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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.
Description
IBM Network Intelligence aims to enhance the transition towards an autonomous network lifecycle by providing instantaneous insights and operational automation across various vendors and domains. It employs network-native AI that is specifically trained on extensive telemetry data rather than generic datasets, merging analytical and reasoning functions to act as a cooperative partner rather than merely an observer. With its transparent and explainable AI decisions, it equips users with the assurance needed to understand the rationale behind each action taken. Built upon an open, interoperable framework, it seamlessly integrates with current tools and can function in on-premises, cloud, or hybrid settings without imposing vendor lock-in or necessitating complete system overhauls. From the outset, its pretrained models and swift ecosystem integration empower teams to reduce distractions by leveraging semantic understanding to highlight only actionable, high-confidence insights. This capability not only decreases the frequency of repeated incidents but also accelerates repair times and enhances overall mean time performance, ultimately streamlining network management. Thus, organizations can confidently adopt this cutting-edge technology to navigate the complexities of modern network environments more effectively.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
No
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
Yes
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
Yes
Live Rep (24/7)
Yes
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
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Black Forest Labs
Founded
2024
Country
Germany
Website
bfl.ai/models/flux-3-action
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/products/network-intelligence