Categories: FAANG

Apple Intelligence Foundation Language Models Tech Report 2025

We introduce two multilingual, multimodal foundation language models that power Apple Intelligence features across Apple devices and services: (i) a ∼3B-parameter on-device model optimized for Apple silicon through architectural innovations such as KV-cache sharing and 2-bit quantization-aware training; and (ii) a scalable server model built on a novel Parallel-Track Mixture-of-Experts (PT-MoE) transformer that combines track parallelism, mixture-of-experts sparse computation, and interleaved global–local attention to deliver high quality with competitive cost on Apple’s Private Cloud Compute…
AI Generated Robotic Content

Recent Posts

Mugen – Modernized Anime SDXL Base, or how to make Bluvoll tiny bit less sane

Your monthly "Anzhc's Posts" issue have arrived. Today im introducing - Mugen - continuation of…

9 hours ago

Mugen – Modernized Anime SDXL Base, or how to make Bluvoll tiny bit less sane

Your monthly "Anzhc's Posts" issue have arrived. Today im introducing - Mugen - continuation of…

9 hours ago

From Prompt to Prediction: Understanding Prefill, Decode, and the KV Cache in LLMs

This article is divided into three parts; they are: • How Attention Works During Prefill…

9 hours ago

From Prompt to Prediction: Understanding Prefill, Decode, and the KV Cache in LLMs

This article is divided into three parts; they are: • How Attention Works During Prefill…

9 hours ago

7 Essential Python Itertools for Feature Engineering

Feature engineering is where most of the real work in machine learning happens.

9 hours ago

7 Essential Python Itertools for Feature Engineering

Feature engineering is where most of the real work in machine learning happens.

9 hours ago