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To stay competitive, businesses across industries use foundation models (FMs) to transform their applications. Although FMs offer impressive out-of-the-box capabilities, achieving a true competitive edge often requires deep model customization through pre-training or fine-tuning. However, these approaches demand advanced AI expertise, high performance compute, fast storage access and can be prohibitively expensive for many organizations. …

Read more “Generative AI foundation model training on Amazon SageMaker”

At Google Cloud, we’ve taken an open approach in building our Vertex AI platform — to provide the most powerful AI tools available along with unparalleled choice and flexibility. That’s why Vertex AI delivers access to over 160 models — including first-party, open-source, and third-party models — so you can build solutions specifically tailored to …

Read more “Announcing Anthropic’s upgraded Claude 3.5 Sonnet on Vertex AI”

The growing demand for personalized and private on-device applications highlights the importance of source-free unsupervised domain adaptation (SFDA) methods, especially for time-series data, where individual differences produce large domain shifts. As sensor-embedded mobile devices become ubiquitous, optimizing SFDA methods for parameter utilization and data-sample efficiency in time-series contexts becomes crucial. Personalization in time series is …

Read more “Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement”