rollup.
317 writings found
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Why Your AI Benchmark Is Probably Wrong: The N,K Trade-off
Google Research reveals why using 3-5 human raters per item isn't enough for reproducible AI evaluation. The depth vs breadth problem explained.
Tests Are the Real Safety Net: Why Your AI Specs Need Executable Validation
Writing specs for LLMs is trendy. But without automated tests, you're flying blind. Here's why the spec document isn't your safety net.
Meta's AI is Reshoring American Concrete, One Mix at a Time
How Bayesian optimization is helping U.S. concrete producers ditch imported cement and redesign mixes in days instead of months.
Sora's Shutdown: When Burning $1M Daily Isn't Worth the Hype
OpenAI killed Sora after six months, ditching a $1B Disney deal. The real story isn't about data grabs, it's about brutal economics and losing ground to Claude.
Building macOS Apps Without Knowing Swift: What Vibe Coding Actually Teaches Us
I built two monitoring tools for my M5 MacBook using Claude and GPT without writing Swift myself. The results work, but should they?
Suno v5.5: AI Music Generation Gets Personal with Voice Cloning and Custom Training
Suno's v5.5 update brings voice cloning, custom model training, and personalization. A look at what this means for creators and the music industry.
GitHub Actions Is Finally Getting Serious About Supply Chain Security
GitHub's 2026 roadmap tackles CI/CD vulnerabilities with dependency locks, execution policies, and endpoint monitoring. Here's what it means for developers.
How Facebook Built Friend Bubbles: A Deep Dive into Social ML Architecture
Meta's friend bubbles system combines closeness prediction models, ranking optimization, and performance engineering to surface friend-driven content at scale.
Google's Vibe Coding XR: When AI Writes Your Spatial Computing Apps in 60 Seconds
Google Research launches XR Blocks with Gemini integration, letting developers prompt their way into physics-aware WebXR apps. I dig into what this means.
Starlette 1.0 and the Problem of Training Data Obsolescence
Starlette finally hits 1.0, but breaking changes expose a fascinating problem: how do you make LLMs generate code for frameworks they weren't trained on?
Starlette 1.0 and the Problem of Teaching AI New Tricks
Starlette finally hits 1.0, but breaking changes expose a fascinating challenge: how do you get LLMs to generate code for versions they weren't trained on?
GitHub's New Data Policy: Your Code Becomes Training Data
GitHub will train AI models on Copilot Free, Pro, and Pro+ user data starting April 24. Here's what developers need to know about this industry shift.
Starlette 1.0 and the curious case of teaching AI new tricks
Starlette finally hits 1.0, but what happens when your LLM was trained on outdated code? Claude's new skills feature might just solve that problem.
Facebook's Friend Bubbles: When Social Graphs Meet Recommendation Systems
Meta's friend bubbles on Reels reveal how social signals and ML models can coexist in video recommendations without destroying performance.
I Built an AI-Powered Issue Triage App and Learned Why Server-Side Architecture Still Matters
Building IssueCrush with GitHub's Copilot SDK taught me hard lessons about session management, graceful degradation, and why mobile AI needs a backend.