Browsing: Workflows

print(“5) Concurrency progress: thread_map / process_map”) def cpuish(n: int) -> int: x = 0 for i in range(50_000): x = (x + (n * i)) %…

Liquid AI has released LFM2-24B-A2B, a model optimized for local, low-latency tool dispatch, alongside LocalCowork, an open-source desktop agent application available in their Liquid4All GitHub Cookbook.…

As the industry moves from simple Large Language Model (LLM) inference toward autonomous agentic systems, the challenge for devs have shifted. It is no longer just…

For the past year, AI devs have relied on the ReAct (Reasoning + Acting) pattern—a simple loop where an LLM thinks, picks a tool, and executes.…

In this tutorial, we build a production-ready agentic workflow that prioritizes reliability over best-effort generation by enforcing strict, typed outputs at every step. We use PydanticAI…

As artificial intelligence and machine learning (AI/ML) workflows grow in scale and complexity, it becomes harder for practitioners to organize and deploy their models. AI projects…

PyCaret is an open-source, low-code machine learning library that simplifies and standardizes the end-to-end machine learning workflow. Instead of acting as a single AutoML algorithm, PyCaret…

Holographic tape operated inside a production LTO library without infrastructure changesLive application software accessed holographic media using standard tape library workflowsCartridge dimensions matched LTO, allowing robotic…

In the world of Large Language Models (LLMs), speed is the only feature that matters once accuracy is solved. For a human, waiting 1 second for…

In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We…