In the evolving landscape of artificial intelligence (AI), the assumption that more data lead to better models has driven unchecked reliance on synthetic data to augment training datasets. Although ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance ...

Legacy data collection systems create blind spots that adversaries exploit with AI-driven attacks. Kam Amir, director of ...

DC research shows Splunk delivers an average $18 million in annual benefits per manufacturer, a 480% ROI over three years, ...

For enterprises, proprietary data is a source of competitive advantage. Take these four steps to ready it for AI-powered ...

Veeam® Software, the #1 global leader in data resilience, today launches Veeam Data Platform v13 — a groundbreaking release ...

Arista Networks leads in data center networking, providing high-performance Ethernet switches crucial for AI workloads and ...

Every 39 seconds, somewhere in the world, a new cyberattack is launched — and far too often, it’s not a sophisticated hack but the reuse of legitimate credentials already exposed online. As data ...

AlertD today launched out of stealth, unveiling its agentic AI SRE (Site Reliability Engineering) and DevOps platform designed to tackle the mounting operational complexity of cloud operations. AlertD ...

Doubles parameters to over 17 billion, to detect threats and recommend actions Exclusive Cisco is working on a new AI model that will more than double the number of parameters used to train its ...

This process is costly, time-consuming, and has a low success rate. KAIST researchers have developed an AI model that, using only information about the target protein, can design optimal drug ...

The Splunk Threat Research Team is releasing v4.0 of Splunk Attack Range, an open source project that allows security teams to spin up a detection development environment to emulate adversary behavior ...