⚙️ MLOps - 915117442 · Scour

Building ML Systems with Feature/Training/Inference Pipelines: The Key to Scalable ML Architectures💖💖💖

dev.to·3h·

Discuss: DEV

⚙️Feature Engineering

ML Evaluation for Production Systems: Metrics, Offline Validation, and Robustness Testing

medium.com

·2d

⚡Machine Learning

LLM Terminology Guide: Weights, Inference, Effective sequence length, and Self-Hosting Explained

devforth.io·9h·

Discuss: Hacker News

teradata-labs/loom: A framework for building autonomous LLM agent threads with natural language agent creation and multi-agent orchestration

github.com·5h·

Discuss: Hacker News

🕸️LangGraph

Rust for ML, Java for Orchestration: How I Split a Real-World AI System Between Two Languages

medium.com

·3h

🎯Fine-tuning

Automatic Configuration of LLM Post-Training Pipelines

arxiv.org·19h

🎯Fine-tuning

Building a Kubernetes-native pattern for AI infrastructure at scale

thenewstack.io·1d

🎯Fine-tuning

vasilyevdm/ai-agent-handbook: Comprehensive guide to AI agent engineering: how 30+ frameworks actually work under the hood. Context rot, compaction, system prompt assembly, SOUL.md, agent loops, memory systems, tool sprawl, MCP, progressive disclosure, multi-agent orchestration, Plan/Act, episodic memory. Code examples throughout. Pick the right stack, avoid the common traps

github.com·5h·

Discuss: r/LocalLLaMA

A straightforward AI optimization

natemeyvis.com·8h

🎯Fine-tuning

How to Build an End-to-End ML Platform Locally: From Experiment Tracking to CI/CD

freecodecamp.org·3d

⚡Machine Learning

Mamba-3: An Inference-First State Space Model

blog.cartesia.ai·1d

🖼️Multimodal AI

MAED: Mathematical Activation Error Detection for Mitigating Physical Fault Attacks in DNN Inference

arxiv.org·19h

🔬Deep Learning

When a Small Language Model Beat Our LLM in Production — Avni Bhatt at AI Engineer Melbourne 2026

webdirections.org·1d

128GB of RAM, Zero Internet, and a Year of Building AI Infrastructure Nobody Asked For

dev.to·20h·

Discuss: DEV

🎯Fine-tuning

Development Issues in ML Pipelines

dinagoethe.medium.com·3d

⚡Machine Learning

Eliminating the ‘Rego tax’: How AI orchestrators automate Kubernetes compliance

next.redhat.com·8h

🎯Fine-tuning

Instrument zero‑code observability for LLMs and agents on Kubernetes

grafana.com·3h

🎯Fine-tuning

Together AI expands fine-tuning service with tool calling, reasoning, and vision support

together.ai·2d

🎯Fine-tuning

Jensen Huang: Nvidia's Future, Physical AI, Agent, Inference Explosion

youtube.com·23h

Five AI Trends from the latest NeurIPS 2023 Conference

relational.ai·2h

Loading more...