Categories: FAANG

On Device Llama 3.1 with Core ML

Many app developers are interested in building on device experiences that integrate increasingly capable large language models (LLMs). Running these models locally on Apple silicon enables developers to leverage the capabilities of the user’s device for cost-effective inference, without sending data to and from third party servers, which also helps protect user privacy. In order to do this, the models must be carefully optimized to effectively utilize the available system resources, because LLMs often have high demands for both memory and processing power.
This technical post details how to…
AI Generated Robotic Content

Recent Posts

New fire just dropped: ComfyUI-CacheDiT ⚡

ComfyUI-CacheDiT brings 1.4-1.6x speedup to DiT (Diffusion Transformer) models through intelligent residual caching, with zero…

16 hours ago

A Beginner’s Reading List for Large Language Models for 2026

  The large language models (LLMs) hype wave shows no sign of fading anytime soon:…

16 hours ago

How Clarus Care uses Amazon Bedrock to deliver conversational contact center interactions

This post was cowritten by Rishi Srivastava and Scott Reynolds from Clarus Care. Many healthcare…

16 hours ago

Build intelligent employee onboarding with Gemini Enterprise

Employee onboarding is rarely a linear process. It’s a complex web of dependencies that vary…

16 hours ago

Epstein Files Reveal Peter Thiel’s Elaborate Dietary Restrictions

The latest batch of Jeffrey Epstein files shed light on the convicted sex offender’s ties…

17 hours ago

A tiny light trap could unlock million qubit quantum computers

A new light-based breakthrough could help quantum computers finally scale up. Stanford researchers created miniature…

17 hours ago