InfoWorld

What is model quantization? Smaller, faster LLMs

Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...
Hackaday

Making The Smallest And Dumbest LLM With Extreme Quantization

The reason why large language models are called ‘large’ is not because of how smart they are, but as a factor of their sheer size in bytes. At billions of parameters at four bytes each, they pose a ...
Devdiscourse

Privacy-preserving AI becomes critical for Industry 4.0

Industry 4.0 depends on continuous data exchange between sensors, machines, production lines, and enterprise systems, but much of this data cannot be centralized due to privacy, security, and ...
InfoWorld

Model quantization and the dawn of edge AI

Model quantization bridges the gap between the computational limitations of edge devices and the demands for highly accurate models and real-time intelligent applications. The convergence of ...

Are LTMs the next LLMs? This new type of AI can do what large-language models can’t

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 ...
Forbes

Large Behavior Models Surpass Large Language Models To Create AI That Walks And Talks

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 ...

Are Large Language Models A Dead End Or Simply Incomplete?

Once a model is deployed, its internal structure is effectively frozen. Any real learning happens elsewhere: through retraining cycles, fine-tuning jobs or external memory systems layered on top. The ...