Apple Machine Learning Research This research aims to comprehensively explore building a multimodal foundation model for egocentric video understanding. To achieve this goal, we work on three fronts. First, as there is a lack of QA data for egocentric video understanding, we automatically generate 7M high-quality QA samples for egocentric videos ranging from 30 seconds […]Continue reading

Apple Machine Learning Research Large generative models are becoming increasingly capable and more widely deployed to power production applications, but getting these models to produce exactly what’s desired can still be challenging. Fine-grained control over these models’ outputs is important to meet user expectations and to mitigate potential misuses, ensuring the models’ reliability and safety. […]Continue reading

AWS Machine Learning Blog Training a frontier model is highly compute-intensive, requiring a distributed system of hundreds, or thousands, of accelerated instances running for several weeks or months to complete a single job. For example, pre-training the Llama 3 70B model with 15 trillion training tokens took 6.5 million H100 GPU hours. On 256 Amazon […]Continue reading

Apple Machine Learning Research Instruction-following is crucial for building AI agents with large language models (LLMs), as these models must adhere strictly to user-provided constraints and guidelines. However, LLMs often fail to follow even simple and clear instructions. To improve instruction-following behavior and prevent undesirable outputs, a deeper understanding of how LLMs’ internal states relate […]Continue reading

Apple Machine Learning Research There is a gap between finding a first-order stationary point (FOSP) and a second-order stationary point (SOSP) under differential privacy constraints, and it remains unclear whether privately finding an SOSP is more challenging than finding an FOSP. Specifically, Ganesh et al. (2023) claimed that an αalphaα-SOSP can be found with α=O~(1n1/3+(dnϵ)3/7)alpha=tilde{O}(frac{1}{n^{1/3}}+(frac{sqrt{d}}{nepsilon})^{3/7})α=O~(n1/31​+(nϵd​​)3/7), […]Continue reading

Apple Machine Learning Research We present RelCon, a novel self-supervised Relative Contrastive learning approach for training a motion foundation model from wearable accelerometry sensors. First, a learnable distance measure is trained to capture motif similarity and domain-specific semantic information such as rotation invariance. Then, the learned distance provides a measurement of semantic similarity between a […]Continue reading

AWS Machine Learning Blog As businesses and developers increasingly seek to optimize their language models for specific tasks, the decision between model customization and Retrieval Augmented Generation (RAG) becomes critical. In this post, we seek to address this growing need by offering clear, actionable guidelines and best practices on when to use each approach, helping […]Continue reading

AWS Machine Learning Blog Today, businesses are using AI and generative models to improve productivity in their teams and provide better experiences to their customers. Personalized outbound communication can be a powerful tool to increase user engagement and conversion. For instance, as a marketing manager for a video-on-demand company, you might want to send personalized […]Continue reading

AWS Machine Learning Blog Today, we are excited to announce that Mistral AI’s Pixtral Large foundation model (FM) is generally available in Amazon Bedrock. With this launch, you can now access Mistral’s frontier-class multimodal model to build, experiment, and responsibly scale your generative AI ideas on AWS. AWS is the first major cloud provider to […]Continue reading

AWS Machine Learning Blog Financial institutions today face an increasingly complex regulatory world that demands robust, efficient compliance mechanisms. Although organizations traditionally invest countless hours reviewing regulations such as the Anti-Money Laundering (AML) rules and the Bank Secrecy Act (BSA), modern AI solutions offer a transformative approach to this challenge. By using Amazon Bedrock Knowledge […]Continue reading

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