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How AI orchestration has become more important than the models themselves

CIO

Large language models (LLMs) just keep getting better. In just about two years since OpenAI jolted the news cycle with the introduction of ChatGPT, weve already seen the launch and subsequent upgrades of dozens of competing models. From Llama3.1 to Gemini to Claude3.5 In fact, business spending on AI rose to $13.8

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The key to operational AI: Modern data architecture

CIO

Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.

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Comprehensive data management for AI: The next-gen data management engine that will drive AI to new heights

CIO

All industries and modern applications are undergoing rapid transformation powered by advances in accelerated computing, deep learning, and artificial intelligence. The next phase of this transformation requires an intelligent data infrastructure that can bring AI closer to enterprise data.

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Data engineers vs. data scientists

O'Reilly Media - Data

It’s important to understand the differences between a data engineer and a data scientist. Misunderstanding or not knowing these differences are making teams fail or underperform with big data. I think some of these misconceptions come from the diagrams that are used to describe data scientists and data engineers.

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IT leaders: What’s the gameplan as tech badly outpaces talent?

CIO

Gen AI-related job listings were particularly common in roles such as data scientists and data engineers, and in software development. To help address the problem, he says, companies are doing a lot of outsourcing, depending on vendors and their client engagement engineers, or sending their own people to training programs.

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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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From Machine Learning to AI: Simplifying the Path to Enterprise Intelligence

Cloudera

Thats why were moving from Cloudera Machine Learning to Cloudera AI. Its a signal that were fully embracing the future of enterprise intelligence. From Science Fiction Dreams to Boardroom Reality The term Artificial Intelligence once belonged to the realm of sci-fi and academic research.