VENDORiQ: Google Ironwood: A driver for Cost Efficiency in AI?
Google’s Ironwood TPU targets AI inference cost/efficiency, vital for scaling complex models amidst fierce competition.
Google’s Ironwood TPU targets AI inference cost/efficiency, vital for scaling complex models amidst fierce competition.
Ready-made GenAI offers speed but limits customisation. Building in-house allows bespoke solutions but demands time and risk. AI platforms provide a hybrid path for rapid, tailored deployment.
Digital transformation, particularly with AI, requires a structured approach like strategic value realisation (SVR) to ensure strategic value capture. SVR aligns stakeholders through clear objectives, focusing on cost reduction, operational enhancement, and stakeholder value. Fragmented AI adoption risks long-term value.