interconnected series. As a result, this model serves as a powerful resource for forecasting intricate, time-dependent phenomena across diverse applications, making it a significant advancement in the field of time series forecasting. Its versatility and precision open up new avenues for exploration and application in various domains.

What is Autobox?

Autobox is distinguished as the most intuitive forecasting solution available, designed to assist both novices and experienced analysts in effortlessly uploading their data to produce expert-level forecasts. No matter which forecasting methods you currently employ, Autobox dramatically improves the accuracy of your predictions. This cutting-edge tool was honored as the "best-dedicated forecasting program" in the Principles of Forecasting textbook and has evolved into an online service. The distinctive approach adopted by AFS circumvents the common issue of confining data to a single model; instead, it enables Autobox to synchronize historical data with relevant causal factors, seamlessly adapting to changes in levels, local time trends, pulses, and seasonal fluctuations when required. Additionally, it possesses the ability to identify new causal variables by scrutinizing historical forecast errors and outliers flagged by its unique engine. Frequently, this analysis uncovers causal elements that might have previously been overlooked, such as promotional events, holidays, and specific weekday effects. By harnessing these revelations, users can substantially enhance the accuracy of their forecasts while also gaining deeper insights into the underlying dynamics affecting their data. This comprehensive capability makes Autobox an invaluable asset for anyone serious about improving their forecasting strategies.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

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

Google

Date Founded

1998

Company Location

United States

Company Website

research.google/blog/timesfm-3-a-zero-shot-foundation-model-for-multivariate-forecasting/

Company Facts

Organization Name

Automatic Forecasting Systems

Company Location

United States

Company Website

autobox.com/cms/index.php/products/autobox

Categories and Features

Categories and Features

Popular Alternatives

Popular Alternatives

CodeQwen Reviews & Ratings

CodeQwen

Alibaba
Kimi K2 Reviews & Ratings

Kimi K2

Moonshot AI
Qwen-7B Reviews & Ratings

Qwen-7B

Alibaba
TimesFM-3 Reviews & Ratings

TimesFM-3

Google