NetCrunch is commercial, self-hosted, agentless network and IT infrastructure monitoring software for Windows Server. It monitors network devices, servers, virtualization platforms, cloud services, applications, websites, logs, telemetry, and network traffic across distributed environments.
NetCrunch supports 680+ monitoring targets and provides 270+ ready-to-use Monitoring Packs for devices, applications, and operating systems. Policy-based monitoring automatically applies monitoring settings, Monitoring Packs, thresholds, and alerts to matching devices and systems. Licensing is based on monitored nodes and network interfaces rather than individual sensors, checks, or metrics.
NetCrunch provides real-time dashboards and automatic Layer 2 and routing topology maps for visibility into network status and performance. Network traffic analysis supports NetFlow, sFlow, IPFIX, and other flow technologies. Its alerting system supports event correlation, dependency-aware suppression, predictive thresholds, escalation, and 40+ automated response actions, including scripts, notifications, API calls, and integrations with external systems.
Distributed Monitoring Probes extend monitoring to remote and isolated locations. NetCrunch also provides a REST API for integration and automation with external IT management, service management, and operational systems.
NetCrunch is self-hosted on Windows Server and can monitor on-premises, air-gapped, cloud, and hybrid IT environments.
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With TrafficGuard, you can put an end to the worry of polluted traffic disrupting your campaign success.
Our advanced ML/AI-powered technology identifies and blocks both simple and complex fraudulent traffic in real time, ensuring your ad spend targets genuine, high-quality clicks and conversions. This leads to better campaign outcomes and an enhanced return on ad spend (ROAS).
This robust solution safeguards every dollar of your advertising budget, allowing you to concentrate on reaching your marketing objectives without stress. Let TrafficGuard handle ad fraud protection, so you can confidently manage your:
Google Search (PPC) campaigns
Mobile user acquisition campaigns
Affiliate spending
Social media advertising
In addition to our technology, we provide expert campaign management and exceptional customer support, making us a reliable partner for all your ad fraud protection needs.
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FLUX 3 Action
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.
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amige.
Amige is a tool that assesses whether an image, video, or piece of text has been generated by AI. It operates by utilizing a weighted collection of independent detectors that combine their findings and highlight areas of disagreement. In instances where the evidence is inconclusive, it opts to state "uncertain" rather than making inaccurate assumptions. Each assessment is accompanied by a confidence percentage, a detailed breakdown from each detector, and an educated guess regarding which of over 90 generative models—such as Midjourney, Sora, Flux, or Stable Diffusion—was responsible for its creation. Additionally, it includes video detection capabilities that text-only checkers are unable to provide. This system also has the capacity to analyze C2PA Content Credentials and SynthID provenance. Users can access a free tier that permits up to three scans each day without requiring a credit card. Overall, Amige offers a comprehensive approach to verifying the authenticity of media content.
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