Improve Threat Intelligence with Data Analytics and Machine Learning

The cybersecurity industry is increasingly producing enormous amounts of raw threat data. The sheer volume of information threat researchers must sift through makes it difficult to collect, analyze, and research that data on time. This in turn limits their ability to understand what data is valid and useful and whether threat artifacts will result in …

Learn How to Transform B2B Sales and Engage with Buyers Online

The age of the connected customer is here. Learn how to build and maintain connected relationships with your buyers using insights from over 2,900 B2B commerce sales professionals. See how sales teams are meeting customers where they are by: Using a single view of the customer to collaborate Deploying self-service to free up time for …

Trust and Understand AI for Successful Transformation with Regulatory Compliance

When considering AI, you may have potential questions or simply want to understand AI better. Trusting and understanding AI is key to a successful AI transformation. This is especially pertinent in industries with stringent regulations, such as financial services, banking, and healthcare. After all, if the AI gets it wrong, people may be adversely affected.

Tackling Clinical Trial Data Overload with Data Lakes and Machine Learning

As clinical trial complexity increases, trial sizes grow, and data variety and volume explode, this problem is only growing worse. For sponsors and CROs who are experiencing this challenge, within and across studies, a clinical data and analytics hub built on big data, data lake architecture offers great promise. This article explores how a data …

Artificial Intelligence and Machine Learning for the fundaments of 5G Network Monitoring

#DestinationAutomation is a six-part campaign featuring videos supported by in-depth white papers, examining how telcos and other businesses can maximize the benefits and opportunities of automation in digital transformation. We’ve already seen automation take off across many industry sectors – from smart cars to smart homes, telemedicine to finance, and retail to field service operations. …

Towards the better Datacenter Operation and Management with Artificial Intelligence

Artificial Intelligence is emerging quickly as a key tool in the operation and management of data centers. As data centers continue to become more business-critical, more technologically complex and networked, and more reliant on empirical/data-driven rather than ‘hunch’ decision making so human capabilities are proving increasing challenged in managing the data center environment. The complexity …

Maximize the use of AI in Commerce to Improve Customer Experience

2020 is coming up fast, but did you know it is predicted that by then, 85% of customer service interactions will be powered by AI bots? Did you also know that by 2020, 100 million consumers are expected to shop using AR technology? The use of AI in commerce is the future of customer experience …

How Texas Instruments Sitara Processors bring greater Intelligence to the Edge

The rise of robots and self-driving vehicles demand greater intelligence at the local level. Keeping the latency to a minimum, more processing will need to be done at the edge and the compute time must be kept to a minimum by use of more sophisticated techniques. See how the closer interaction of human beings with …

How Cloud, AI and Hybrid Rendering are Transforming Media and Entertainment Industrial

Media companies are well aware of shifting consumption patterns and realize the need for change. However, where to start in the digital journey can be confusing and daunting. A constantly changing digital landscape and shifting audience usage patterns makes it challenging for companies to know where and how to fully commit. In this article, we’ll …

How Sensor Data is Powering ML and AI in Next-Generation Robotics

From traditional industrial robotic systems to today’s latest collaborative robots (or “cobots”), robots rely on sensors that generate increasingly massive volumes of highly varied data. This data can help build better machine learning (ML) and artificial intelligence (AI) models that robots rely on to become “autonomous,” making real-time decisions and navigating in dynamic real-world environments. …