The use of algorithms to design structures has led to new parts optimized for ultralight aircraft, high-bandwidth antennas, and F1 racing cars. But the best algorithmic design techniques still require lots of computation and time: Users only see the final design after it’s complete, after which they often must start the design process all over again to make changes. That process also makes i...
Today, Amazon announced that SGLang-Neuron is publicly available and can be accessed through an AWS Deep Learning Container, released by RadixArk in collaboration with Annapurna Labs. With SGLang-Neuron, you can serve models and generate reinforcement learning (RL) rollouts with SGLang on AWS Trainium using the same SGLang interface you use today. Trainium is a portfolio of AWS AI chips that...
Most AI coworker products are vendor locked. They pick the model, host the data, and write the rules. CopilotKit is taking the opposite route. OpenBot 1. 0, was released November 9th, an MIT-licensed, self-hostable agent workspace. What sets it apart is, a company brings their own models, agents and infrastructure. Governance is fully baked in, and every Bot action is checked against a polic...
Despite fears about robots replacing humans at work, there are still plenty of things humans can do far better than machines. That’s fine with Robust AI, a startup building robots designed to complement what humans do best. The company’s mobile robot, named Carter, resembles a utility cart on wheels and is designed to fit seamlessly alongside humans in fast-changing warehouse and factory env...
Three technologies developed by MIT Lincoln Laboratory are among recipients of 2026 R&D 100 Awards. The awards recognize the 100 most significant innovations that have transitioned to use or been made available for license in the past year. R&D World, an online publication, manages the awards program, which has run annually since 1963. The worldwide competition is judged by an indepe...
More enterprises are building AI agents into their daily work, and a common pattern is an agent that searches internal documents to compose its answers. A single organization might soon run hundreds of agents, each connected to many data sources and tools. This raises a question. When an agent searches on behalf of a user, can you make sure that it uses only the information that user is allo...
Accurate, up-to-date climate projections are essential for planning decisions that enhance the resilience of power grids, protect public health, maximize agricultural yields, and more. Now, MIT researchers have developed a technique that streamlines the production of fast, trustworthy, and adaptable artificial intelligence models for climate prediction. These specialized AI models, known as ...
In code review, using a textual difference between files can be misleading due to syntactic changes that don't affect meaning. A semantic diff, computed using anti-unification, identifies shared parts and disagreements between policies. This is useful when generating formal language models from natural language or comparing different policy formats like Cedar, Dogwood, or OpenShell policies. Ag...
Overcoming Unnoticed Data Corruption in Amazon SageMaker HyperPod: Detection and Recovery Strategies
Silent data corruption (SDC) in machine learning training occurs when hardware, such as a GPU, returns incorrect but plausible numbers without raising errors. This can lead to the propagation of incorrect data into gradients and weights in distributed training, resulting in a weaker model or unexplained divergence. Detection of SDC is challenging as it does not trigger hardware errors and can s...
In this post, you will discover how reusable assets from the AWS Generative AI Innovation Center can help reduce development time and costs for generative AI solutions. These assets, including Retrieval Augmented Generation pipelines, document processors, and agent scaffolding, can save teams months of development time as shown by companies like DoorDash, Lyft, and Ricoh. The post also explains...
From November 30th to December 4th, Amazon Web Services (AWS) will hold its annual premier learning event: re:Invent. At this event, attendees will become stronger and more proficient in various areas of AWS technology through a variety of experiences: keynotes given by AWS leaders, interactive working sessions led by AWS experts, and fun, immersive activities such as live entertainment and ...
In this summary, I will describe a solution for observability data lake needs in Amazon Bedrock workloads. When running multiple model invocations daily across different accounts, it becomes challenging to understand what happened after a request was sent. Questions arise, such as which prompt was used, the model response, token usage, handling model, and response quality. As a platform or ML e...
Tata Consultancy Services (TCS) identified that for Banking, Financial Services, and Insurance (BFSI) clients, the slowest part of a release is not writing application code, but rather the chain of work that follows. This includes interpreting requirements, designing scenarios, writing and maintaining automation, preparing execution environments, investigating failures, and assembling evidence ...
In the given study, the author explores the performance of two encoding techniques for tree-based machine learning models, focusing on gradient boosting regression with decision tree weak learners. The first technique, referred to as super simple, uses ordinal encoding for categorical variables. The second technique, referred to as complex, employs smoothed-target encoding for continuous variab...
Moonshot AI's new post-trained version of Kimi K3.1, named Kimi K3.1 Pro Highspeed, is now accessible on Amazon Bedrock. With the same open-weight architecture and context window, this upgraded model benefits from additional post-training compute, focusing on long-horizon tasks and reducing factual errors. It enhances professional functions, including financial modeling and document processing,...