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Differentially private heatmaps

Posted by Badih Ghazi, Staff Research Scientist, and Nachiappan Valliappan, Staff Software Engineer, Google Research Recently, differential privacy (DP) has emerged as a mathematically robust notion of user privacy for data aggregation and machine learning (ML), with practical deployments including the 2022 US Census and in industry. Over the last few years, we have open-sourced …

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Financial text generation using a domain-adapted fine-tuned large language model in Amazon SageMaker JumpStart

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more. With access to massive amounts of data, LLMs have the potential to revolutionize the way we …

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Three ways media leaders can leverage generative AI

The digital era turned the traditional formula for media and entertainment success on its head, ushering in new technologies that have changed how content is produced, distributed, experienced, and monetized. Audiences have more choice, flexibility, and power over what they consume, and today’s media companies have to embrace ongoing transformation or risk falling behind – …

FaceLit: Neural 3D Relightable Faces

We propose a generative framework, FaceLit, capable of generating a 3D face that can be rendered at various user-defined lighting conditions and views, learned purely from 2D images in-the-wild without any manual annotation. Unlike existing works that require careful capture setup or human labor, we rely on off-the-shelf pose and illumination estimators. With these estimates, …

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Deploy large models at high performance using FasterTransformer on Amazon SageMaker

Sparked by the release of large AI models like AlexaTM, GPT, OpenChatKit, BLOOM, GPT-J, GPT-NeoX, FLAN-T5, OPT, Stable Diffusion, and ControlNet, the popularity of generative AI has seen a recent boom. Businesses are beginning to evaluate new cutting-edge applications of the technology in text, image, audio, and video generation that have the potential to revolutionize …

Revolutionizing the consumer goods industry with integrated business planning

The world of business demands the right decisions to succeed. For Al Rabie—a prominent juice manufacturing company in the Middle East—their reality was no different. However, their manual planning and budgeting process in spreadsheets posed several challenges, including lack of control, delayed data, poor execution, and the need for continuous follow-up with IT for actual …

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Beyond automatic differentiation

Posted by Matthew Streeter, Software Engineer, Google Research Derivatives play a central role in optimization and machine learning. By locally approximating a training loss, derivatives guide an optimizer toward lower values of the loss. Automatic differentiation frameworks such as TensorFlow, PyTorch, and JAX are an essential part of modern machine learning, making it feasible to …

Angler: Helping Machine Translation Practitioners Prioritize Model Improvements

*=Authors contributed equally Machine learning (ML) models can fail in unexpected ways in the real world, but not all model failures are equal. With finite time and resources, ML practitioners are forced to prioritize their model debugging and improvement efforts. Through interviews with 13 ML practitioners at Apple, we found that practitioners construct small targeted …

5 takeaways from the early days of IBM Partner Plus

The past three months have been transformative for the IBM Ecosystem. Our investment in the ecosystem is deeper than ever before, and momentum is accelerating across all partner types as they continue to scale and innovate. This demonstrates their commitment to clients, deep expertise and hunger to collaborate and co-create with us. Thanks to each …