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  • 大実験!ChatGPTは競プロの問題を解けるのか (2024年5月版) - E869120's Blog

    1. はじめに 2024 年 5 月 14 日、OpenAI 社から新たな生成 AI「GPT-4o」が発表され、世界に大きな衝撃を与えました。これまでの GPT-4 よりも性能を向上させただけでなく1、音声や画像のリアルタイム処理も実現し、さらに応答速度が大幅に速くなりました。「ついにシンギュラリティが来てしまったか」「まるで SF の世界を生きているような感覚だ」という感想も見受けられました。 しかし、いくら生成 AI とはいえ、競技プログラミングの問題を解くのは非常に難しいです。なぜなら競技プログラミングでは、問題文を理解する能力、プログラムを実装する能力だけでなく、より速く答えを求められる解法 (アルゴリズム) を考える能力も要求されるからです。もし ChatGPT が競技プログラミングを出来るようになれば他のあらゆるタスクをこなせるだろう、と考える人もいます。 それでは、現代最強の

      大実験!ChatGPTは競プロの問題を解けるのか (2024年5月版) - E869120's Blog
    • GPT in 60 Lines of NumPy | Jay Mody

      January 30, 2023 In this post, we'll implement a GPT from scratch in just 60 lines of numpy. We'll then load the trained GPT-2 model weights released by OpenAI into our implementation and generate some text. Note: This post assumes familiarity with Python, NumPy, and some basic experience with neural networks. This implementation is for educational purposes, so it's missing lots of features/improv

      • Taming Floating-Point Sums | orlp.net

        Suppose you have an array of floating-point numbers, and wish to sum them. You might naively think you can simply add them, e.g. in Rust: fn naive_sum(arr: &[f32]) -> f32 { let mut out = 0.0; for x in arr { out += *x; } out } This however can easily result in an arbitrarily large accumulated error. Let’s try it out: naive_sum(&vec![1.0; 1_000_000]) = 1000000.0 naive_sum(&vec![1.0; 10_000_000]) = 1

        • Golang Mini Reference 2022: A Quick Guide to the Modern Go Programming Language (REVIEW COPY)

          Golang Mini Reference 2022 A Quick Guide to the Modern Go Programming Language (REVIEW COPY) Harry Yoon Version 0.9.0, 2022-08-24 REVIEW COPY This is review copy, not to be shared or distributed to others. Please forward any feedback or comments to the author. • feedback@codingbookspress.com The book is tentatively scheduled to be published on September 14th, 2022. We hope that when the release da

          • AST vs. Bytecode: Interpreters in the Age of Meta-Compilation

            233 AST vs. Bytecode: Interpreters in the Age of Meta-Compilation OCTAVE LAROSE, University of Kent, UK SOPHIE KALEBA, University of Kent, UK HUMPHREY BURCHELL, University of Kent, UK STEFAN MARR, University of Kent, UK Thanks to partial evaluation and meta-tracing, it became practical to build language implementations that reach state-of-the-art peak performance by implementing only an interprete

            • Fizz Buzz with Cosines - Susam Pal

              Fizz Buzz is a counting game that has become oddly popular in the world of computer programming as a simple test of basic programming skills. The rules of the game are straightforward. Players say the numbers aloud in order beginning with one. Whenever a number is divisible by 3, they say 'Fizz' instead. If it is divisible by 5, they say 'Buzz'. If it is divisible by both 3 and 5, the player says

              • PowerShell: the object-oriented shell you didn’t know you needed

                PowerShell is an interactive shell and scripting language from Microsoft. It’s object-oriented — and that’s not just a buzzword, that’s a big difference to how the standard Unix shells work. And it is actually usable as an interactive shell. Getting Started PowerShell is so nice, Microsoft made it twice. Specifically, there concurrently exist two products named PowerShell: Windows PowerShell (5.1)

                • Accelerate Python code 100x by import taichi as ti | Taichi Docs

                  Python has become the most popular language in many rapidly evolving sectors, such as deep learning and data sciences. Yet its easy readability comes at the cost of performance. Of course, we all complain about program performance from time to time, and Python should certainly not take all the blame. Still, it's fair to say that Python's nature as an interpreted language does not help, especially

                  • Manuel Cerón

                    Last year I finally decided to learn some Rust. The official book by Steve Klabnik and Carol Nichols is excellent, but even after reading it and working on some small code exercises, I felt that I needed more to really understand the language. I wanted to work on a small project to get some hands-on experience, but most of my ideas didn’t feel very well suited for Rust. Then I started reading the

                    • What's New in Emacs 28.1?

                      Try Mastering Emacs for free! Are you struggling with the basics? Have you mastered movement and editing yet? When you have read Mastering Emacs you will understand Emacs. It’s that time again: there’s a new major version of Emacs and, with it, a treasure trove of new features and changes. Notable features include the formal inclusion of native compilation, a technique that will greatly speed up y

                      • Type Parameters Proposal

                        Ian Lance Taylor Robert Griesemer August 20, 2021 StatusThis is the design for adding generic programming using type parameters to the Go language. This design has been proposed and accepted as a future language change. We currently expect that this change will be available in the Go 1.18 release in early 2022. AbstractWe suggest extending the Go language to add optional type parameters to type an

                        • The simplicity of Prolog

                          Back to homepage Nowadays the most popular programming languages are Python, Javascript, Java, C++, C#, Kotlin and Ruby, and the average programmer is probably familiar with one or more of these languages. It's relatively easy to switch from one to another (barring any framework specific knowledge that may be needed), since they are all imperative (and for the most part object-oriented) languages,

                          • The World's Smallest Hash Table | orlp.net

                            This December I once again did the Advent of Code, in Rust. If you are interested, my solutions are on Github. I wanted to highlight one particular solution to the day 2 problem as it is both optimized completely beyond the point of reason yet contains a useful technique. For simplicity we’re only going to do part 1 of the day 2 problem here, but the exact same techniques apply to part 2. We’re go

                            • Practical SQL for Data Analysis

                              Pandas is a very popular tool for data analysis. It comes built-in with many useful features, it's battle tested and widely accepted. However, pandas is not always the best tool for the job. SQL databases have been around since the 1970s. Some of the smartest people in the world worked on making it easy to slice, dice, fetch and manipulate data quickly and efficiently. SQL databases have come such

                                Practical SQL for Data Analysis
                              • A from-scratch tour of Bitcoin in Python

                                I find blockchain fascinating because it extends open source software development to open source + state. This seems to be a genuine/exciting innovation in computing paradigms; We don’t just get to share code, we get to share a running computer, and anyone anywhere can use it in an open and permissionless manner. The seeds of this revolution arguably began with Bitcoin, so I became curious to dril

                                • Python behind the scenes #6: how Python object system works

                                  As we know from the previous parts of this series, the execution of a Python program consists of two major steps: The CPython compiler translates Python code to bytecode. The CPython VM executes the bytecode. We've been focusing on the second step for quite a while. In part 4 we've looked at the evaluation loop, a place where Python bytecode gets executed. And in part 5 we've studied how the VM ex

                                  • Why APL is a language worth knowing

                                    “A language that doesn't affect the way you think about programming, is not worth knowing.”, by Alan J. Perlis. Why APL is a language worth knowing Alan Perlis, the computer scientist recipient of the first Turing award, wrote “A language that doesn't affect the way you think about programming, is not worth knowing.” ― Alan J. Perlis, 1982. Special feature: Epigrams on programming. ACM Sigplan Not

                                      Why APL is a language worth knowing
                                    • Loopr: A Loop/Reduction Macro for Clojure

                                      I write a lot of reductions: loops that combine every element from a collection in some way. For example, summing a vector of integers: (reduce (fn [sum x] (+ sum x)) 0 [1 2 3]) ; => 6 If you’re not familiar with Clojure’s reduce, it takes a reducing function f, an initial accumulator init, and a collection xs. It then invokes (f init x0) where x0 is the first element in xs. f returns a new accumu

                                      • Interprocedural Sparse Conditional Type Propagation

                                        It’s 11 o’clock. Do you know where your variables are pointing? def shout(obj) obj.to_s + "!" end It’s hard to tell just looking at the code what type obj is. We assume it has a to_s method, but many classes define methods named to_s. Which to_s method are we calling? What is the return type of shout? If to_s doesn’t return a String, it’s really hard to say. Adding type annotations would help… a l

                                          Interprocedural Sparse Conditional Type Propagation
                                        • The RAM myth

                                          December 19, 2024 Reddit Hacker NewsThe RAM myth is a belief that modern computer memory resembles perfect random-access memory. Cache is seen as an optimization for small data: if it fits in L2, it’s going to be processed faster; if it doesn’t, there’s nothing we can do. Most likely, you believe that code like this is the fastest way to shard data (I’m using Python as pseudocode; pretend I used y

                                            The RAM myth
                                          • NumPy for Data Science Beginners in Python

                                            NumPy library on Python is an essential tool for data scientists to work on numerical data, especially when they deal with data arrays, especially multi-dimensional, and need a memory-efficient fast indexing of arrays, However, knowing about other useful packages when solving data science problems is essential. So, let’s see which packages are available in Python programming language and are used

                                              NumPy for Data Science Beginners in Python
                                            • Linear-time parser combinators

                                              My birthday just passed, and to relax I wrote a parser combinator library. Over the last few years, I have worked quite a bit with Ningning Xie and Jeremy Yallop on parser combinators, which has led to a family of parser combinators which have optimal linear-time performance in theory, and which are many times faster than lex+yacc in practice. But these use advanced multistage programming techniqu

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