Google released the Colab CLI, letting developers and AI agents run local code on remote Colab GPU and TPU runtime
The post Google’s New Colab CLI Lets Developers and AI Agents Run Python on Remote Colab GPUs and TPUs From the Terminal appeared first on MarkTechPost.
I got tired of copying files into an AI chat just to get feedback. So I built a pure Python MCP server that gives AI tools direct access to my local project—no frameworks, no dependencies. It runs over stdio for local use and switches to HTTP/SSE for concurrent clients with a single flag. The result: 5 clients, under 50ms, and a design that stays simple without sacrificing capability.
The post My AI Couldn’t See My Files — I Built a Zero-Dependency MCP Server appeared first on Towards Data Science.
DeepMind's framework highlights the need for robust AI delegation protocols, emphasizing trust, accountability, and resilience in multi-agent systems.
The post Google DeepMind proposes Intelligent AI Delegation framework for task management appeared first on Crypto Briefing.
A veritable garden of linters and type checkers has blossomed in the Python ecosystem. Pyright and Mypy are two of the most popular, while Astral’s ty and Meta’s Pyrefly are two promising Rust-based newcomers. We compared early-stage ty and Pyrefly last June. One year later, Meta has released Pyrefly 1.0.
Pyrefly is intended to stand out from the pack by way of a few key features. It’s written in Rust for performance and memory efficiency, and it has a number of intriguing forward-looking features, some still experimental.
Setting up Pyrefly
Pyrefly installs into a Python environment like any other Python type checker (pip install pyrefly) and brings with it no additional dependencies. Visual Studio Code users can work with Pyrefly via an extension, but the extension doesn’t give you access to the command-line tools offered by Pyrefly when it’s installed in a project venv.
You can start using Pyrefly right away, with no actual setup. If Pyrefly detects no configuration for a given pro
Describe a dataset in one sentence; Bigset's orchestrator and parallel sub-agents research the live web and return structured tables.
The post TinyFish Launches BigSet: An Open-Source Multi-Agent System That Builds Structured Live Datasets from Plain-English Descriptions appeared first on MarkTechPost.
In this article, we will dive deep into five must-know Python concepts that will help you transition from writing clunky, slow spaghetti code to constructing lightning-fast, production-grade, and beautifully functional data pipelines.