AI agents have fundamentally changed the threat model of AI model-based applications. By equipping these models with plugins (also called tools), your agents no longer just generate text; they now ...

An agent harness is the scaffolding that lets an AI model operate autonomously on a real task: run tools, observe results, and loop until the job is done. Unlike a chat interface where you steer every ...

We begin this tutorial by showing how we can combine MLE-Agent with Ollama to create a fully local, API-free machine learning workflow. We set up a reproducible environment in Google Colab, generate a ...

CLIP by OpenAI excels at connecting images with natural language, making it powerful for zero-shot image classification and retrieval tasks.

Large language models (LLMs) by themselves are less than meets the eye; the moniker “stochastic parrots” isn’t wrong. Connect LLMs to specific data for retrieval-augmented generation (RAG) and you get ...

Code embeddings are a transformative way to represent code snippets as dense vectors in a continuous space. These embeddings capture the semantic and functional relationships between code snippets, ...

I've noticed while upgrading our code to v2 that we had big slowdowns within our test suites. And I narrowed it down to our numerous calls to isinstance checks. Turns out that isinstance for a ...

TensorFlow 2.14 introduces a new installation method for Linux, simplifying CUDA library setup. The 'strict_mode' API turns deprecation warnings into runtime errors for better user guidance. New API ...

from typing import Union def f(x : Union[int, float]): if isinstance(x, float): print("b", x) elif isinstance(x, int): print("a", x) with --warn-unreachable returns ...