In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful ...

GenAI chatbot systems face critical limitations in real-time feedback processing, including delayed data collection, semantic ambiguity, and slow model ...

A set of recent research papers proposes that freezing or selectively tuning a small fraction of neurons inside large ...

Model selection, infrastructure sizing, vertical fine-tuning and MCP server integration. All explained without the fluff. Why Run AI on Your Own Infrastructure? Let’s be honest: over the past two ...

Abstract: Fine-tuning large language models (LLMs) on private, on-device data can empower tailored personalized AI agents. However, fine-tuning LLMs on resource-constrained edge devices faces ...

Abstract: Data augmentation in reinforcement learning (RL) aims to generate diverse and extensive datasets to enhance the learning process. Most existing studies on RL augmentation employ sample-based ...

What if the most profound leap toward Artificial General Intelligence (AGI) wasn’t a headline-grabbing announcement, but a quiet breakthrough flying under the radar? Enter Grok 5, a development that ...

Researchers at the Massachusetts Institute of Technology (MIT) are gaining renewed attention for developing and open sourcing a technique that allows large language models (LLMs) — like those ...

In this Law Punx blast, Scott Stevenson of Spellbook discusses the limitations of fine-tuning AI models for legal use cases, arguing that it has become an overrated technique. He emphasizes the ...

Thinking Machines Lab, a heavily funded startup cofounded by prominent researchers from OpenAI, has revealed its first product—a tool called Tinker that automates the creation of custom frontier AI ...