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Jesse Korosi, Thijs van de Kamp, Mayra Vega, Laura Futuro, Anton Margoline The journey from script to screen is full of challenges in the ever-evolving world of film and television. The industry has always innovated, and over the last decade, it started moving towards cloud-based workflows. However, unlocking cloud innovation and all its benefits on …
Read more “Globalizing Productions with Netflix’s Media Production Suite”
This post is co-authored with Joao Moura and Tony Kipkemboi from CrewAI. The enterprise AI landscape is undergoing a seismic shift as agentic systems transition from experimental tools to mission-critical business assets. In 2025, AI agents are expected to become integral to business operations, with Deloitte predicting that 25% of enterprises using generative AI will …
Read more “Build agentic systems with CrewAI and Amazon Bedrock”
By Ko-Jen Hsiao, Yesu Feng and Sudarshan Lamkhede Motivation Netflix’s personalized recommender system is a complex system, boasting a variety of specialized machine learned models each catering to distinct needs including “Continue Watching” and “Today’s Top Picks for You.” (Refer to our recent overview for more details). However, as we expanded our set of personalization …
Read more “Foundation Model for Personalized Recommendation”
Amazon Bedrock Guardrails announces the general availability of image content filters, enabling you to moderate both image and text content in your generative AI applications. Previously limited to text-only filtering, this enhancement now provides comprehensive content moderation across both modalities. This new capability removes the heavy lifting required to build your own image safeguards or …
When implementing machine learning (ML) workflows in Amazon SageMaker Canvas, organizations might need to consider external dependencies required for their specific use cases. Although SageMaker Canvas provides powerful no-code and low-code capabilities for rapid experimentation, some projects might require specialized dependencies and libraries that aren’t included by default in SageMaker Canvas. This post provides an …
Read more “Integrating custom dependencies in Amazon SageMaker Canvas workflows”
Amazon SageMaker JumpStart is a machine learning (ML) hub that provides pre-trained models, solution templates, and algorithms to help developers quickly get started with machine learning. Within SageMaker JumpStart, the private model hub feature allows organizations to create their own internal repository of ML models, enabling teams to share and manage models securely within their …
Read more “Amazon SageMaker JumpStart adds fine-tuning support for models in a private model hub”
Gemini 2.5 is our most intelligent AI model, now with thinking built in.
Data augmentation is crucial to make machine learning models more robust and safe. However, augmenting data can be challenging as it requires generating diverse data points to rigorously evaluate model behavior on edge cases and mitigate potential harms. Creating high-quality augmentations that cover these “unknown unknowns” is a time- and creativity-intensive task. In this work, …
Read more “Exploring Empty Spaces: Human-in-the-Loop Data Augmentation”
Amazon Bedrock announces the preview launch of Session Management APIs, a new capability that enables developers to simplify state and context management for generative AI applications built with popular open source frameworks such as LangGraph and LlamaIndex. Session Management APIs provide an out-of-the-box solution that enables developers to securely manage state and conversation context across …
Read more “Amazon Bedrock launches Session Management APIs for generative AI applications (Preview)”
Over the past decade, AI has evolved at a breakneck pace, turning from a futuristic dream into a tool now accessible to everyone. One of the technologies that opened up this new era of AI was Ray. As the open-source AI Compute Engine, Ray has made it easier for developers to scale the most complex …
Read more “Anyscale powers AI compute for any workload using Google Compute Engine”