AI

As artificial intelligence (AI) technology continues to evolve rapidly, the risks associated with its use also increase in complexity and severity. To help organizations navigate this challenging landscape, researchers from MIT and other institutions have developed the AI Risk Repository. This database is a comprehensive collection of over 700 documented risks posed by AI systems,
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Integrating generative AI into healthcare practices goes beyond just implementing new technology. Kiran Mysore, chief data and analytics officer at Sutter Health, and Aashima Gupta, Google Cloud Director for global healthcare, highlighted the transformative power of generative AI during a panel at VentureBeat’s Transform event. They emphasized how this technology has significantly reduced the burden
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Artificial intelligence (AI) research has reached new heights with the introduction of ToolSandbox by researchers at Apple. This innovative benchmark aims to revolutionize the assessment of AI assistants by providing a more comprehensive evaluation of their real-world capabilities. ToolSandbox addresses critical gaps in existing evaluation methods for large language models (LLMs) and incorporates stateful interactions,
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In the fast-paced world of artificial intelligence development, one of the key factors that can determine the success of enterprises is the availability of large language models (LLMs). The regional availability of these models can provide a significant competitive advantage, allowing faster access to innovation. However, many organizations face challenges when models are not yet
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In the suburbs of northeast Paris, Equinix, an American data center company, has recently completed a new data center known as PA10. This massive terra-cotta-colored warehouse houses a labyrinth of windowless corridors filled with high-density racks of computer servers. The constant whirring sound emanating from the cooling systems is a testament to the company’s efforts
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As business leaders, the rapid advancement of Artificial Intelligence (AI) technology presents a challenge in identifying clear use cases and guidelines within organizations. The evolving nature of AI requires us to think ahead while also grounding ourselves in the present reality of how it impacts our business models, employee experience, and customer interactions. It is
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