Odyssey-3

Odyssey-3

Odyssey
TimesFM-3

TimesFM-3

Google
+
+

Related Products

  • LTX
    182 Ratings
    Visit Website
  • DataBuck
    6 Ratings
    Visit Website
  • Grafana Cloud
    860 Ratings
    Visit Website
  • myACI
    481 Ratings
    Visit Website
  • iTacit
    46 Ratings
    Visit Website
  • Qloo
    23 Ratings
    Visit Website
  • NINJIO
    416 Ratings
    Visit Website
  • Code-Cube.io
    7 Ratings
    Visit Website
  • SMS Storetraffic
    130 Ratings
    Visit Website
  • Seertech
    15 Ratings
    Visit Website

About

Odyssey-3 is a foundation world model and learned dynamical system that predicts how objects move and interact through space and how situations evolve over time. Implemented as an autoregressive diffusion transformer, it learns representations of physics, dynamics, and cause-and-effect from a broad dataset of visual observations and uses that knowledge to simulate environments and train policies for physical systems. Odyssey-3 can generate embodied environments from a prompt and predict in real time how they change as a person or agent acts or introduces events, with first-person and third-person navigation and independent camera movement. Its learned world knowledge can be adapted to different systems by training an action decoder or policy on paired observations and actions. With relatively small amounts of task-specific data, Odyssey-3 has been used to control robot arms, power humanoids, drive vehicles, and generate synchronized multi-sensor observations. It can also provide intera

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.

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

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

Audience

AI developers, teams, and researchers seeking to simulate dynamic environments, train agents, and adapt learned world knowledge to robots, vehicles, drones, and physical systems

Audience

Data scientists, researchers, and developers wanting to forecast multiple related time series and incorporate historical and known future signals

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Odyssey
Founded: 2023
United States
odyssey.systems/meet-odyssey-3

Company Information

Google
Founded: 1998
United States
research.google/blog/timesfm-3-a-zero-shot-foundation-model-for-multivariate-forecasting/

Alternatives

No Alternatives

Alternatives

CodeQwen

CodeQwen

Alibaba
Kimi K2

Kimi K2

Moonshot AI
Qwen-7B

Qwen-7B

Alibaba

Categories

AI World Models Supported
Foundation Models Supported

Categories

AI Models Supported
Foundation Models Supported

Integrations

No info available.

Integrations

No info available.
Claim Odyssey-3 and update features and information
Claim Odyssey-3 and update features and information
Claim TimesFM-3 and update features and information
Claim TimesFM-3 and update features and information