🛠️ Feature Engineering - micaleel · Scour

AI Is Breaking QA: Rethinking Quality Engineering in 2026 🤖Machine Learning

qasource.com·6d

Scaling Ruby's defenses with AI 📦Parquet

blog.rubygems.org·1d

logrittr: A Verbose Pipe Operator for Logging dplyr Pipelines 📊Data Science

r-bloggers.com·1d

FlowBot: Inducing LLM Workflows with Bilevel Optimization and Textual Gradients 💬Natural Language Processing

Learning Long-Term Motion Embeddings for Efficient Kinematics Generation 🧠Deep Learning

machinelearning.apple.com·6d

The Next 5 Years of AI: Tools, Agents, and Automation 💬Natural Language Processing

·1d

CI/CD pipeline abuse: the problem no one is watching 🔨LLVM

RAG precision tuning can quietly cut retrieval accuracy by 40%, putting agentic pipelines at risk 🔍Retrieval Systems

venturebeat.com·3d

From deployment to open standards: Arm advances AI infrastructure for the agentic era 🧠Deep Learning

newsroom.arm.com·1d

Pipelines: The Forgotten SLO 🚀Model Serving

thefridaydeploy.substack.com·4d·Substack

Can a Chip That Loves Zeros Make Huge AI Models More Efficient? 🧮Vector Databases

spectrum.ieee.org

·2d·Hacker News, r/hardware

Operations Context for AI | Ontology in Fabric IQ 🦆DuckDB

techcommunity.microsoft.com·1d

Learning Agentic Design Systems (8 minute read) 💬Natural Language Processing

brandstructure.figma.site·3d

Protein Function Prediction with Pretrained ProtT5 Embeddings and Gradient Boosting 🤖Machine Learning

biorxiv.org·1d

Multi-sensor and MTConnect dataset of metal cutting anomaly in milling from laboratory and industry settings 🤖Machine Learning

How Microsoft 1ES uses agentic AI to take on security and compliance at scale 🤖Machine Learning

techcommunity.microsoft.com·2d

Building a Private Karpathy-Style LLM Wiki With gbrain and gstack 📓Note-Taking

blog.saeloun.com·2d

You can’t prompt your way out of complexity: Why enterprise AI is turning to to process intelligence 🦆DuckDB

siliconangle.com·3d

The Creative Machine: AI and India’s AVGC Industry 🧠Deep Learning

orfonline.org·2d

DB-KSVD: Scalable Alternating Optimization for Disentangling High-Dimensional Embedding Spaces 🧮Vector Databases

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