Infosecurity outlines key recommendations for CISOs and security teams to implement safeguards for AI-assisted coding ...

From cost and performance specs to advanced capabilities and quirks, answers to these questions will help you determine the ...

The OWASP Top 10 for LLM Applications is the most widely referenced framework for understanding these risks. First released in 2023, OWASP updated the list in late 2024 to reflect real-world incidents ...

The transition from a raw dataset to a fine-tuned Large Language Model (LLM) traditionally involves significant infrastructure overhead, including CUDA environment management and high VRAM ...

Why are we asking for donations? Why are we asking for donations? This site is free thanks to our community of supporters. Voluntary donations from readers like you keep our news accessible for ...

When enterprises fine-tune LLMs for new tasks, they risk breaking everything the models already know. This forces companies to maintain separate models for every skill. Researchers at MIT, the ...

Orchestrate an end-to-end LLM fine-tuning workflow that ingests Goodreads book data, engineers genre features, creates training files, submits fine-tuning jobs to OpenAI, and validates the resulting ...

A new technique developed by researchers at Shanghai Jiao Tong University and other institutions enables large language model agents to learn new skills without the need for expensive fine-tuning. The ...

Abstract: Large Language Models (LLMs) show promise for recommendation but frequent fine-tuning on ever-growing data is costly. We study data-efficient fine-tuning and propose a task-specific pruning ...

Thinking Machines Lab Inc. today launched its Tinker artificial intelligence fine-tuning service into general availability. San Francisco-based Thinking Machines was founded in February by Mira Murati ...