Remove AI Development Remove Data Ingestion Remove Large Language Models
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The importance of data ingestion and integration for enterprise AI

IBM Journey to AI blog

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. In the generative AI or traditional AI development cycle, data ingestion serves as the entry point.

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Databricks + Snorkel Flow: integrated, streamlined AI development

Snorkel AI

In todays fast-paced AI landscape, seamless integration between data platforms and AI development tools is critical. At Snorkel, weve partnered with Databricks to create a powerful synergy between their data lakehouse and our Snorkel Flow AI data development platform. Sign up here!

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Upstage AI Introduces Dataverse for Addressing Challenges in Data Processing for Large Language Models

Marktechpost

With the incorporation of large language models (LLMs) in almost all fields of technology, processing large datasets for language models poses challenges in terms of scalability and efficiency. If you like our work, you will love our newsletter.

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Unlock proprietary data with Snorkel Flow and Amazon SageMaker

Snorkel AI

Large language models (LLMs) fine-tuned on proprietary data have become a competitive differentiator for enterprises. Snorkel Flow: the AI data development platform Snorkel Flow accelerates AI development by focusing on data development.

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Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

AWS Machine Learning Blog

SnapLogic , a leader in generative integration and automation, has introduced the industry’s first low-code generative AI development platform, Agent Creator , designed to democratize AI capabilities across all organizational levels.

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Databricks + Snorkel Flow: integrated, streamlined AI development

Snorkel AI

In todays fast-paced AI landscape, seamless integration between data platforms and AI development tools is critical. At Snorkel, weve partnered with Databricks to create a powerful synergy between their data lakehouse and our Snorkel Flow AI data development platform. Sign up here!

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Generative AI operating models in enterprise organizations with Amazon Bedrock

AWS Machine Learning Blog

Three common operating model patterns are decentralized, centralized, and federated, as shown in the following diagram. Decentralized model In a decentralized approach, generative AI development and deployment are initiated and managed by the individual LOBs themselves.