CRM

How to Use the Python Connector for Data Cloud

The ability to efficiently access data wherever it resides is crucial when building visual data models, performing analytical operations, or building machine learning models. The Data Cloud Python Connector abstracts Data Cloud’s Query APIs to help developers quickly authenticate and access data within Data Cloud. In this blog post, we’ll delve into the key features […]

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Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts

TL;DR: We propose Moirai-MoE, the first mixture-of-experts time series foundation model, achieving token-level model specialization in a data-driven manner. Extensive experiments on 39 datasets reveal that Moirai-MoE delivers up to 17% performance improvements over Moirai at the same level of model size and outperforms other time series foundation models, such as Chronos (from Amazon) and

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3 Ways Life Sciences Organizations Can Use AI Today

Artificial intelligence (AI) for life sciences has the potential to help your organization make better decisions by integrating into daily workflows for healthier businesses and better outcomes. From process automation and predictive intelligence to generative and agentic AI, an industry-specific AI-powered CRM platform can provide the essential tools for Pharma and MedTech companies to easily

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3 Ways Connected Assets Can Transform Your Manufacturing Operations

As the manufacturing industry continues to evolve at a rapid pace, staying ahead of the curve is essential. Operational transformation is top of mind for manufacturers, according to our latest Trends in Manufacturing report — 85% of manufacturers believe they must transform their day-to-day operations to remain competitive. One of the most promising developments that

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Transforming Telecom Maintenance: How AI Streamlines Asset Management

There’s a major shift underway in field service in the communications industry – a move away from traditional, reactive models toward proactive and predictive. The way telecom asset management has traditionally been handled – equipment would break, and the service team would respond – is inefficient, costly, and leads to significant downtime. In telecommunications, where

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