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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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10 most in-demand enterprise IT skills

CIO

Python Python is a programming language used in several fields, including data analysis, web development, software programming, scientific computing, and for building AI and machine learning models. Its widespread use in the enterprise makes it a steady entry on any in-demand skill list.

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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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IDC chief research officer: GenAI, from experimentation to adoption

CIO

Back in 2023, at the CIO 100 awards ceremony, we were about nine months into exploring generative artificial intelligence (genAI). Fast forward to 2024, and our data shows that organizations have conducted an average of 37 proofs of concept, but only about five have moved into production. We were full of ideas and possibilities.

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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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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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Top 7 Tips for Scaling Your Artificial Intelligence Strategy

OTS Solutions

There Are Top Seven Tips for Scaling Your Artificial Intelligence Strategy. In just the last few years, a large number of enterprises have started to work on incorporating an artificial intelligence strategy into their business. Include Responsibility and Accountability. Start Small and Experiment.