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To understand the risks posed by AI, follow the money

O'Reilly on Data

Time and again, leading scientists, technologists, and philosophers have made spectacularly terrible guesses about the direction of innovation. Others retort that large language models (LLMs) have already reached the peak of their powers. Shortly thereafter, the consensus switched to fears of an imminent nuclear holocaust.

Risk 221
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Large Scale Industrialization Key to Open Source Innovation

Cloudera

We are now well into 2022 and the megatrends that drove the last decade in data — The Apache Software Foundation as a primary innovation vehicle for big data, the arrival of cloud computing, and the debut of cheap distributed storage — have now converged and offer clear patterns for competitive advantage for vendors and value for customers.

Big Data 114
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A history of tech adaptation for today’s changing business needs

CIO Business Intelligence

To do this, Ipsos uses large language models to generate cutting-edge insights built using AI capabilities, complemented by its data science models and tailored to the services it offers,” says Mohammed. But to get to this point, the organization has had to rely on technology for decades as a strategic tool.

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8 questions CIOs should ask to prime their business for gen AI

CIO Business Intelligence

Critical to getting this right is understanding and linking gen AI and innovation to enterprise success. Companies are now recognizing the work ahead of them to get their data, people, and processes ready to capitalize on gen AI’s potential. So leaders will need to radically re-think how work gets done. So, what can CIOs do now?

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The future of application delivery starts with modernization

IBM Big Data Hub

Access to new software innovation: Software has become the lifeline of all domains. Organizations must keep up with the technology of today so they can innovate and satisfy the ever-changing needs of the customers. Many organizations have disappeared from the technology map because of failing to adapt and adopt innovation quickly.

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Demystifying Multimodal LLMs

Dataiku

This scenario is not science fiction but a glimpse into the capabilities of Multimodal Large Language Models (M-LLMs), where the convergence of various modalities extends the landscape of AI. But instead, a machine seamlessly identifies the scene and its location, provides a detailed description, and even suggests nearby attractions.

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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

The big data market is expected to exceed $68 billion in value by 2025 , a testament to its growing value and necessity across industries. The big data market is expected to exceed $68 billion in value by 2025 , a testament to its growing value and necessity across industries. Did you know? Where is all of that data going to come from?

Big Data 275