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Inferencing holds the clues to AI puzzles

CIO

Inferencing has emerged as among the most exciting aspects of generative AI large language models (LLMs). A quick explainer: In AI inferencing , organizations take a LLM that is pretrained to recognize relationships in large datasets and generate new content based on input, such as text or images.

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Building a vision for real-time artificial intelligence

CIO

Data is a key component when it comes to making accurate and timely recommendations and decisions in real time, particularly when organizations try to implement real-time artificial intelligence. Real-time AI involves processing data for making decisions within a given time frame. It isn’t easy.

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Salesforce Data Cloud updates aim to ease data analysis, AI app development

CIO

Salesforce is updating its Data Cloud with vector database and Einstein Copilot Search capabilities in an effort to help enterprises use unstructured data for analysis. The Einstein Trust Layer is based on a large language model (LLM) built into the platform to ensure data security and privacy.

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Henkel embraces gen AI as enabler and strategic disruptor

CIO

Gearing up for change Headquartered in Dusseldorf with 50,000-plus employees, Henkel is more than a CPG enterprise. But to achieve Henkel’s digital vision, Nilles would need to attract data scientists, data engineers, and AI experts to an industry they might not otherwise have their eye on.

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What is Oracle’s generative AI strategy?

CIO

“Our tier strategy resembles a three-layer cake and each of these layers targets different enterprise customers depending on their needs,” said Karan Batta, vice president of Oracle Cloud Infrastructure (OCI). Oracle is also planning to extend the service to enterprises that have their data and applications in their own data centers.

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What is a data engineer? An analytics role in high demand

CIO

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. The data engineer role.

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Here’s where MLOps is accelerating enterprise AI adoption

TechCrunch

But with time, enterprises overcame their skepticism and moved critical applications to the cloud. DevOps fueled this shift to the cloud, as it gave decision-makers a sense of control over business-critical applications hosted outside their own data centers.