AI

Using Amazon SageMaker Pipelines, organizations can automate their machine learning (ML) workloads and distribute them over many AWS accounts and AWS Regions as part of their Machine Learning Operations (MLOps) strategy. However, monitoring SageMaker Pipelines can become complex when they are distributed across many AWS environments. Developers and operations engineers must manually switch between multiple […]

Inkling, a 975-billion-parameter open source model, was trained to understand video and audio. It could help Thinking Machines establish itself among competitors like Anthropic and OpenAI.

Treadwell brings nearly a decade of experience running Amazon’s technology platform to his new role.

Gidi Littwin’s new AI startup, Hemispheric, makes diagnostic brain scans for conditions like depression, PTSD, and Parkinson’s. He wants the technology to be as cheap and easy as a blood test.

Companies’ increasing reliance on AI chatbots isn’t making the customer service experience smarter. It’s just making it more infuriating.

OpenAI employees have donated more than $215,000 to a political effort opposing Leading the Future, a group backed by the company’s president, Greg Brockman.

Systems using artificial intelligence to enhance forecasting, planning, and decision-making in businesses have been proliferating in recent years, but in many cases, they lack the detailed, specific information about the organization itself, limiting the usefulness of those tools.  Devavrat Shah, a principal investigator at MIT’s Laboratory for Information and Decision Systems (LIDS), faculty member with

Your prospects leave trails across multiple sources: a founder asks “What should I use for X?” in r/SaaS while their product launches on Hacker News. Stack Overflow questions spike. A GitHub repo crosses 2,400 stars. Each signal alone is noise, but correlated across sources, they reveal a prospect ready to buy. Multi-agent systems built with

Artificial intelligence has rapidly transformed software engineering. Generative AI and large language models (LLMs) can create huge volumes of code and documentation; machine-learning algorithms can monitor performance and detect security vulnerabilities. But when the task is to conceive, design, and make a complex physical system such as a jet engine, are those AI tools equally

Production quality assurance (QA) workflows require more than individual test execution. You must organize tests into regression suites that run as a batch, and integrate them into continuous integration and continuous delivery (CI/CD) pipelines so that test results gate deployments automatically. In a previous post, we introduced QA Studio, a reference solution for agentic QA