Startups integrating artificial intelligence face unprecedented challenges: increasingly rapid development times, limited funding, and rising infrastructure costs.

Infrastructure choices and long-term consequences

Easy access to resources such as cloud credits, GPUs, and foundation models offered by platforms like Google Cloud, allows for a faster start. However, initial infrastructure decisions can have significant repercussions as startups grow and scale their operations. It is crucial to carefully assess the long-term implications of these choices.

For those evaluating on-premise deployments, there are trade-offs to consider carefully. AI-RADAR offers analytical frameworks on /llm-onpremise to evaluate these aspects.