The Microsoft CPO says it's possible software engineers will be viewed as "software operators" in the future, but the role is unlikely to disappear.

The traditional architect role no longer fits modern software development and companies started adjusting

Computational efficiency is a significant challenge when scaling solutions to a marketplace as large and as complex as Uber. The running and tuning of the Uber rides business relies on substantial numbers of machine learning models and optimization algorithms. Luckily, many pieces of the system can be treated in parallel. Ray® is a general compute engine for Python® that’s designed for ML, AI, and other algorithmic workloads. We describe how Uber has adopted Ray to enable mission-critical systems. Using Uber’s mobility marketplace allocation tuning system as an example, we found performance improvements of up to 40 times that unlocked new capabilities. It also improved developer productivity by increasing iteration speed, reducing incident mitigation time, and lowering code complexity.

Amazon S3 Tables optimize tabular data storage (like transactions and sensor readings) in Apache Iceberg, enabling high-performance, low-cost queries using Athena, EMR, and Spark.

Agoda recently described their innovative approach to transitioning from a monolithic GraphQL API to a microservices architecture. Unlike traditional methods focusing on breaking down server-side comp...

I’m fascinated by how LLMs are starting to impact education, especially for our children. The transformation is already underway…