Goostman, a chatbot, passes the Turing Test, with 1/3 of judges believing that Eugene is human 6/18: OpenAI releases GPT-1, the first of their large language models 6/20: OpenAI releases vs. 2023 (1 year) AI Development Trending = Unprecedented41 AI Performance = In 2024… Surpassed Human Levels of Accuracy & Realism, per Stanford HAI AI System Performance on MMLU Benchmark Test – 2019-2024 knowledge and problem-solving in large language models. 89.8% is the generally-accepted benchmark for human performance. Stats above show average accuracy of top-performing AI models in each calendar year.

model condenses information, using 
 agreed-upon-metrics for accuracy, relevance, and coherence. 03 Human trainers Comparing AI results to responses from expert advisors, grading for accuracy and relevance process huge amounts of data from many sources, it can create customer experiences that feel more human because they’re more relevant and personalized. Indeed, the world’s No. 1 job site, uses GPT-4o find the right jobs—and understanding why a given opportunity is right for them—is a profoundly human outcome. Indeed's team has used AI to help connect more people 
 to jobs, faster—a win for everyone

cannot eliminate error by eliminating the people who caused the error. 1. “Human error is not our cause of troubles; instead, human error is a consequence of the design of the tools that we gave them.”

creating quality cannot. To have humans executing tests that should be automated is a waste of human potential.” iii. Aggressively resolve unreliable tests and false positives iv. Focus on automating new work as long as responsibility for immediately resolving the issue is addressed v. Changing human behaviors and incentives is more challenging than the technical aspects n. WHY WE NEED TO PULL THE

primary purposes: to take advantage of Julia's powerful multiple-dispatch mechanism, to improve human readability, and to catch programmer errors. Describing Julia in the lingo of type systems, it is: expanded to interpolate the value of the argument into the final expression: julia> @sayhello("human") Hello, human We can view the quoted return expression using the function macroexpand (important note: macros): julia> ex = macroexpand(Main, :(@sayhello("human")) ) :(Main.println("Hello, ", "human")) julia> typeof(ex) Expr We can see that the "human" literal has been interpolated into the expression

primary purposes: to take advantage of Julia's powerful multiple-dispatch mechanism, to improve human readability, and to catch programmer errors. Describing Julia in the lingo of type systems, it is: expanded to interpolate the value of the argument into the final expression: julia> @sayhello("human") Hello, human We can view the quoted return expression using the function macroexpand (important note: macros): julia> ex = macroexpand(Main, :(@sayhello("human")) ) :(Main.println("Hello, ", "human")) julia> typeof(ex) Expr We can see that the "human" literal has been interpolated into the expression

primary purposes: to take advantage of Julia's powerful multiple-dispatch mechanism, to improve human readability, and to catch programmer errors. Describing Julia in the lingo of type systems, it is: expanded to interpolate the value of the argument into the final expression: julia> @sayhello("human") Hello, human We can view the quoted return expression using the function macroexpand (important note: macros): julia> ex = macroexpand(Main, :(@sayhello("human")) ) :(Main.println("Hello, ", "human")) julia> typeof(ex) Expr We can see that the "human" literal has been interpolated into the expression

primary purposes: to take advantage of Julia's powerful multiple-dispatch mechanism, to improve human readability, and to catch programmer errors. Describing Julia in the lingo of type systems, it is: expanded to interpolate the value of the argument into the final expression: julia> @sayhello("human") Hello, human We can view the quoted return expression using the function macroexpand (important note: macros): julia> ex = macroexpand(Main, :(@sayhello("human")) ) :(Main.println("Hello, ", "human")) julia> typeof(ex) Expr We can see that the "human" literal has been interpolated into the expression

primary purposes: to take advantage of Julia's powerful multiple-dispatch mechanism, to improve human readability, and to catch programmer errors. Describing Julia in the lingo of type systems, it is: expanded to interpolate the value of the argument into the final expression: julia> @sayhello("human") Hello, human We can view the quoted return expression using the function macroexpand (important note: macros): julia> ex = macroexpand(Main, :(@sayhello("human")) ) :(Main.println("Hello, ", "human")) julia> typeof(ex) Expr We can see that the "human" literal has been interpolated into the expression

已经实现了名为 fly 方法的类型 Human 上实现这两个 trait。每一个 fly 方法都进行了不同的 操作： 文件名：src/main.rs trait Pilot { fn fly(&self); } trait Wizard { fn fly(&self); } struct Human; impl Pilot for Human { fn fly(&self) println!("This is your captain speaking."); } } impl Wizard for Human { fn fly(&self) { println!("Up!"); } } impl Human { fn fly(&self) { println!("*waving arms furiously*"); fly 方法，并在直接定义有 fly 方法的 Human 类型上实现 这两个 trait 当调用 Human 实例的 fly 时，编译器默认调用直接实现在该类型上的方法，如示例 20-18 所 示。 文件名：src/main.rs 480/562Rust 程序设计语言 简体中文版 fn main() { let person = Human; person.fly(); }