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Unlocking the Power of AI with a Real-Time Data Strategy

CIO

ChatGPT and Stable Diffusion are two popular examples of how AI is becoming increasingly mainstream. With organizations looking for increasingly sophisticated ways to employ AI capabilities, data becomes the foundational energy source for such technology. Now, with the rise of AI, this power is becoming even more evident.

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10 most difficult-to-fill IT roles — and how to address the gap

CIO

The CIO’s biggest hiring challenge is clear: “There is simply not enough talent to go around,” says Scott duFour, global CIO of business payments company Fleetcor, for whom positions in areas such as AI, cloud architecture, and data science remain the toughest to fill.

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From particle physics to video streaming: predicting churn with AI

Agile Engine

Explore Data Studio projects and expertise in-depth Learn more Business challenge: addressing subscriber churn in the video streaming industry The client engaging our ML and data engineers is a premium streaming video on demand (SVOD) network top-listed by CNET in 2023.

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Announcing Cloudera’s Enterprise Artificial Intelligence Partnership Ecosystem

Cloudera

Founding AI ecosystem partners | NVIDIA, AWS, Pinecone NVIDIA | Specialized Hardware Highlights: Currently, NVIDIA GPUs are already available in Cloudera Data Platform (CDP), allowing Cloudera customers to get eight times the performance on data engineering workloads at less than 50 percent incremental cost relative to modern CPU-only alternatives.

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Technology Trends for 2023

O'Reilly Media - Ideas

In 2021, we saw that GPT-3 could write stories and even help people write software ; in 2022, ChatGPT showed that you can have conversations with an AI. Content about software development was the most widely used (31% of all usage in 2022), which includes software architecture and programming languages. growth over 2021.

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Data Collection for Machine Learning: Steps, Methods, and Best Practices

Altexsoft

Both data integration and ingestion require building data pipelines — series of automated operations to move data from one system to another. For this task, you need a dedicated specialist — a data engineer or ETL developer. Data engineering explained in 14 minutes. No wonder only 0.5