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
7 Essential Python Itertools for Feature Engineering
Feature engineering is where most of the real work in machine learning happens.
7 Essential Python Itertools for Feature Engineering
Feature engineering is where most of the real work in machine learning happens.
Entropy-Preserving Reinforcement Learning
Policy gradient algorithms have driven many recent advancements in language model reasoning. An appealing property is their ability to learn from exploration on their own trajectories, a process crucial for fostering diverse and creative solutions. As we show in this paper, many policy gradient algorithms naturally reduce the entropy—and thus…
How Ring scales global customer support with Amazon Bedrock Knowledge Bases
This post is cowritten with David Kim, and Premjit Singh from Ring. Scaling self-service support globally presents challenges beyond translation. In this post, we show you how Ring, Amazon’s home security subsidiary, built a production-ready, multi-locale Retrieval-Augmented Generation (RAG)-based support chatbot using Amazon Bedrock Knowledge Bases. By eliminating per-Region infrastructure…