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Local LLM setup: how to use RAG and an embedding model to stop wasting context

Local LLMs degrade fast when context fills up. An embedding model and RAG pipeline fixes that — and runs entirely on your ...
TheServerSide

Run Llama LLMs on your laptop with Hugging Face and Python

There are numerous ways to run large language models such as DeepSeek, Claude or Meta's Llama locally on your laptop, including Ollama and Modular's Max platform. But if you want to fully control the ...
9to5Mac

Apple taught an LLM to predict tokens up to 5x faster in math and coding tasks

A new research paper from Apple details a technique that speeds up large language model responses, while preserving output quality. Here are the details. Traditionally, LLMs generate text one token at ...
Business Wire

Inception Launches Mercury 2, the Fastest Reasoning LLM — 5x Faster Than Leading Speed-Optimized LLMs, with Dramatically Lower Inference Cost

PALO ALTO, Calif.--(BUSINESS WIRE)--Inception, the company behind the first commercial diffusion large language models (dLLMs), today announced the launch of Mercury 2, the fastest reasoning LLM and ...
InfoWorld

3 of the best LLM integration tools for R

Do you need to add LLM capabilities to your R scripts and applications? Here are three tools you'll want to know. When we first looked at this space in late 2023, many generative AI R packages focused ...
Ars Technica

Google’s Gemma 4 AI models get 3x speed boost by predicting future tokens

Google launched its Gemma 4 open models this spring, promising a new level of power and performance for local AI. Google’s take on edge AI could be getting even faster already with the release of ...