Promoting Cross-Modal Representations to Improve Multimodal Foundation Models for Physiological Signals

Many healthcare applications are inherently multimodal, involving several physiological signals. As sensors for these signals become more common, improving machine learning methods for multimodal healthcare data is crucial. Pretraining foundation models is a promising avenue for success. However, methods for developing foundation models in healthcare are still in early exploration and it is unclear which …

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Import data from Google Cloud Platform BigQuery for no-code machine learning with Amazon SageMaker Canvas

In the modern, cloud-centric business landscape, data is often scattered across numerous clouds and on-site systems. This fragmentation can complicate efforts by organizations to consolidate and analyze data for their machine learning (ML) initiatives. This post presents an architectural approach to extract data from different cloud environments, such as Google Cloud Platform (GCP) BigQuery, without …

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‘India Should Manufacture Its Own AI,’ Declares NVIDIA CEO

Artificial intelligence will be the driving force behind India’s digital transformation, fueling innovation, economic growth, and global leadership, NVIDIA founder and CEO Jensen Huang said Thursday at NVIDIA’s AI Summit in Mumbai. Addressing a crowd of entrepreneurs, developers, academics and business leaders, Huang positioned AI as the cornerstone of the country’s future. India has an …

Smart Audit System Empowered by LLM

Manufacturing quality audits are pivotal for ensuring high product standards in mass production environments. Traditional auditing processes, however, are labor-intensive and heavily reliant on human expertise, posing challenges in maintaining transparency, accountability, and continuous improvement across complex global supply chains. To address these challenges, we propose a smart audit system empowered by large language models …

Divide-or-Conquer? Which Part Should You Distill Your LLM?

Recent methods have demonstrated that Large Language Models (LLMs) can solve reasoning tasks better when they are encouraged to solve subtasks of the main task first. In this paper we devise a similar strategy that breaks down reasoning tasks into a problem decomposition phase and a problem solving phase and show that the strategy is …

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How Planview built a scalable AI Assistant for portfolio and project management using Amazon Bedrock

This post is co-written with Lee Rehwinkel from Planview. Businesses today face numerous challenges in managing intricate projects and programs, deriving valuable insights from massive data volumes, and making timely decisions. These hurdles frequently lead to productivity bottlenecks for program managers and executives, hindering their ability to drive organizational success efficiently. Planview, a leading provider …

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AI Hypercomputer software updates: Faster training and inference, a new resource hub, and more

The potential of AI has never been greater, and infrastructure plays a foundational role in driving it forward. AI Hypercomputer is our supercomputing architecture based on performance-optimized hardware, open software, and flexible consumption models. Together, these offer exceptional performance and efficiency, resiliency at scale, and give you the flexibility to choose offerings at each layer …

Combining Machine Learning and Homomorphic Encryption in the Apple Ecosystem

At Apple, we believe privacy is a fundamental human right. Our work to protect user privacy is informed by a set of privacy principles, and one of those principles is to prioritize using on-device processing. By performing computations locally on a user’s device, we help minimize the amount of data that is shared with Apple …

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Super charge your LLMs with RAG at scale using AWS Glue for Apache Spark

Large language models (LLMs) are very large deep-learning models that are pre-trained on vast amounts of data. LLMs are incredibly flexible. One model can perform completely different tasks such as answering questions, summarizing documents, translating languages, and completing sentences. LLMs have the potential to revolutionize content creation and the way people use search engines and …

Adapting model risk management for financial institutions in the generative AI era

Generative AI (gen AI) promises to usher in an era of transformation for quality, accessibility, efficiency, and compliance in the financial services industry. As with any new technology, it also introduces new complexities and risks. Striking a balance between harnessing its potential and mitigating its risks will be crucial for the adoption of gen AI …