Training an LLM in Swift, Part 2: macOS built-in frameworks🔒 SSL Verified

Table of Contents

• ↓ Training an LLM in Swift, Part 1: Taking matrix multiplication from Gflop/s to Tflop/s
• ↓ Have LLMs improved for Swift coding in the last 12 months?
• ↓ Using Copilot to write a raindrop audio synthesizer using AVAudioEngine
• ↓ App architecture basics in SwiftUI Part 4: Services
• ↓ App architecture basics in SwiftUI Part 3: Module-separated layers
• ↓ App architecture basics in SwiftUI, Part 2: SwiftUI's natural pattern
• ↓ Top Alternatives to cocoawithlove.com

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"Articles about Swift, Cocoa, software design and programming."

"Covering the Accelerate, BNNS, CoreML and MPS implementations in macOS."

"In this article, I’m going to look at some of the frameworks that are built into macOS for numerical algorithms. Fitting with the theme of this series, I’ll mostly be looking at frameworks that can also train an ML model. But there’s a lot of different approaches – Accelerate (BLAS), BNNS, CoreML, MPSGraph – and the real challenge is knowing which one to use …"

"10 implementations of handwritten matrix multiplication: from plain C and Swift through to Metal"

Key Topics & Focus Areas for cocoawithlove.com:

Training an LLM in Swift, Part 1: Taking matrix multiplication from Gflop/s to Tflop/s

Have LLMs improved for Swift coding in the last 12 months?

Using Copilot to write a raindrop audio synthesizer using AVAudioEngine

App architecture basics in SwiftUI Part 4: Services

App architecture basics in SwiftUI Part 3: Module-separated layers

App architecture basics in SwiftUI, Part 2: SwiftUI's natural pattern