Anti-forgetting representation learning method reduces the weight aggregation interference on model memory and augments the ...

Thermometer, a new calibration technique tailored for large language models, can prevent LLMs from being overconfident or underconfident about their predictions. The technique aims to help users know ...

Founder and Managing Principal of DBP Institute. I consult companies on how to transform technology and data into a valuable business asset. Today, every company is looking at data and analytics to ...

AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology ...

These days, large language models can handle increasingly complex tasks, writing complex code and engaging in sophisticated ...

Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...

A common criticism of fundamentals models is that they are extremely easy to “over-fit”—the statistical term for deriving equations that provide a close match to historical data, but break down when ...

A new technical paper titled “Novel Transformer Model Based Clustering Method for Standard Cell Design Automation” was published by researchers at Nvidia. “Standard cells are essential components of ...

Last month, AI founders and investors told TechCrunch that we’re now in the “second era of scaling laws,” noting how established methods of improving AI models were showing diminishing returns. One ...

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...