Remove real-time-data-in-machine-learning-challenges-and-solutions
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TIAA modernizes the customer journey with AI

CIO

Sastry Durvasula, chief information and client services officer at TIAA, says the multilayered platform’s extensive use of machine learning as part of its customer service line partnership with Google AI makes JSOC a formidable tool for financial and retirement planning and guiding customers through complex financial journeys.

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Real-Time Data in Machine Learning: Challenges and Solutions

Dataversity

In today’s dynamic global marketplace, events outside of our control are constantly making the data we’ve collected erroneous and outdated. There are instances in which real-time decision-making isn’t particularly critical (such as demand forecasting, customer segmentation, and multi-touch attribution).

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How AI is reshaping Saudi Aramco’s oil exploration and underwater operations strategy

CIO

USD billion in 2023, representing a 15% annual increase despite global challenges. These images are then analyzed using machine learning algorithms to detect oil spills and pollutants. Known as Aramco METABRAIN, the generative AI model is trained on data accumulated by the company over the past 90 years.

Startups 669
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Building a vision for real-time artificial intelligence

CIO

By George Trujillo, Principal Data Strategist, DataStax I recently had a conversation with a senior executive who had just landed at a new organization. He had been trying to gather new data insights but was frustrated at how long it was taking. Real-time AI involves processing data for making decisions within a given time frame.

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UPS delivers customer wins with generative AI

CIO

During pilot testing, UPS earned 50% reduction in the time agents spent resolving e-mails. This shift to a confirmation role — with standardized workflows — saves the company both time and money, Subramanian says. United Parcel Service last year turned to generative AI to help streamline its customer service operations.

Win 859
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AI and generative AI are revolutionizing manufacturing…here’s how

CIO

The timing for these advancements is optimal as the industry grapples with skilled labor shortages, supply chain challenges, and a highly competitive global marketplace. AI can help with all of these challenges via manufacturing-specific use cases that benefit manufacturers, their employees, and their customers. Here’s how.

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Transform the modern data center: From today to the future

CIO

A seismic shift is underway in the evolution of the data center, driven by a variety of converging factors. These include the accelerating transition to cloud platforms, the growth of hybrid and remote work models, and the rapid adoption of artificial intelligence (AI) and machine learning (ML) technologies across every industry.

Learning 506