Researchers at arXiv propose a hybrid pre-training objective for language models that combines a Joint Embedding Predictive Architecture (JEPA) latent-space prediction loss with masked language modell…
A developer spent a week trying to extract structured data from free-form emails using regex and spaCy before switching to an AI agent with function calling. The agent, built with OpenAI's API and a P…
Researchers have developed EURO-5K, a new dataset of sentence-level reporting obligations from 136 EU legislative acts, to improve automated extraction of regulatory requirements. Benchmarking discrim…
Chinese AI labs have progressed from early BERT-era models to trillion-parameter systems like Wu Dao 2.0 (1.75T parameters) and cost-efficient architectures such as DeepSeek V3 (trained for $5.6M), ac…
A developer used a local Japanese sentiment AI (BERT) to analyze 87,621 messages from an 8-year LINE chat history, running entirely on a DGX Spark to keep the private conversation data on-device. By s…
Personal analogy comparing career phases to three types of large language model (LLM) architectures. The author describes their early education as an "encoder-only" phase focused on absorbing knowledg…
GPT models are decoder-only transformers that generate text by predicting the next token one at a time, conditioning each new prediction on all previous tokens. Unlike BERT, which reads entire sequenc…
BERT (Bidirectional Encoder Representations from Transformers) is an encoder-only transformer model that reads all tokens in a sentence simultaneously, using masked language modeling (MLM) and next se…