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Scale Agentic AI Without Lock-In

Scale Agentic AI Without Lock-In

AWS outlines enterprise patterns for operating many agentic AI systems across diverse frameworks, models, and providers. The guidance focuses on preserving flexibility and enabling multi-agent systems to scale together without vendor lock-in.

AWS Machine Learning BlogOfficial12h ago#agentic-ai#multi-agent#vendor-lock-in
Build Agents Where Data Lives

Build Agents Where Data Lives

AWS presents its portfolio of vector search capabilities embedded in existing databases and storage services, eliminating the need for a standalone vector database or data migration. The post compares six purpose-built services and provides a framework for selecting the right vector engine.

AWS Machine Learning BlogOfficial12h ago#vector-search#rag#databases
ByteDance Restructures Seed AI Team

ByteDance Restructures Seed AI Team

ByteDance’s Seed foundation-model division has reportedly completed another internal restructuring. Its foundation-model organization now includes four first-level departments focused on pretraining data, reinforcement learning, product post-training for work, and product post-training for chat.

How LLMs Are Transforming Mental Health Care

How LLMs Are Transforming Mental Health Care

This systematic review examines how large language models support mental-health applications, including social-media analysis, clinical conversational agents, therapy support, and psychoeducation. It also covers multimodal diagnosis, prompt engineering, interpretability, and the ethical and regulatory safeguards needed for responsible deployment.

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