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What is IBM Network Intelligence?

IBM Network Intelligence is designed to facilitate a smooth transition to an autonomous network lifecycle by delivering real-time insights and automating operations across diverse vendors and sectors. Utilizing network-native AI specifically developed on comprehensive telemetry data, it combines analytical capabilities with reasoning to function as a collaborative partner rather than a passive observer. Its AI decisions are transparent and explainable, providing users with the confidence to grasp the reasoning behind every action taken. Built on an open and interoperable framework, it integrates effortlessly with existing tools and operates in on-premises, cloud, or hybrid environments without enforcing vendor lock-in or requiring extensive system changes. From the beginning, its pretrained models and rapid ecosystem integration enable teams to minimize distractions by focusing on actionable, high-confidence insights. This functionality not only reduces the number of recurring incidents but also speeds up repair times and improves overall mean time performance, leading to more efficient network management. Thus, organizations can adopt this innovative technology with confidence, effectively addressing the challenges presented by today's complex network landscapes. Ultimately, this advancement empowers businesses to stay ahead in an ever-evolving digital world.

What is FLUX 3 Action?

FLUX 3 Action is a dynamic 7B model designed to improve action prediction in robotics and other high-latency environments. It is founded on the multimodal FLUX 3 backbone and has been rigorously pretrained on extensive datasets that include images, videos, and audio, with a significant emphasis on video materials. Following this, it enters a joint video-action training and fine-tuning phase that is specifically tailored for various robotic applications and action frameworks. By processing instructions, visual data from cameras, and robot joint angles, FLUX 3 Action can forecast motor commands while also anticipating visual results, allowing robots to execute actions, reassess their environment, and refine their plans accordingly. Unlike traditional methods that separate visual prediction from control, this model merges future video predictions with action commands, effectively using insights gained from its comprehensive video pretraining to enhance robot control strategies. Impressively, its single-step 7B model boasts a success rate of 38.3% on the RoboLab-120 benchmark, underscoring its practicality in real-world scenarios. Additionally, this novel fusion of action and perception represents a groundbreaking leap forward in the domain of robotic control, paving the way for more sophisticated and capable robotic systems. As technology advances, the implications of such an integrated approach could lead to even more intelligent and responsive robots in various applications.

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

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/products/network-intelligence

Company Facts

Organization Name

Black Forest Labs

Date Founded

2024

Company Location

Germany

Company Website

bfl.ai/models/flux-3-action

Categories and Features

Network Management

Not specified

Categories and Features

AI Models

Not specified

AI World Models

Not specified

Open-Weight AI Models

Not specified

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