5 Ways to Transform Worker Safety with Artificial Intelligence

5 Ways to Transform Worker Safety with Artificial Intelligence
Leverage proven enterprise computer vision technology to automate real-time visual analytics and alerts using your existing camera infrastructure. SparkCognition Visual AI Advisor supports more than 125 end-to-end use cases to improve safety, security, visual inspection, productivity, and situational awareness.
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Spotlight

OTHER ON-DEMAND WEBINARS

AI for Media and Entertainment

Digital Domain

In this webinar, visual effects and digital production company Digital Domain will share their experience developing AI-based toolsets for applying deep learning to their content creation pipeline. AI is no longer just a research project but also a valuable technology that can accelerate labor-intensive tasks, giving time and control back to artists.
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Practicalities of Artificial Intelligence Making AI Business-Smart

SAS

Artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Most AI examples that you hear about today – from chess-playing computers to self-driving cars – rely heavily on deep learning and natural language processing. Using these technologies, computers can be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data.
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Can Your Network Survive the Miercom Torture Test?

Silver Peak

Join leading independent product assessment group, Miercom and technical experts from Silver Peak as they discuss the performance expectations of today’s networks and how the right SD-WAN solution can improve application availability across the WAN using any type of transport. They will disclose how Silver Peak’s SD-WAN solution, Unity EdgeConnect fared in their aggressive stress test environment and provide a live demo on its performance capabilities.
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Take AI/ML models to production faster by bringing performance & productivity to your MLOps

According to industry analysts, more than 85% of artificial intelligence (AI) deployments never make it into production. Moving from research (using small data sets) to robust online production environments is far from trivial. Production environments need to process large amounts of real-world data and meet application performance and SLA goals. To bring AI projects from the lab to production, organizations need a production-first mindset. They also need underlying infrastructure built for scale and high performance.
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