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 ...
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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NEW YORK - June 3, 2026 - Lagrange Labs today announced the open-source release of DeepProve, its production-grade zero-knowledge machine learning (zkML) system. DeepProve has generated more than 12 ...
Perplexity announced "hybrid agentic inference" at Computex 2026, a system that automatically splits AI workloads between a user's local device and cloud-based frontier models—no manual configuration ...
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