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TL;DR: MLOps tools help teams track experiments, automate pipelines, deploy models, and monitor performance. Tools such as MLflow, Kubeflow, BentoML, and Evidently AI support diffe...
How MLOps Works: A Step-by-Step Guide for BeginnersContinue reading on Medium »
From notebooks to monitored, reproducible pipelines — the essentialsContinue reading on Medium »
The Model Context Protocol (MCP) lets an AI application call out to external tools and data sources through a standard client-server interface. When a tool runs on the server, the...
The Model Context Protocol (MCP) is quietly becoming one of the most useful ideas in AI tooling. Here, we describe what MCP is, why it matters, and how to build an MCP server yours...
Originally appeared on Carmine Paolino.RubyLLM 2.1 is out. I released it on stage at Deccan Queen on Rails in Pune. It builds on 2.0 and adds an MCP client, typed judgments, evalu...
Lost in endless lists of AI developer tools? Follow one clear path from your first local model to tested, traced and deployed LLM apps, with code you can run on a laptop today.
The five MLOps monitoring assumptions agents break, and which inherited signals now pass failed runs as healthy. The post AgentOps Is Not MLOps: What Breaks in Your Monitoring Stac...
Large Language Models (LLMs) are commonly accessed through cloud APIs provided by services such as OpenAI, Anthropic, or Google Gemini. However, there are many situations where dev...
a brave new world
JetBrains released Mellum2.1, an Apache 2.0, 12B mixture-of-experts thinking model with 2.5B active parameters. RL in real repositories lifted its SWE-bench Verified score from 2.0...
Today at the PyTorch Conference, we released llm-d 1.0, an open-source, Kubernetes-native stack for distributed LLM inference. Co-founded by Google with Red Hat, IBM and others, we...
Привет, Хабр! Меня зовут Павел, я старший разработчик ML-платформы в Авито и последние полтора года занимаюсь MLOps. На прошедшей Kuber Conf я выступал с докладом про нашу платформ...
ИИ всё чаще упирается не в качество промпта, а в то, что происходит дальше: как встроить модель в рабочий процесс, наблюдать за агентом, контролировать качество и понимать стоимост...
Prompt caching, model routing, RAG trimming and batching: a practical LLM cost optimization playbook that keeps quality intact.Continue reading on Medium »
A visual guide to MCP that explains how it works, how to use it with Claude Code, Tavily, GitHub, and Playwright, and what is new through simple diagrams that make the whole concep...
llm.rb is an advanced runtime for building agentic AI applications on CRuby. It has zero runtime dependencies by default, supports concurrent and parallel tool execution and has a...
llm.rb is an agentic runtime for building AI applications on CRuby. It supports 14 different providers, it has zero runtime dependencies by default, and it can execute tool calls o...
KServe serves your ML model on Kubernetes from a few lines of YAM, scaling out under load, to zero when idle, and updating with zero downtime.
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