Large language models are routinely described in terms of their size, with figures like 7 billion or 70 billion parameters ...

At CES 2026, Nvidia revealed it is planning a software update for DGX Spark which will significantly extend the device's ...

A new technical paper titled “Hardware Acceleration for Neural Networks: A Comprehensive Survey” was published by researchers ...

Multimodal large language models have shown powerful abilities to understand and reason across text and images, but their ...

Ternary quantization has emerged as a powerful technique for reducing both computational and memory footprint of large language models (LLM), enabling efficient real-time inference deployment without ...

I'm encountering an assertion error when attempting to quantize a Qwen2-based model (A.X-4.0-Light-7B) to FP8 format using TensorRT-LLM's quantization script. The ...

Why does it sometimes feel like the tools we rely on are getting worse, not better? Imagine asking a innovative AI model a question, only to receive a response that feels oddly incoherent or ...

Processing-in-Memory (PIM) is emerging as a promising next-generation hardware to address memory bottlenecks in large language model (LLM) inference by leveraging internal memory bandwidth, enabling ...

What if you could harness the power of innovative artificial intelligence without relying on the cloud? Imagine running a large language model (LLM) locally on your own hardware, delivering ...