Fundamental, which just closed a $225 million funding round, develops ‘large tabular models’ for structured data like tables and spreadsheets. Large-language models (LLMs) have taken the world by ...
The barrage of misinformation in the field of health care is persistent and growing. The advent of artificial intelligence (AI) and large language models (LLMs) in health care has expedited the ...
Popular large language models (LLMs) are unable to provide reliable information about key public services such as health, taxes and benefits, the Open Data Institute (ODI) has found.
With the rapid advancement of Large Language Models (LLMs), an increasing number of researchers are focusing on Generative Recommender Systems (GRSs). Unlike traditional recommendation systems that ...
Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I closely explore the rapidly emerging ...
SHANGHAI, Feb. 10, 2026 (GLOBE NEWSWIRE) -- Industry research platform VBData recently highlighted “XingShi” Large Language Model (“XS LLM”) from Fangzhou Inc. ("Fangzhou" or the "Company") (HKEX: ...
As recently as 2022, just building a large language model (LLM) was a feat at the cutting edge of artificial-intelligence (AI) engineering. Three years on, experts are harder to impress. To really ...
Are tech companies on the verge of creating thinking machines with their tremendous AI models, as top executives claim they are? Not according to one expert. We humans tend to associate language with ...
Apertus was released in early September 2025. It is a multilingual model developed by the Swiss Federal Institutes of Technology in Zurich (ETH) and Lausanne (EPFL). The model was pretrained with 60% ...
Singapore’s national AI program has moved its Sea-Lion large language model off Meta’s model family and adopted Alibaba Cloud’s Qwen architecture, according to information cited by foreign media from ...
The proliferation of edge AI will require fundamental changes in language models and chip architectures to make inferencing and learning outside of AI data centers a viable option. The initial goal ...