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Responsible AI is a competitive advantage

IBM Journey to AI blog

In the era of generative AI, the promise of the technology grows daily as organizations unlock its new possibilities. However, the true measure of AI’s advancement goes beyond its technical capabilities. An interactive version of the foundation model white paper is also available through IBM watsonx™ AI risk atlas.

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CUDA Accelerated: How CUDA Libraries Bolster Cybersecurity With AI

NVIDIA

Accelerated AI-Powered Cybersecurity Modern cybersecurity relies heavily on AI for predictive analytics and automated threat mitigation. NVIDIA GPUs are essential for training and deploying AI models due to their exceptional computational power. Read the NVIDIA AI Enterprise security white paper to learn more.

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LLMWare Introduces Model Depot: An Extensive Collection of Small Language Models (SLMs) for Intel PCs

Marktechpost

Similarly, ONNX provides an open-source format for AI models, both deep learning and traditional ML, with a current focus on the capabilities needed for inferencing. The processing time shows the total runtime for all 21 questions: Detailed information about LLMWare ’s testing methodology can be found in the white paper.

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Embedding secure generative AI in mission-critical public safety applications

Flipboard

By embedding advanced AI into their cloud-native platform, Mark43 enables officers to receive instant answers to natural language queries and automated case report summaries, reducing administrative time from minutes to seconds. Visit the Amazon Q Business User Guide to learn more about how to embed generative AI into your applications.