When a network fails, the bottleneck is not engineering expertise. It is cognitive overload. A new approach augments a network graph with agentic AI to produce a "digital twin" that can help isolate network failures. The system runs a three-stage cascade of graph algorithms: decomposition narrows thousands of candidate nodes to hundreds, community detection clusters those to tens, and topology-aware centrality ranking identifies the most likely root cause. The key shift is conditioning every centrality measure on the specific failure, not the full graph. Personalized PageRank seeds random walks from nodes that are issuing alarms. Degree centrality counts only edges to those nodes. Closeness measures distance to the failure cluster, not the geometric center: https://amzn.to/4s8P0lr
Amazon Science
Research Services
Seattle, Washington 396,443 followers
The latest news and research from Amazon’s science community. #AmazonScience
About us
Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Follow us on LinkedIn and visit our website to get a deep dive on innovation at Amazon, and explore the many ways you can engage with our scientific community. #AmazonScience
- Website
-
https://www.amazon.science
External link for Amazon Science
- Industry
- Research Services
- Company size
- 10,001+ employees
- Headquarters
- Seattle, Washington
- Founded
- 2020
- Specialties
- Artificial Intelligence, Machine Learning, Computer Vision, Cloud, Economics, Sustainability, AI, ML, Conversational AI, Natural Language Processing, NLP, Robotics, Security, Privacy, Information, Knowledge Management, Operations, Scientific Research, Search, Amazon, and Alexa
Updates
-
The biggest barrier to adopting new AI hardware is the months spent rewriting and revalidating code that already works. Announcing TorchNeuron, which lets PyTorch code run natively on AWS Trainium chips with a single configuration change. No rewrite, and the tools developers already use to test, debug, and scale their models all work on Trainium without modification. Startups and enterprises in robotics, video, world models, self-driving cars, speech, drug discovery, LLMs, and finance are already building on it. TorchNeuron will be open sourced at the PyTorch Conference on October 20: https://amzn.to/4icd1Ut
-
Building trust into computing grows more urgent as AI becomes more autonomous and systems become more complex. The Amazon Trustworthy Computing Symposium brought together Amazon researchers and academic leaders in Arlington for a day of work on provably correct and secure systems, trustworthy agentic AI, and privacy-preserving technology. Across every topic, the same principle held: rigor is required at every layer, from hardware foundations to the safeguards governing autonomous agents. Thank you to all the speakers and participants for a day of meaningful research exchange. Nickolai Zeldovich Ruzica Piskac Ioana Boureanu Carlson Lingming Zhang Amin Kharraz Yiling Lou Yuan Tian Joe Calandrino Baris Coskun Jim Grundy Boaz Barak
-
-
-
-
-
+3
-
-
AI-powered smart glasses are helping Amazon delivery drivers navigate hands-free, using computer vision and real-time sensing to guide them from van to the customer's doorstep. Yelin Kim, who leads computer vision and machine learning science for Amazon’s Last Mile AR delivery glasses, talks about the edge AI behind them and what it means for human-centered design. Hear more at COLM this week. #COLM2026
-
This week, Amazon researchers are presenting work at COLM 2026 across agentic AI, constrained decoding, retrieval optimization, and LLM code generation. Explore the research: https://amzn.to/4j2c8jc #COLM2026
-
Amazon and the Georgia Institute of Technology launched a joint science hub to support research in robotics, industrial and systems engineering, aerospace technology, and innovation in foundational and emerging technologies. Georgia Tech researchers will also use Sprout, the robotics development platform from Fauna Robotics, to advance work in human-robot interaction and perception. Leadership and GT alumni marked the initiative at Lab 126 last week alongside Sprout and Buzz, the GT mascot: https://amzn.to/47yynWW
-
-
Announcing the Amazon Research Awards fall 2026 call for proposals across nine research areas. Successful applicants receive unrestricted funds, AWS promotional credits, and training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers. Deadline for submissions is November 4: https://amzn.to/4AQbKef
-
-
Amazon researchers are presenting work at the Conference on Language Modeling (COLM) in San Francisco next week spanning agentic AI, LLM post-training, multi-agent systems, and automated reasoning. Stop by our booth for talks, meet-the-scientist sessions, and conversations with our team. See our accepted publications and full booth schedule: https://amzn.to/4jvZr0a
-