Achieving Proper Data Governance by Training Centrally; Inferring Locally; and Protecting Data Everywhere
After devoting much of 2023 to AI pilots and experiments following the debut of ChatGPT and GenAI, AI-minded organizations are now working to scale their AI initiatives to capitalize on their early but limited successes. Their goal? To integrate advanced AI capabilities across their operations for greater efficiency, innovation, and competitiveness. An April KPMG survey found that … continue reading
Working toward AIOps maturity? It’s never too early (or late) for platform engineering
Until about two years ago, many enterprises were experimenting with isolated proofs of concept or managing limited AI projects, with results that often had little impact on the company’s overall financial or operational performance. Few companies were making big bets on AI, and even fewer executive leaders lost their jobs when AI initiatives didn’t pan … continue reading
Unleashing innovation via Composable Cloud: Customizing AI tech stacks for inference at the edge
Edge operations dominate the CTO agenda today, and as artificial intelligence (AI) and machine learning grow increasingly important across business operations, the CIO, CAIO, CDO, and other leaders are joining the conversation, leaning into edge operations to deliver AI at scale. However, the traditional edge operations designed to support distributed web apps can’t handle the … continue reading
How IT leaders can get their cloud back in order
The evolution of cloud operations currently revolves around the offerings of the hyperscale cloud providers (hyperscalers). We should consider these “traditional cloud models,” and they typically offer decent value when organizations are just beginning their cloud journeys. But these plans tend to become extremely expensive once the organization starts scaling its cloud initiatives. According to … continue reading
