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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. The underpinning architecture needs to include event-streaming technology, high-performing databases, and machine learning feature stores.

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Composite AI: The trifecta that is transforming AIOps

CIO

When it comes to the different types of artificial intelligence (AI), 1+1+1 can equal more than three. Composite AI provides explanations of root causes in plain language and often automatically fixes issues before they grow into giant headaches for IT. AI trained on biased data may produce unreliable results.

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FinOps and AI: Balancing innovation and cost efficiency

CIO

Accelerated adoption of artificial intelligence (AI) is fuelling rapid expansion in both the amount of stored data and the number of processes needed to train and run machine learning models. It takes huge volumes of data and a lot of computing resources to train a high-quality AI model.

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AI, Cybersecurity and the Rise of Large Language Models

Palo Alto Networks

Artificial intelligence (AI) plays a crucial role in both defending against and perpetrating cyberattacks, influencing the effectiveness of security measures and the evolving nature of threats in the digital landscape. A large language model (LLM) is a state-of-the-art AI system, capable of understanding and generating human-like text.

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Deploy large language models for a healthtech use case on Amazon SageMaker

AWS Machine Learning - AI

To support overarching pharmacovigilance activities, our pharmaceutical customers want to use the power of machine learning (ML) to automate the adverse event detection from various data sources, such as social media feeds, phone calls, emails, and handwritten notes, and trigger appropriate actions.

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Generative AI in enterprises: LLM orchestration holds the key to success

CIO

Many enterprises are accelerating their artificial intelligence (AI) plans, and in particular moving quickly to stand up a full generative AI (GenAI) organization, tech stacks, projects, and governance. We think this is a mistake, as the success of GenAI projects will depend in large part on smart choices around this layer.

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Pentagon’s first chief AI officer leaves after two years

CIO

The first leader of the fledgling Chief Digital and Artificial Intelligence Office [CDAO] in the US Department of Defense is leaving his post, but the Pentagon already has a successor lined up. Martell had previously served as head of machine learning at Lyft and as head of machine intelligence at Dropbox.