Tom Fenton moves from local AI concepts to hands-on tools for matching LLMs to hardware, running local chatbots with Ollama and benchmarking AI performance.
Abstract: The rapid evolution of artificial intelligence has created a demand for deploying machine learning models on low-computational devices, such as microcontrollers. However, these models are ...
The artificial intelligence (AI)-fueled demand for flash storage in data centers has supercharged Sandisk's growth, and the good news is that the primary catalyst behind the company's growth is ...
Abstract: As a major provider of LLM inference services, ByteDance has continuously explored diverse accelerator options to meet the rapidly growing inference demands of various heterogeneous LLM ...
Apple (AAPL) revealed that it plans to extend its Private Cloud Compute beyond Apple's data centers for the first time through a new collaboration with Google (GOOG)(GOOGL) and Nvidia (NVDA). This ...
D-Matrix says its chips can run inference workloads 10 times faster and using five times less energy than a standalone graphics processing unit from Nvidia. Like Cerebras, D-Matrix is trying to prove ...
Our long-term goal is to build efficient and reliable 2.5B diffusion-based decoding for document OCR. MinerU-Diffusion reframes document OCR as an inverse rendering problem and replaces slow, ...
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