Tech Xplore

Adaptive drafter model uses downtime to double LLM training speed

Reasoning large language models (LLMs) are designed to solve complex problems by breaking them down into a series of smaller ...

AI agents are fast, loose, and out of control, MIT study finds

The majority of agentic AI systems disclose nothing about what safety testing, and many systems have no documented way to shut down a rogue bot, a study by MIT found.
GitHub

Machine Learning Engineering Open Book

This is an open collection of methodologies, tools and step by step instructions to help with successful training and fine-tuning of large language models and multi-modal models and their inference.
GitHub

TfELM : Extreme Learning Machines Framework with Python and TensorFlow

This framework provides a comprehensive set of tools and utilities for implementing and experimenting with Extreme Learning Machines using Python and TensorFlow. ELMs are a type of machine learning ...
IEEE

In-Network Machine Learning Using Programmable Network Devices: A Survey

Abstract: Machine learning is widely used to solve networking challenges, ranging from traffic classification and anomaly detection to network configuration. However, machine learning also requires ...
IEEE

sQUlearn: A Python Library for Quantum Machine Learning [Focus: Quantum Software and Its Engineering]

Abstract: sQUlearn introduces a user-friendly, noisy intermediate-scale quantum (NISQ)-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine ...