MIT AIWho will benefit from AI?
Examining the potential beneficiaries of AI and its role in enhancing worker productivity and economic prosperity.
PinterestLessons from debugging a tricky direct memory leak
Debugging process and insights for fixing a direct memory leak issue in a large-scale distributed system using Apache Flink
DuolingoWhy I chose Duolingo: Parker Henry, Learning Designer
Parker Henry, a Learning Designer, shares his experience at Duolingo
DuolingoMulti-talented, multi-national: why we chose to work on the DET
Exploring the reasons behind the team's decision to work on the DET and its potential impact on higher education worldwide.
Modular AIModular: How to setup a Mojo🔥 development environment with Docker containers
Setting up a development environment for Mojo🔥 using Docker containers
Google AIDynIBaR: Space-time view synthesis from videos of dynamic scenes
A blogpost describing DynIBaR, a method for generating photorealistic free-viewpoint renderings from a single video of a complex, dynamic scene, enabling various video effects such as bullet time, video stabilization, depth of field, and slow motion.
AWS MLAccenture creates a Knowledge Assist solution using generative AI services on AWS
Accenture discusses the development of a Knowledge Assist solution utilizing generative AI services on AWS to address challenges faced by enterprises in leveraging their information and knowledge bases for business operations.
Google AIRe-weighted gradient descent via distributionally robust optimization
The blogpost introduces a variant of the SGD algorithm, called Re-weighted Gradient Descent (RGD), which re-weights data points based on their difficulty during optimization and improves the performance of learning algorithms across various tasks.
AWS MLCreate a Generative AI Gateway to allow secure and compliant consumption of foundation models
Securely and compliantly consume foundation models with a Generative AI Gateway
AWS MLRobust time series forecasting with MLOps on Amazon SageMaker
Robust time series forecasting with MLOps on Amazon SageMaker
AWS MLSpeed up your time series forecasting by up to 50 percent with Amazon SageMaker Canvas UI and AutoML APIs
How to accelerate time series forecasting with Amazon SageMaker Canvas UI and AutoML APIs
Cohere AIIntroducing Chat with Retrieval-Augmented Generation (RAG)
Introducing a Chat API with Retrieval-Augmented Generation (RAG), allowing developers to integrate user inputs, data sources, and model generations for powerful and verifiable product experiences.