Eight hours of robot data collection yield just two to four hours of usable training data. Explore what physical AI leaders say about closing that gap.
Engineers build tools, hand them off and move on. Here’s why contact center AI adoption fails at the frontline — and how embedded engineering fixes it.
Most contact center AI underperforms because of data, not technology. Learn how structured transcript annotation and institutional knowledge build a contact center AI data strategy that improves agent performance.
The age verification methods most platforms have relied on for the past decade do not satisfy regulators or hold up against AI-driven bypass. Learn how enterprises can adapt their strategies to remain compliant.
100 hand-crafted test questions weren't enough. Here's what Fortify found and how it changed the team's approach to AI security and governance.
What is an AI developer? The term is drifting, with multiple definitions and none of them quite right. Here's the definition that matters for enterprise teams.
What is an AI system builder? It’s the role most enterprises don't have and can't scale AI without. Here’s a practical definition for engineering leaders.
What 164 corporate treasurers told us about North American banking’s infrastructure gap — and why closing it doesn’t require a core replacement.
Google I/O 2026 changed how enterprise AI gets built. Here's what leaders need to act on and what can wait.
Discover how TELUS Digital has built the infrastructure for frontier AI, including expert talent pipelines, human-AI collaboration architecture and adversarial safety tools designed for a moment when qualified human judgment, at scale, is the real bottleneck.
TELUS Digital tested 34 AI models with 620,000 adversarial attacks. Here's what the data shows about your AI attack surface — and how to close the gap.
Learn how world models differ from LLMs, the five properties that make them useful and why causality and action-conditioned prediction are keys to physical AI.
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