AI

“Manufacturing is the engine of society, and it is the backbone of robust, resilient economies,” says John Hart, head of MIT’s Department of Mechanical Engineering (MechE) and faculty co-director of the MIT Initiative for New Manufacturing (INM). “With manufacturing a lively topic in today’s news, there’s a renewed appreciation and understanding of the importance of […]

Is this movie review a rave or a pan? Is this news story about business or technology? Is this online chatbot conversation veering off into giving financial advice? Is this online medical information site giving out misinformation? These kinds of automated conversations, whether they involve seeking a movie or restaurant review or getting information about

Researchers studying the emotional impact of tools like ChatGPT propose a new kind of benchmark that measures a models’ emotional and social impact.

At Amazon, our team builds Rufus, a generative AI-powered shopping assistant that serves millions of customers at immense scale. However, deploying Rufus at scale introduces significant challenges that must be carefully navigated. Rufus is powered by a custom-built large language model (LLM). As the model’s complexity increased, we prioritized developing scalable multi-node inference capabilities that

Agentic AI is revolutionizing the financial services industry through its ability to make autonomous decisions and adapt in real time, moving well beyond traditional automation. Imagine an AI assistant that can analyze quarterly earnings reports, compare them against industry expectations, and generate insights about future performance. This seemingly straightforward task involves multiple complex steps: document

AI assistants that forget what you told them 5 minutes ago aren’t very helpful. While large language models (LLMs) excel at generating human-like responses, they are fundamentally stateless—they don’t retain information between interactions. This forces developers to build custom memory systems to track conversation history, remember user preferences, and maintain context across sessions, often solving

Data analysis often presents significant challenges for business users who aren’t proficient in SQL. Traditional methods require technical expertise to query databases, leading to delayed insights and dependence on data teams. Many organizations struggle with making their data accessible to business users while maintaining the analytical capabilities of Amazon Athena. Modern AI agents are transforming

Imagine harnessing the power of 72 cutting-edge NVIDIA Blackwell GPUs in a single system for the next wave of AI innovation, unlocking 360 petaflops of dense 8-bit floating point (FP8) compute and 1.4 exaflops of sparse 4-bit floating point (FP4) compute. Today, that’s exactly what Amazon SageMaker HyperPod delivers with the launch of support for

This post is co-written with Rudra Kannemadugu and Shravan K S from Indegene Limited. In today’s digital-first world, healthcare conversations are increasingly happening online. Yet the life sciences industry has struggled to keep pace with this shift, facing challenges in effectively analyzing and deriving insights from complex medical discussions on a scale. This post will

This post is co-authored with Karsten Weber and Rosary Wang from Lexbe. Legal professionals are frequently tasked with sifting through vast volumes of documents to identify critical evidence for litigation. This process can be time-consuming, prone to human error, and expensive—especially when tight deadlines loom. Lexbe, a leader in legal document review software, confronted these