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5 machine learning essentials nontechnical leaders need to understand

TechCrunch

We’re living in a phenomenal moment for machine learning (ML), what Sonali Sambhus , head of developer and ML platform at Square, describes as “the democratization of ML.” Snehal Kundalkar is the chief technology officer at Valence. She has been leading Silicon Valley firms for the last two decades, including work at Apple and Reddit.

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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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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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How companies around the world apply machine learning

O'Reilly Media - Data

Strata Data London will introduce technologies and techniques; showcase use cases; and highlight the importance of ethics, privacy, and security. The growing role of data and machine learning cuts across domains and industries. Data Science and Machine Learning sessions will cover tools, techniques, and case studies.

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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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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.

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Enhancing customer care through deep machine learning at Travelers

CIO

And we recognized as a company that we needed to start thinking about how we leverage advancements in technology and tremendous amounts of data across our ecosystem, and tie it with machine learning technology and other things advancing the field of analytics. But we have to bring in the right talent.