TimesFM-3Google
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Related Products
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About
Address the change and scale of your warehouse operations with robotic automation, built by the world’s leading AI research scientists. Trained on millions of picks from Covariant robots in warehouses around the world, the Covariant Brain enables robots to autonomously pick virtually any SKU or item on Day One. Covariant’s AI-powered Robotic Putwall autonomously sorts items from mixed-SKU totes, closing labor gaps while increasing throughput. Each deployment is meticulously tailored to fit into your existing floorplan, systems, and upstream/downstream processes. With fleet learning, each robot learns from millions of picks performed by connected robots in warehouses around the world. Right out of the box, Covariant robots can handle virtually any SKU or item, regardless of shape, size, or packaging.
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About
TimesFM-3 is a state-of-the-art time series foundation model designed for highly accurate multivariate forecasting in a single forward pass. The 330 million parameter model is pre-trained on a real-world and synthetic time-series corpus comprising more than 1 trillion time points, building on the efficiency and zero-shot generalization of earlier TimesFM models. It can jointly predict multiple coevolving time series and capture dependencies that improve accuracy without task-specific fine-tuning. The model supports multiple targets with point and quantile forecasts, past covariates that are known only historically, and past-future dynamic covariates such as planned promotions, holidays, or weather forecasts. TimesFM-3 uses a decoder-only transformer architecture, processes contiguous data in patches of 32 time steps, and applies alternating causal temporal attention and full variate attention to combine patterns across time and related series.
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Platforms Supported
Windows
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Mac
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Linux
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Cloud
Supported
On-Premises
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iPhone
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iPad
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Android
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Chromebook
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Organizations looking for an universal AI solution to give robots the ability to see, reason and act on the world around them
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Audience
Data scientists, researchers, and developers wanting to forecast multiple related time series and incorporate historical and known future signals
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Support
Phone Support
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24/7 Live Support
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Online
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Support
Phone Support
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24/7 Live Support
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Online
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API
Offers API
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API
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Pricing
No information available.
Free Version
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Free Trial
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Pricing
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Reviews/
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Training
Documentation
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Webinars
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Live Online
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In Person
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Training
Documentation
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Webinars
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Live Online
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Company InformationCovariant
Founded: 2017
United States
covariant.ai/
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Company InformationGoogle
Founded: 1998
United States
research.google/blog/timesfm-3-a-zero-shot-foundation-model-for-multivariate-forecasting/
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