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Description
Agora-1 is an innovative multi-agent world model that facilitates real-time interaction among several participants, whether they are human or AI, within a shared world simulation. This model represents the inaugural installment in a sequence of multi-agent world models aimed at uncovering new shared experiences in various fields such as gaming, robotics, defense, education, and foundational models. Traditionally, world models have excelled at creating high-fidelity simulations of diverse environments but were limited by the fact that only one active participant could engage with these simulated worlds at a time. With Agora-1, the concept of multi-agent world simulations is brought to life, enabling as many as four players to engage simultaneously in the same generated environment. These players are immersed in a competitive deathmatch simulation, where each participant interacts with the same world concurrently, as the model adeptly simulates player actions, manages a unified world state, and streams the rendered visuals to every player, enhancing the immersive experience. This advancement paves the way for more collaborative and interactive engagements in various domains.
Description
FLUX 3 Action is a versatile 7B world-action model aimed at enhancing action prediction for robotics and other environments with high latency demands. This model is built upon the multimodal FLUX 3 backbone and has undergone extensive pretraining on vast datasets encompassing images, videos, and audio, with a notable focus on video content. It then goes through a phase of joint video-action training and fine-tuning tailored to specific robotic applications and action frameworks. By utilizing instructions, visual input from cameras, and robot joint angles, FLUX 3 Action is capable of predicting motor commands alongside anticipated visual outcomes, enabling robots to perform actions, reassess their surroundings, and iterate on their plans. This approach contrasts with methods that treat visual prediction and control as separate processes, as FLUX 3 Action integrates future video predictions with action commands, effectively leveraging knowledge gained from extensive video pretraining to refine robot control mechanisms. Impressively, its single-step 7B model achieves a success rate of 38.3% on the RoboLab-120 benchmark, showcasing its effectiveness in real-world applications. Furthermore, this innovative integration of action and perception marks a significant advancement in the field of robotic control.
API Access
Has API
No
API Access
Has API
Yes
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Odyssey
Founded
2023
Country
United States
Website
odyssey.ml/introducing-agora-1
Vendor Details
Company Name
Black Forest Labs
Founded
2024
Country
Germany
Website
bfl.ai/models/flux-3-action