std::ranges::sort(v); const auto medianIndex = std::size(v) / 2; return v[medianIndex]; } 6Evolution of a Median Algorithm Pete Isensee Engineering Director 7Goal 8 template

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feels like a new language” again, for the whole language?5 Major improvement via directed evolution 10 simpler metric: 90% of today’s guidance not needed 50 safer metric: 98% fewer type personal experiment My hope: To start a conversation about what could be possible within C++’s own evolution to rejuvenate C++ W A R N I N G EXPERIMENT IN PROGRESS github.com/hsutter/cppfront cppfront Objective-C) C++ examples — TypeScript Swift(A) “10%” incremental evolution-as-usual plan Default for existing evolution JS & other examples 10% Status quo language (e.g., JavaScript, C++, Objective-C)

can outpace us. The pace and scope of change related to the artificial intelligence technology evolution is indeed unprecedented, as supported by the data. This document is filled with user, usage and Internet User Ramps Powered by AI from Get-Go = Growth We Have Not Seen Likes of Before • AI & Work Evolution = Real + Rapid 3 1 2 3 4 5 6 7 8 9-51 52-128 129-152 153-247 248-298 299-307 308-322 Tower (5/25) 5/23 4/25 Mobile App Monthly Active Users, MM Details on Page 315 AI & Work Evolution = Real + Rapid 8 USA IT Jobs – AI vs. Non-AI Details on Page 302 +448% -9% 1/18 4/25 Source:

Receiving E-Mail Mes- sages ........................................................ 61 3.4.1. Using Evolution Mail ................ 61 3.4.2. Using an Alternative E-Mail Client ............................ three are inter-linked, there are distinct differences which are made clearer when looking at their evolution. 1.2.1. The Free Software Movement In the 1960s, it was typical for software to be distributed technical, hard core open source programming tool. Thousands of developers con- tributed to its evolution as it became more user friendly. This has resulted in the launch of hundreds of commer- cial and

(4) evolution of libprocess (5) eventuals (6) scheduling (7) streams (8) type erasurechapters (1) motivating futures/promises + actors (2) libprocess (3) revisiting the problem (4) evolution of (4) evolution of libprocess (5) eventuals (6) scheduling (7) streams (8) type erasurechapters (1) motivating futures/promises + actors (2) libprocess (3) revisiting the problem (4) evolution of (4) evolution of libprocess (5) eventuals (6) scheduling (7) streams (8) type erasurechapters (1) motivating futures/promises + actors (2) libprocess (3) revisiting the problem (4) evolution of

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 3.4.1 使用 Evolution 邮件客户端 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 3.4.2 使用其他电子邮件客户端 . . . . . . 7 使用 Ubuntu 软件中心安装应用程序 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 1.8 Evolution 邮件客户端 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 图片 11 Ubuntu 桌面培训 目录 3.21 启动 Evolution 邮件 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 III.IV.I 使用 Evolution 邮件客户端 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 III.IV.II 使用其他电子邮件客户端 . . . . 8 使用 Ubuntu 软件中心安装应用程序 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 I.9 Evolution 邮件客户端 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 III.23 启动 Evolution 邮件 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

(Ruibo) • University of Washington, department of applied mathematics • Cancer Modeling Group: Evolution of cancer initiation • Group leader: Personal programming advisor: initiation • The mathematical model and simulation study • Generate a single tumor (A single step of evolution) • Generate multiple tumors (Tasked Based Concurrency) • Obtain statistical properties of the tumors cancer is found early, it may be easier to treat or cure • Mathematical models help understand the evolution quantitatively. (e.g. predict the window of opportunity for screening) National Cancer Institute

(1.); 24 // Computation 25 auto evolution = compute(hubble_0 , omega_r0 , omega_m0 , omega_l0 , omega_k0 , h, a0); 26 // Output 27 std :: cout << std:: abs(evolution.back ()[0] / (1. E9 ∗ year )) << // Variables 5 T t = 0; 6 T a = a0; 7 // Output 8 std ::vector > evolution; 9 evolution.reserve (( static_cast (1) / hubble_0) / h); 10 // Function to integrate 11 auto da_dt numeric_limits :: epsilon ()) { 21 evolution. emplace_back (std ::array {{t, a}}); 22 a = a − h ∗ da_dt(t, a); 23 t = t − h; 24 } 25 // Output 26 return evolution; 27 } CppCon - Vincent Reverdy

concern?Quality Ownership Knowledge Evolution Innovation TransformationWhat-If? Did you consider? Suggest Better ways Ask about Simplicity Remind about Evolution Identify Technical DebtWhat-If DebtWhat-If? Did you consider? Suggest Better ways Ask about Simplicity Remind about Evolution Identify Technical DebtDoesn’t really happen Reviewer less prepared Multiple cycles Too Late each otherModernisation/gradual introduction of new Ways of workingQuality Ownership Knowledge Evolution Transformations InnovationCan we do better?Pair ProgrammingMistakes by Driver Mistakes by