AWS Insights
Author: Dr. Matt Wood
Matt returned to AWS as Chief AI & Technology Officer in May 2026, after almost 15 years at AWS and most recently leading commercial technology and innovation at PwC. During his earlier tenure, he was part of the early AI and machine learning organization and worked across foundational AWS services, helping build, launch, or scale products including Amazon Bedrock, SageMaker, Lambda, Kinesis, and QuickSight. Today, Matt works with customers, builders, partners, and AWS teams to help turn AI from possibility into production. His focus is on where the technology is going, how customers can put it to work, and what it takes to build durable products, platforms, and businesses on top of it. He has spent his career bringing ideas to life through technology, and believes the next era of AWS will be shaped by inventors and builders who use AI to reinvent products, services, and experiences. Matt holds a PhD in machine learning, attended medical school at the University of Nottingham, and completed a postdoctoral fellowship at Weill Cornell Medicine, where his research focused on natural language processing and bioinformatics.
Your last hardware decision shouldn’t decide what you build next.
AWS launched TorchNeuron, which developers can use to run their existing PyTorch code natively on AWS Trainium with a configuration change instead of a rewrite. Making it cheaper to move between AI chips reshapes not just cost, but what teams can choose to build next.
Wrong, not broken
Software operations has always asked one question: Is it broken? AI agents change that. Here’s the shift toward measuring correctness at the level of the run, and the thinking behind Amazon CloudWatch Omni.