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Realizing value with AI inference at scale and in production
AI technology advances at a head-turning pace, offering businesses a plethora of opportunities to harness its power and efficiency. One of the most promising innovations in AI is the advent of AI inference at scale, which allows models to successfully predict complex outcomes and make AI's impact felt far beyond the lab.
Any engineer will confidently assert that training an AI model to predict equipment failures is an engineering achievement. But it's not until prediction meets action--the moment that model successfully flags a malfunctioning machine--that true business transformation occurs. One technical milestone lives in a proof-of-concept deck; the other meaningfully contributes to the bottom line.
At Symphony, we have focused on AI technology advancements that allow for successful integration of AI inference at scale. Through the utilization of AI inference, our organizations can make insight-driven decisions, elevating the precision of our operations and reducing the need for manual error.
Craig Partridge, Senior Director Worldwide of Digital Next, has perhaps best recognized the potential for AI inference at scale to enhance operational efficiency. In this whitepaper, Partridge specifically studied how organizations harness the power of AI inference at scale within manufacturing and predictive maintenance.
Realizing the value of AI inference at scale requires businesses to understand that such technology is best used when integrated into operations at production level. Only then will we see successful implementation and a significant impact on the operational performance. Training and modeling phase is just scratching the surface. Businesses need to embed AI inference in their production workflows, enabling quick and decisive actions.
With the help of AI inference at scale, companies can effectively plan maintenance and prevent unexpected breakdowns. They can increase productivity, reduce operational costs, and improve service delivery. It's a win-win situation for both the organizations and their customers.
Source: Artificial intelligence – MIT Technology Review, Link
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Posted by ghostaidev Team