koher

Foundation Models

At WWDC 25 Apple opened up the on-device large-language model that powers Apple Intelligence to every iOS, iPadOS, macOS and visionOS app via a new “Foundation Models” framework. The model is a compact ~3 billion-parameter LLM that has been quantized to just 2 bits per weight, so it runs fast, offline and entirely on the user’s device, keeping data private while still handling tasks such as summarization, extraction, short-form generation and structured reasoning. ([developer.apple.com][1], [machinelearning.apple.com][2]) Below is a developer-focused English-language overview—based mainly on Apple’s own announcements, docs and WWDC sessions—followed by ready-to-paste Swift code samples.

1. What Are Apple’s On-Device Foundation Models?

Apple ships two sibling LLMs: a device-scale model (~3 B params) embedded in Apple silicon and a server-scale mixture-of-experts model that runs inside Private Cloud Compute when more heft is required. ([machinelearning.apple.com][2]) The

koher

import SwiftUI
import Foundation
import FoundationModels
import AudioToolbox

enum Role: Hashable {
    case user
    case assistant
}

koher

// https://twitter.com/koher/status/1627284858493075463
for n in 2 ... 1000000 {
    var a = n * n - 1
    while a.isMultiple(of: 2) {
        a /= 2
    }
    while a.isMultiple(of: 5) {
        a /= 5
    }
    guard a == 1 else { continue }

koher

import Foundation

actor UUIDSerialNumberGenerator {
    static let shared: UUIDSerialNumberGenerator = .init()

    private var nextSerialNumber: Int = 0
    private var uuidToSerialNumber: [UUID: Int] = [:]

    private init() {}

koher

標準入力で1以上の整数が一つ与えられます。このとき、1から与えられた整数までの合計を計算して出力するプログラムを、Swiftで書いて下さい。

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次のようなSwiftプログラムを書くことで、1から与えられた整数までの合計を計算して出力できます。

import Foundation

// 入力

koher

import CoreGraphics

let vectors: [CGVector] = [CGVector(dx: 2, dy: 1), CGVector(dx: -3, dy: 0)]

// ∞ノルムの平均の計算

// extension なし
vectors.lazy
    .map { max($0.dx.magnitude, $0.dy.magnitude) }
    .reduce(0, +) / CGFloat(vectors.count)

koher

enum JSON {
    case number(Double)
    case boolean(Bool)
    case string(String)
    case array([JSON])
    case object([String: JSON])
    case null
}

extension JSON: Codable {

koher

// https://algo-method.com/tasks/302
func readInt3(line: Int = #line, file: String = #file) -> (Int, Int, Int) {
    let values = readLine()!.split(separator: " ").map { Int(String($0))! }
    precondition(values.count == 3)
    return (values[0], values[1], values[2])
}

var (n, x, y) = readInt3()

for _ in 2 ..< n {

koher

let aa = (1...100).shuffled().dropFirst(50).sorted()
print(aa.count, 100)
print(aa.map(\.description).joined(separator: " "))

let aaSet = Set(aa)

var count = 0
var ans: [Int] = []
for i in 1 ... 1000 {
    if aaSet.contains(i) { continue }

koher

let pp = readLine()!.split(separator: " ")
let e = pp[0]
let y = Int(pp[1])!
let m = Int(pp[2])!
let d = Int(pp[3])!

let dd = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]

struct YMD: Comparable {
    let y: Int