The model training process is also evolving. RAG training and parameter-efficient fine-tuning are seen as evolutions of traditional model training that produce better quality output with lower ...

LongCat-Flash has shown excellent performance in cost control, reducing the cost per million output tokens to $0.7, whi ...

In July, EPFL, ETH Zurich, and CSCS announced their joint initiative to build a large language model (LLM). Now, this model ...

Research has shown that parameters pruned after training, a process that decreases the model size, could have been pruned before training without any effect on the network’s ability to learn.

The process begins with feeding an algorithm enormous amounts of data—books, math problems, captioned photos, voice recordings, and so on—to establish the model’s baseline capabilities.

They found that the process of building and testing a final paper-worthy model required training 4,789 models over a six-month period.

Decentralized AI is emerging as a powerful alternative, enabling smaller businesses to build AI without massive data centers.

A Practitioner Model Informed by Theory and Research guides the CAPS training program. Practicum students are trained to ground their practice of psychology in theory and research. This model is ...