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Изходен канал @clockstackwheels · Post #1228 · 7.04

Гришка у себя в канале на днях писал о том, что плохо, когда софт начинает думать за человека и выполнять действия, которые человек не подразумевал. Вот вам пример довольно тупого автокорректора в поиске Авито. Я искал игру «Ксия: Искры покинутой звезды», и ввёл в поиск «ксия искры». Оно поменяло на «секс игры» 🗿 Смешно, конечно, но на самом деле какого хрена? Причём, Авито делает эту замену автоматически при нажатии кнопки подтверждения. А искать без замены можно только неочевидным способом — выбрав свой вариант в списке выпавших подсказок. #web@clockstackwheels

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GitHub Trends

@githubtrending · Post #15283 · 09.11.2025 г., 14:30

#go#a2a#agents#agents_sdk#ai#aiagentframework#gemini#genai#go#llm#mcp#multi_agent_collaboration#multi_agent_systems#sdk#vertex_ai The Agent Development Kit (ADK) for Go is an open-source toolkit that makes it easy to build, test, and deploy smart AI agents using the Go programming language. It lets you create simple or complex agent workflows, use ready-made or custom tools, and run your agents anywhere, especially in cloud environments. With ADK, you get full control, flexibility, and the ability to scale your applications, making it faster and simpler to develop powerful AI solutions for real-world tasks. https://github.com/google/adk-go

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@githubtrending · Post #14693 · 10.05.2025 г., 12:00

#jupyter_notebook#a2a#agentic_ai#dapr#dapr_pub_sub#dapr_service_invocation#dapr_sidecar#dapr_workflow#docker#kafka#kubernetes#langmem#mcp#openai#openai_agents_sdk#openai_api#postgresql_database#rabbitmq#rancher_desktop#redis#serverless_containers The Dapr Agentic Cloud Ascent (DACA) design pattern helps you build powerful, scalable AI systems that can handle millions of AI agents working together without crashing. It uses Dapr technology with Kubernetes to efficiently manage many AI agents as lightweight virtual actors, ensuring fast response, reliability, and easy scaling. You can start small using free or low-cost cloud tools and grow to planet-scale systems. The OpenAI Agents SDK is recommended for beginners because it is simple, flexible, and gives you good control to develop AI agents quickly. This approach saves costs, avoids vendor lock-in, and supports resilient, event-driven AI workflows, making it ideal for developers aiming to create advanced, cloud-native AI applications[1][2][3][4]. https://github.com/panaversity/learn-agentic-ai