
OpenAI Cybersecurity Grant Program
Exploring the OpenAI Cybersecurity Grant Program for cutting-edge research and innovation in the field.

Modular: The world's fastest unified matrix multiplication
A blogpost showcasing the world's fastest unified matrix multiplication using the Modular framework.

Spark Analysers: Catching Anti-Patterns In Spark Apps
A real-time system to catch anti-patterns in Spark applications at Uber scale, helping developers optimize their apps.

OpenAI cybersecurity grant program
Facilitating development of AI-powered cybersecurity capabilities for defenders through grants and support.

Ensuring the Successful Launch of Ads on Netflix
This blogpost discusses the methods used to ensure a successful launch of Ads on Netflix, including testing the system, technologies involved, and best practices developed.

Retrieval-augmented visual-language pre-training
A visual-language model called REVEAL, which utilizes a multi-source multi-modal "memory" to answer knowledge-intensive queries, overcoming the limitations of existing retrieval-augmented models and reducing the need for massive amounts of training data and parameter size.

Highlights from Git 2.41
Highlights of the new features and updates in Git 2.41

Improving mathematical reasoning with process supervision
Enhancing mathematical cognition through guided processes

How MLCommons is democratizing data with public datasets
MLCommons is democratizing data with public datasets, focusing on the importance of data in machine learning and the need for better tools and standards for creating and improving datasets.
Python Async Workers on Fly Machines
Implementing lightweight background jobs for a Python web application using Fly Machines

A more effective way to train machines for uncertain, real-world situations
Algorithm for determining when a machine should follow a teacher or learn independently in uncertain real-world situations

New tool helps people choose the right method for evaluating AI models
A new tool facilitates the selection of the appropriate method to evaluate AI models, enabling users to interpret predictions accurately.