AWS Batch now supports Amazon SageMaker Training jobs, enabling customers to manage and scale machine learning training workloads without building infrastructure. With the introduction of quota management in AWS Batch, administrators can divide and share GPU resources among teams or projects, maximizing utilization and prioritizing workloads. Quota shares include capacity limits and resource-sh...
MoEngage, a customer engagement platform used by over 1,350 consumer brands, faced a challenge when building AI agents that required access to internal APIs. These APIs, numbering around 400, already existed but needed to be safely accessible to agents without being exposed to the public internet, controlling identity, and without overwhelming context windows with hundreds of tool definitions. ...
A data scientist shares their experience of implementing kernel support vector regression (SVR) from scratch using Python, opting for stochastic gradient descent (SGD) instead of the commonly used SMO algorithm. They note the complexity of SMO and caution about incorrect information on SVR and SMO. The demo involves synthetic data, and the SGD-trained SVR model is shown to yield comparable resu...
In the context of expanding quality assurance (QA) automation adoption within an organization, new challenges emerge as teams attempt to manage and organize an increasing number of tests for various applications. The author explores a solution called QA Studio, which facilitates defining tests in natural language and running them through AI-powered visual navigation. In this post, the focus shi...
Infrastructure has continually evolved in tandem with technological advancements throughout history. From the construction of dams, bridges, and canals during the 18th century to the development of railways, sewage systems, and megacities' infrastructure in the 20th century, each technological shift brought about new types and scales of infrastructure. Today, the definition of infrastructure ex...
The article discusses the challenge of scaling PyTorch training on a cluster, which is primarily caused by the complexity of building and maintaining the required containers. This involves ensuring that every container has the same CUDA runtime, PyTorch build, NCCL, EFA libraries, and AWS OFI NCCL plugin. To address this issue, AWS introduced the Ray Train Deep Learning Container (DLC), which i...
NVIDIA's RTX Spark powers new thin and light laptops from major manufacturers, including ASUS, Dell, HP, Lenovo, Microsoft, and MSI. These systems are equipped with an NVIDIA Blackwell RTX GPU and Grace CPU in a single superchip, offering up to 128GB of unified memory and up to 1 petaflop of FP4 AI performance. RTX Spark includes features like NVIDIA's CUDA platform, RTX graphics, and personal ...
Meta's Privacy Aware Infrastructure (PAI) introduces PrivacyLib, a common library used for enforcing and monitoring data flows in the final stage of PAI workflow. Previously, new privacy requirements meant integrating privacy enforcement separately into each data and processing system, leading to a lengthy process. PrivacyLib allows system integration once, with new privacy capabilities as modu...
Amazon Web Services (AWS) has been named a leader in Gartner's 2026 Magic Quadrant for Contact Center as a Service (CCaaS) for the fourth consecutive year for Amazon Connect. Amazon Connect Customer is designed to deliver personalized, intelligent experiences without sacrificing efficiency, flexibility, or control. The solution builds a comprehensive picture of every customer, uses AI to unders...
Amazon SageMaker's new SOCI (Seekable OCI) indexing for AI Training and Processing jobs allows for lazy loading of container images, reducing image download time from minutes to seconds. SOCI indexing is an open-source technology that maps every file inside an image and stores it in Amazon ECR as a separate artifact. SageMaker checks for the index automatically and behaves accordingly, either l...
MIT Professor Paris Smaragdis, a musician and computer scientist, is on a mission to enhance machine hearing. He aims to develop machines with superior hearing capabilities, enabling them to locate sounds such as traffic accidents or industrial drill malfunctions. Smaragdis, a Greek native, discovered his fascination with sound and technology at a young age through classical guitar and synthesi...
Exowatt, a company specializing in modular, dispatchable solar systems, uses advanced technology to harness solar energy, store it as heat, and generate electricity on demand for energy-intensive applications like AI data centers. To optimize operations, they've implemented an AI system for real-time alarm triage and decision-making at the edge, where connectivity and resources are limited. Tra...
In this post, we share the story of Property Finder, a digital real estate application, where 96.8% of their evaluation labels were found to be inherited from a single model's predictions rather than verified by human experts, leading to systemic bias and inaccurate comparisons of alternative models. Property Finder, which processes thousands of property images daily across the Middle East and ...
The author implemented a decision tree regression system using JavaScript and used an AI system to analyze its correctness. The AI discovered edge cases where the code might fail and suggested improvements for enhanced performance. After extensive efforts, a revised version of the JavaScript decision tree regression was developed, leading to a synthetic dataset with 220 items as an example. Key...
In this text, the author explains the concept of an "AI agent" and how it faces the same issue as the character in the movie "Groundhog Day," where it must re-read its entire story before performing an action. This leads to high costs due to repeated inputs. The author then introduces "prompt caching," a solution where previously processed inputs are saved and reused, reducing costs and maintai...