Claude Skills and Subagents: Escaping the Prompt Engineering Hamster Wheel
How reusable, lazy-loaded instructions solve the context bloat problem in AI-assisted development.
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Scaling ML Inference on Databricks: Liquid or Partitioned? Salted or Not?
A case study on techniques to maximize your clusters
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Designing Data and AI Systems That Hold Up in Production
A system-level perspective on architecture, agents, and responsible scale
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A practical guide to identifying, restoring, and transforming elements within your images
The post Detecting and Editing Visual Objects with Gemini appeared first on Towards Data Science.
Scaling Feature Engineering Pipelines with Feast and Ray
Utilizing feature stores like Feast and distributed compute frameworks like Ray in production machine learning systems
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Breaking the Host Memory Bottleneck: How Peer Direct Transformed Gaudi’s Cloud Performance
Engineering RDMA-like performance over cloud host NICs using libfabric, DMA-BUF, and HCCL to restore distributed training scalability
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Aliasing in Audio, Easily Explained: From Wagon Wheels to Waveforms
Understanding the foundational distortion of digital audio from first principles, with worked examples and visual intuition
The post Aliasing in Audio, Easily Explained: From Wagon Wheels to Waveforms appeared first on Towards Data Science.
Optimizing Token Generation in PyTorch Decoder Models
Hiding host-device synchronization via CUDA stream interleaving
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A deep dive into the Sharpness-Aware-Minimization (SAM) algorithm and how it improves the generalizability of modern deep learning models
The post Optimizing Deep Learning Models with SAM appeared first on Towards Data Science.
Inside the research that shows algorithmic price-fixing isn't a bug in the code. It's a feature of the math.
The post AI Bots Formed a Cartel. No One Told Them To. appeared first on Towards Data Science.
Use Claude Code to quickly build completely personalized applications
The post Build Effective Internal Tooling with Claude Code appeared first on Towards Data Science.
The Reality of Vibe Coding: AI Agents and the Security Debt Crisis
Why optimizing for speed over safety is leaving applications vulnerable, and how to fix it.
The post The Reality of Vibe Coding: AI Agents and the Security Debt Crisis appeared first on Towards Data Science.
Multi-tenancy, scheduling, and cost modeling on Kubernetes
The post Architecting GPUaaS for Enterprise AI On-Prem appeared first on Towards Data Science.
The Missing Curriculum: Essential Concepts For Data Scientists in the Age of AI Coding Agents
AI can write the code, but you have to steer the ship. Master the knowledge to keep you relevant in the age of AI.
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AlpamayoR1: Large Causal Reasoning Models for Autonomous Driving
All you need to know about Chain of Causation reasoning and the current state of Autonomous Driving!
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When your warehouse and transportation teams blame each other for late deliveries, who's right? We can ask an agent connected to the data settle the debate.
The post Can AI Solve Failures in Your Supply Chain? appeared first on Towards Data Science.
Building Cost-Efficient Agentic RAG on Long-Text Documents in SQL Tables
Designing a hybrid SQL + vector retrieval system without schema changes, data migration, or performance trade-offs
The post Building Cost-Efficient Agentic RAG on Long-Text Documents in SQL Tables appeared first on Towards Data Science.
Agentic AI for Modern Deep Learning Experimentation
Stop babysitting training runs. Start shipping research. Autonomous experiment management built for/by deep learning engineers.
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Iron Triangles: Powerful Tools for Analyzing Trade-Offs in AI Product Development
Conceptual overview and practical guidance
The post Iron Triangles: Powerful Tools for Analyzing Trade-Offs in AI Product Development appeared first on Towards Data Science.