How does #Netflix scale personalization to 300M+ users without drowning in technical debt?
Moumita Bhattacharya breaks down UniCoRn (Unified Contextual Ranker) and their proprietary User Foundation Model.
Learn how Netflix moved from bespoke models to a single transformer-based “Harry Potter” model to drive personalization across the entire platform.
🎬 Watch now | 📄 #transcript included ⇨ https://bit.ly/3NV5UEm
As the AI coding industry matures, one thing is clear: #AI used poorly creates massive #TechnicalDebt.
Skeleton Architecture helps tame the chaos. By separating human-owned base classes from AI logic, we can enforce security & structure while maintaining high velocity - all without architectural drift.
The 3 Key Pillars: 🔹 Structure code for AI consumption 🔹 Implement rigid guardrails 🔹 Shift skills from translation → modeling
📰 Dive deeper into Patrick Ferry’s #InfoQ article: https://bit.ly/4bv05Hr
#AIDevelopment #CodeGeneration #SoftwareArchitecture #SoftwareDevelopment
Introducing Daggr - a new #opensource #Python library that simplifies building & debugging multi-step AI workflows.
Developers can define workflows in Python, and Daggr automatically generates a visual canvas showing intermediate states, inputs, and outputs at every step.
Learn more on #InfoQ ⇨ https://bit.ly/4qcr0eD
Dive into the #ModelContextProtocol (MCP)
Discover what MCP is, how it supercharges AI agent development, and why leading open-source frameworks are already embracing it.
This #InfoQ article breaks down the core capabilities MCP enables - plus real-world use cases - showing why it’s quickly becoming essential for building context-aware, modular AI systems.
📰 Read more: https://bit.ly/4qWN0LP
Why do most #ML projects fail to reach production?
According to Wenjie Zi, 5 recurring pitfalls drive failures in ML projects:
❶ Choosing the wrong problem
❷ Data quality and labeling issues
❸ The model-to-product gap
❹ Offline success vs. online reality
❺ Non-technical blockers
🔗 Read the #InfoQ article and learn how you can reduce the chance of encountering them: https://bit.ly/4c66ysr
#GoogleDeepMind has introduced ATLAS - a new set of scaling laws that finally formalize how model size, data volume, and language mixtures interact.
⇨ 774 controlled training runs ⇨ Models ranging from 10M to 8B parameters ⇨ Data covering 400+ languages ⇨ Performance evaluated across 48 target languages.
🔗 Dive into the full technical breakdown on #InfoQ ⇨ https://bit.ly/4rly3CW
Railway’s engineering team just dropped a guide on #Observability.
The guide explains how developers & SRE teams can use:
✅ Logs
✅ Metrics
✅ Traces
✅ Alerts
It’s the roadmap for moving from reactive firefighting to proactive reliability engineering!
🔗 Read the deep dive on #InfoQ: https://bit.ly/45LeueY
In this #InfoQ video, Laurent Doguin shows how #WASM components supercharge Function as a Service (#FaaS) - making it faster, safer & way more flexible.
The takeaway❓ An optimistic view of WASM’s potential to reshape serverless computing, unlocking broader adoption and more flexible function deployment across platforms.
🎬 Watch now: https://bit.ly/4cdkZuO
📄 #transcript included
Prism is a free, cloud-based LaTeX workspace for academic collaboration, with GPT-5.2 integrated directly into the authoring environment.
It unifies document editing, compilation, citation management, and AI-assisted revision in a single web workspace - optimized for long-form scientific writing.
Details here ⇨ https://bit.ly/4qfYqsW
In this #InfoQ #podcast, David Gudeman dives into #SoftwareArchitecture for #Startups.
He explores how to make decisions with imperfect information, how uncertainty and ambiguity shape architecture, and why architects must balance product strategy with technical decisions.
🎧 Listen now: https://bit.ly/3Ohcs00
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