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Ordnance Survey: Navigating the role of AI and ethical considerations in geospatial technology

AI News

As we approach a new year filled with potential, the landscape of technology, particularly artificial intelligence (AI) and machine learning (ML), is on the brink of significant transformation. This focus on ethics is encapsulated in OSs Responsible AI Charter, which guides their approach to integrating new techniques safely.

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Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

AWS Machine Learning Blog

The rapid advancement of generative AI promises transformative innovation, yet it also presents significant challenges. Concerns about legal implications, accuracy of AI-generated outputs, data privacy, and broader societal impacts have underscored the importance of responsible AI development.

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Advancing AI trust with new responsible AI tools, capabilities, and resources

AWS Machine Learning Blog

As generative AI continues to drive innovation across industries and our daily lives, the need for responsible AI has become increasingly important. At AWS, we believe the long-term success of AI depends on the ability to inspire trust among users, customers, and society.

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Using responsible AI principles with Amazon Bedrock Batch Inference

AWS Machine Learning Blog

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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How to Build a Responsible AI with TensorFlow?

Analytics Vidhya

With the pace at which AI is developing, ensuring the technology is safe has become increasingly important. This is where responsible AI comes into the picture. Responsible AI refers to the sustainable […] The post How to Build a Responsible AI with TensorFlow?

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LLMOps: The Next Frontier for Machine Learning Operations

Unite.AI

Machine learning (ML) is a powerful technology that can solve complex problems and deliver customer value. This is why Machine Learning Operations (MLOps) has emerged as a paradigm to offer scalable and measurable values to Artificial Intelligence (AI) driven businesses.

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Five machine learning types to know

IBM Journey to AI blog

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?