OpenAIのBatch APIを使ってお得にプロンプトを一括処理してみる - Taste of Tech Topics
はじめに こんにちは。データサイエンスチームYAMALEXのSsk1029Takashiです。 最近はOpenAIに日本支社が出来て、日本語対応が加速するというニュースにわくわくしています。 今回はそんなOpenAIから発表されたBatch APIという機能が便利、かつお得な機能だったのでどのように使えるのか試してみます。 Introducing the Batch API: save costs and get higher rate limits on async tasks (such as summarization, translation, and image classification). Just upload a file of bulk requests, receive results within 24 hours, and get 50% off API pri
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
What We Learned from a Year of Building with LLMs (Part I)
It’s an exciting time to build with large language models (LLMs). Over the past year, LLMs have become “good enough” for real-world applications. The pace of improvements in LLMs, coupled with a parade of demos on social media, will fuel an estimated $200B investment in AI by 2025. LLMs are also broadly accessible, allowing everyone, not just ML engineers and scientists, to build intelligence into
There are millions of GitHub repos and filtering them is an insane amount of work. It takes a huge time, effort, and a lot more. We have done this for you. In this article, we’ll share a curated list of 100+ widely-known, recommended, and most popular repositories and open source GitHub projects for Machine Learning and Deep Learning. So without further ado, Let’s see all the hubs created by exper
This article is a translation, the original version is available here. I started using the OCaml language regularly around 2012, and since then, my interest and enthusiasm for this language have only grown. It has become my preferred choice for almost all my personal projects, and it has also influenced my professional choices. Since 2014, I have been actively participating in public conferences d
Exactly ten years ago today, we published "Why We Created Julia", introducing the Julia project to the world. At this point, we have moved well past the ambitious goals set out in the original blog post. Julia is now used by hundreds of thousands of people. It is taught at hundreds of universities and entire companies are being formed that build their software stacks on Julia. From personalized me
The Pitchfork Story
A bit more than two years ago, as part of my work in Shopify’s Ruby and Rails Infrastructure team, I released a new Ruby HTTP server called Pitchfork. It has a bit of an unusual design and makes hard tradeoffs, so I’d like to explain the thought process behind these decisions and how I see the future of that project. Unicorn’s Design Is Fine Ever since I joined Shopify over 11 years ago, the main
Accelerating Generative AI with PyTorch: Segment Anything, Fast – PyTorch
Blog Accelerating Generative AI with PyTorch: Segment Anything, Fast This post is the first part of a multi-series blog focused on how to accelerate generative AI models with pure, native PyTorch. We are excited to share a breadth of newly released PyTorch performance features alongside practical examples of how these features can be combined to see how far we can push PyTorch native performance.
Double Machine Learning Algorithm# Main Features# Double / debiased machine learning Chernozhukov et al. (2018) for Partially linear regression models (PLR) Partially linear IV regression models (PLIV) Interactive regression models (IRM) Interactive IV regression models (IIVM) The object-oriented implementation of DoubleML is very flexible. The model classes DoubleMLPLR, DoubleMLPLIV, DoubleMLIRM
Home > Computer Vision > Mastering All YOLO Models from YOLOv1 to YOLOv12: Papers Explained (2025) What is YOLO? You Only Look Once (YOLO): Unified, Real-Time Object Detection is a single-stage object detection model published at CVPR 2016, by Joseph Redmon, famous for having low latency and high accuracy. The entire YOLO series of models is a collection of pioneering concepts that have shaped tod
Simon Peyton Jones
Recorded 2022-02-01. Published 2022-03-25. Simon Peyton Jones is interviewed by Andres Löh and Joachim Breitner. Simon is the creator of Haskell and in this episode he talks about his new position at Epic, the origins of Haskell and why “it feels right”, and the (extra)ordinary Haskell programmers. Andres Löh: Hello Simon. Thank you so much for joining us today. Simon Peyton Jones: Hi Andres, hi J
Essential Machine Learning Equations: A Reference Guide
Why This Guide Exists I created this as a practical reference for the mathematical foundations of machine learning. It’s not comprehensive (no guide could be), but it covers equations I find myself returning to regularly. Each section includes working Python implementations that I’ve tested or used at some point. This started from a tweet by @goyal__pramod and grew as I collected formulas I actual
Paul: Today’s spotlight: Paolo Perrone, master of turning tech into scroll-stopping content. This one’s packed, let’s go 👀 ↓ I’m going to be honest with you. Most AI agent tutorials are garbage. They show you how to copy-paste LangChain code, build a demo that breaks the moment you try anything real, and leave you feeling like you learned something. Three months later, you try to build something
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