Small language models shine for domain-specific or specialized use cases, while making it easier for enterprises to balance performance, cost, and security concerns. Since ChatGPT arrived in late 2022 ...

Forbes contributors publish independent expert analyses and insights. Exploring Cloud, AI, Big Data and all things Digital Transformation. Frontier models in the billions and trillions of parameters ...

The partnership will combine Uniphore’s Business AI Cloud as the foundation for building and fine-tuning small language models (SLMs), while Cognizant will lead the solution development, deployment an ...

Forbes contributors publish independent expert analyses and insights. How Global Leaders are Rebooting industries-business-societies & more. Andrew Ross Sorkin and Elon Musk speak onstage during The ...

Advanced AI gave way to Large Language Models, such as Megatron-Turing NLG, capable of executing a huge number of tasks. However, large-scale LLMs come with huge challenges that include high energy ...

While Large Language Models (LLMs) like GPT-3 and GPT-4 have quickly become synonymous with AI, LLM mass deployments in both training and inference applications have, to date, been predominately cloud ...

Until now, the AI revolution has been largely measured by size: the bigger the model, the bolder the claims. However, as we move closer to truly autonomous and pervasive AI systems, a new trend is ...

Small language models, known as SLMs, create intriguing possibilities for higher education leaders looking to take advantage of artificial intelligence and machine learning. SLMs are miniaturized ...

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. Ever-more ...

H2OVL Mississippi 0.8B Model Surpasses Leading Small Vision Language Models (SVLMs) and Impressively Outperforms Larger State-of-the-Art Vision Language Models (VLMs) in OCR Benchmarks for Text ...

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 ...