LLMs tagged posts

Developers are increasingly relying on large language models (LLMs) for everyday computing tasks such as fixing bugs, explaining code and automating text-processing tasks like filtering logs.

However, it’s not as simple as entering or submitting a question and relying on the model to give you the answer. While humans easily understand these tasks and know exactly what they want, it is difficult to translate them into rigid computer code.

The cloud dilemma
As standard programming is often not up to the task, developers often use AI to handle jobs that are difficult to express as traditional rules...

New work explaining the inner workings of artificial intelligence could provide a way around the threat of AI “model collapse,” potentially averting growing numbers of AI hallucinations in the future.

First coined in 2024, “model collapse” refers to a scenario where an AI model trained on AI-produced data ceases to provide accurate results, instead producing inaccurate “gibberish” because of the poor quality of its training data.

Some have warned that high-quality text data to train systems like Large Language Models (LLMs) is set to run out as early as this year, and so data produced by models themselves has taken a larger training role—inviting the threat of model collapse.

Simple statistical models reveal a fix
Through analysis of a simple yet powerful set of statistical ...

Is artificial intelligence (AI) capable of suggesting appropriate behavior in emotionally charged situations? A team from the University of Geneva (UNIGE) and the University of Bern (UniBE) put six generative AIs—including ChatGPT—to the test using emotional intelligence (EI) assessments typically designed for humans.

The outcome: these AIs outperformed average human performance and were even able to generate new tests in record time. These findings open up new possibilities for AI in education, coaching, and conflict management. The study is published in Communications Psychology.

Large language models (LLMs) are artificial intelligence (AI) systems capable of processing, interpreting and generating human language...

A small team of AI engineers at Zoom Communications has developed a new approach to training AI systems that uses far fewer resources than the standard approach now in use. The team has published their results on the arXiv preprint server.

The new approach developed at Zoom is called Chain of Draft (CoD), an update of the traditional approach now in use called Chain of Thought (CoT). CoT uses a step-by-step approach to solving a problem, similar in many ways to human problem-solving...