software-engineering.
81 writings found
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Building Responsible AI: The NIST Framework and Developer Accountability
Microsoft's Chief Product Officer for Responsible AI discusses the NIST approach, why experimentation without impact consideration breeds irresponsible systems, and human-AI workflow design.
Meta's Hierarchical Interest Representation: A New Approach to Graph-Scale ML
Exploring Meta's breakthrough in recommendation systems that combines sparse engagement signals with world knowledge to power ads across billions of users.
Building Responsible AI with NIST Approach
Exploring Microsoft's approach to responsible AI with insights from Sarah Bird.
How Meta Rebuilt Its Storage Stack for AI Workloads
Meta rearchitected its BLOB storage layer to eliminate GPU stalls and cut data ingestion times. Here is what it means for AI infrastructure at scale.
How Meta Cracked the Zero-Notice Disaster Problem: Instantaneous PowerLoss Storms
Inside Meta's extreme disaster testing and how they solved the ultimate chicken-and-egg problem
What Zero-Notice Disasters Taught Meta About Building Unbreakable Systems
How Meta tests for instant power loss across entire data centers and what it means for developers.
Why Smarter Agent Delegation Matters More Than You Think
GitHub Copilot CLI cut failures by 23% by teaching agents when NOT to delegate
What Meta's PowerLoss Storm Teaches Us About Building Resilient Systems
How Meta tests for zero-notice disasters and why it matters for every engineer building distributed systems.
What I Learned From Meta's PowerOutage Tests on Entire Data Center Regions
A deep dive into Meta's Instantaneous PowerLoss Storm program and what it means for building resilient infrastructure.
How Meta Rewrote Recommendation Systems From Scratch With Index as Model
Inside SilverTorch: Meta's radical shift from microservices to a single neural network for retrieval
SilverTorch and the Death of the Recommendation Microservice
Meta's new Index-as-Model paradigm replaces microservice retrieval with a single PyTorch neural network, and the implications for AI developers are massive.
SilverTorch: How Meta Rewrote the Rules of Recommendation Systems
Meta's radical shift from microservices to a unified neural network transforms retrieval at scale.
The Hidden Complexity Behind Meta's Friend Bubbles
A deeper look at why seemingly simple features demand the deepest engineering work
When Simple Features Hide Complex Engineering: Lessons from Meta's Friend Bubbles
Exploring the hidden complexity behind Meta's Friend Bubbles feature and what it reveals about modern social platform engineering.
Why Simple Features Break Engineering: Lessons from Meta's Friend Bubbles
Friend Bubbles seemed straightforward, but required deep ML work. What this teaches us about 'simple' features in production systems.