Artificial intelligence has taken the world by storm. In biology, AI tools called deep neural networks (DNNs) have proven invaluable for predicting the results of genomic experiments. Their usefulness ...
For IT and HR teams, SLMs can reduce the burden of repetitive tasks by automating ticket handling, routing, and approvals, while providing substantial cost savings versus LLMs. Large language models ...
Small language models, known as SLMs, create intriguing possibilities for business leaders looking to take advantage of artificial intelligence and machine learning. SLMs are miniature versions of the ...
According to Jeff Dean, the influential AI distillation paper was initially rejected from NeurIPS 2014 as it was considered 'unlikely to have significant impact.' Despite this, model distillation has ...
The rollout of edge AI is creating new security risks due to a mix of small language models (SLMs), their integration into increasingly complex hardware, and the behavior and interactions of both over ...
Cody Pierce is the CEO and founder of Neon Cyber. He has 25 years of experience in cybersecurity and a passion for innovation. Large language models (LLMs) have captured the world’s imagination since ...
French AI startup Mistral launched its new Mistral 3 family of open-weight models on Tuesday, a launch that aims to prove it can lead in making AI publicly available and serve business clients better ...
Lin Tian receives funding from the Advanced Strategic Capabilities Accelerator (ASCA) and the Defence Innovation Network. Marian-Andrei Rizoiu receives funding from the Advanced Strategic Capabilities ...
Abstract: Large Language Models (LLMs) demonstrate exceptional reasoning capabilities, often achieving state-of-the-art performance in various tasks. However, their substantial computational and ...
Abstract: Chain-of-thought distillation (CoT-distillation) aims to endow small language models (SLMs) with reasoning ability to improve their performance toward specific tasks by allowing them to ...
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 ...
There’s a paradox at the heart of modern AI: The kinds of sophisticated models that companies are using to get real work done and reduce head count aren’t the ones getting all the attention.