Author's): TANVEER MUSTAFA
Originally published in Towards Artificial Intelligence.
Training costs are falling – inference costs are exploding: 6 types of inference that will save your AI budget
We are witnessing a remarkable paradox in artificial intelligence: while the cost of training sophisticated AI models continues to fall rapidly, the cost of actually using these models – making inferences – is rising rapidly. This change represents a fundamental transformation in the way organizations budget and deploy AI systems.
The article discusses the rising costs associated with AI inference despite decreasing training costs, highlighting the dramatic change in budgeting for AI systems as the demand for inference increases. Covers the complexities and challenges of managing inference spend and the various strategies organizations can employ to optimize costs while maintaining performance, including batch, streaming, edge, hybrid, cached, and speculative inference methods. The importance of developing effective inference strategies is highlighted as a way to increase performance and compete in the evolving artificial intelligence landscape.
Read the entire blog for free on Medium.
Published via Towards AI
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