AI content generation is about feeding your AI models with semantic and contextual information. The result is a platform that can ‘understand’ what an item is, and how it should be used. AI creates content using semantic knowledge in any form of content including video, 3d, VR and more.
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Latest Artificial Intelligence Content News
Integrating Netflix’s Foundation Model into Personalization applications
Authors: Divya Gadde, Ko-Jen Hsiao, Dhaval Patel and Moumita BhattacharyaThe motivation for building the Netflix Foundation Model for personalization was laid out in this previous blog post. The Netflix homepage is powered by several specialized models and it requires significant time and resources to maintain and continue innovating on these…
Build self-improving document processing using Amazon Bedrock AgentCore
IDC research shows that document-related challenges cost organizations $19,732 for each information worker annually and reduce productivity by 21.3 percent. Organizations receiving invoices from hundreds of suppliers often face layouts that vary by issuer and change without notice. Template-based systems require constant maintenance at this scale. Staff can spend up…
Predictable AI spend in BigQuery: Introducing cost management for generative AI functions
The generative AI functions in BigQuery (AI.GENERATE, AI.IF, AI.CLASSIFY, AI.SCORE, and more) bring large language models (LLMs) directly into your SQL, so a single query can classify millions of support tickets or score each product review for sentiment. However, because these functions are billed by the token, scaling them across…
Trump Aides Admit the House Is a Lost Cause
With the midterm elections just a few weeks away, the White House knows it has to go all in on Senate races—while virtually forfeiting the House.