Amazon is encouraging sellers to use AI-generated product listings
Amazon is launching a new AI tool that generates product listings for sellers. The feature uses a large language model (LLM) “trained on large amounts of data” to make it faster and simpler for vendors to describe their products. The company describes the tool as distilling the “significant work” of creating titles, bullet points and descriptions down to “just one step.” Amazon says its Generative
GPTの仕組みと限界についての考察（１） - conceptualization
GPT4が登場してChatGPTが盛り上がってますね。 本記事は、GPT（を支えるTransformerという仕組み）をChatGPTユーザにとって分かりやすく説明し、その能力と限界についての見通しをよくしよう、という趣旨になります。 少し長くなりそうなので、全部で記事を3回に分けようと思います。 （１）大まかな背景と概要：本記事 （２）GPTの能力と可能性：実際の使用例とTransformerの仕組みを踏まえて説明 （３）GPTの限界と未来展望：Transformerの仕組みが持つ限界と研究の進展を予想 GPT3と4の違い： トークン長とは何か？ まずここから話を始めます。GPT-3は、パラメータ数が750億個（850GBの容量を食う）でトークン長が4097(GPT-3.5)でした。GPT-4は、パラメータ数は非公開でトークン長は32768ですので、ちょうど8倍になります。 さて、トーク
The Full Stack - LLM Bootcamp - Spring 2023
What are the pre-requisites for this bootcamp? Our goal is to get you 100% caught up to state-of-the-art and ready to build and deploy LLM apps, no matter what your level of experience with machine learning is. Please enjoy, and email us, tweet us, or post in our Discord if you have any questions or feedback! Learn to Spell: Prompt Engineering High-level intuitions for prompting Tips and tricks fo
The Embedding Archives: Millions of Wikipedia Article Embeddings in Many Languages
Read more about how this data was prepared and processed in the dataset card. What Can You Build with This?The sky's the limit to what you can build with this. A few common use cases include: Neural Search Systems Wikipedia is one of the world’s most valuable knowledge stores. This embedding archive can be used to build search systems that retrieve relevant knowledge based on a user query. In this
The Little Book of Deep Learning
The Little Book of Deep Learning François Fleuret François Fleuret is a professor of computer sci- ence at the University of Geneva, Switzerland. The cover illustration is a schematic of the Neocognitron by Fukushima [1980], a key an- cestor of deep neural networks. This ebook is formatted to fit on a phone screen. Contents Contents 5 List of figures 7 Foreword 8 I Foundations 10 1 Machine Learnin
東大が無料公開している超良質なPython/Data Science/Cloud教材まとめ (*随時更新) - Digital, digital and digital
東京大学がちょっとびっくりするくらいの超良質な教材を無料公開していたので、まとめました Python入門講座 東大のPython入門が無料公開されています。scikit-learnといった機械学習関連についても説明されています。ホントいいです Pythonプログラミング入門 東京大学 数理・情報教育研究センター: utokyo-ipp.github.io 東大のPython本も非常にオススメです Pythonによるプログラミング入門 東京大学教養学部テキスト: アルゴリズムと情報科学の基礎を学ぶ https://amzn.to/2oSw4ws Pythonプログラミング入門 - 東京大学 数理・情報教育研究センター Google Colabで学習出来るようになっています。練習問題も豊富です https://colab.research.google.com/github/utokyo-ip
Practical Deep Learning for Coders - Practical Deep Learning
A free course designed for people with some coding experience, who want to learn how to apply deep learning and machine learning to practical problems. This free course is designed for people (and bunnies!) with some coding experience who want to learn how to apply deep learning and machine learning to practical problems. Deep learning can do all kinds of amazing things. For instance, all illustra
Practical Deep Learning for Coders - The book
Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD is the book that forms the basis for this course. We recommend reading the book as you complete the course. There’s a few ways to read the book – you can buy it as a paper book or Kindle ebook, or you can read it for free online. The whole book is written as Jupyter notebooks, so you can also execute all the code in th
fast.ai - Mojo may be the biggest programming language advance in decades
I remember the first time I used the v1.0 of Visual Basic. Back then, it was a program for DOS. Before it, writing programs was extremely complex and I’d never managed to make much progress beyond the most basic toy applications. But with VB, I drew a button on the screen, typed in a single line of code that I wanted to run when that button was clicked, and I had a complete application I could now
書籍 Kaggleに挑む深層学習プログラミングの極意、を読み終えて - A Day in the Life
表題の書籍を読み終えてたので感想を。一言で言うと、短い内容にKaggle関係なく機械学習のエッセンスがぎゅっと詰まったインデックスとして解りやすい良書、機械学習初心者にもKaggle初心者にもオススメである。また自分(いちおう自分はKaggle Competitions Master である)も理解が浅かった部分の理解が進み、知らなかったテクニックもいくつもあり、機械学習エンジニアやKaggle有識者も得られるものが多いはずだ。 なお書籍、Kaggle に挑む深層学習プログラミングの極意は著者の一人である石原祥太郎氏から献本いただいたものである（ありがとうございます）。 この書籍の良さの一つは短いことである。索引を抜くと約200Pで、機械学習関連は分厚い書籍が多い中、程よくまとまっている。理論を説明する本はきちんと説明が入るので長くなるし、良くない本は分かりにくい内容でただただ冗長に説明、
A Survey of Large Language Models
Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language. As a major approach, language modeling has been widely studied for language understanding and generation in the past two decades, evolving from statistical language models to neural langu
OpenAIのEvalsを利用してLLMの性能をテストする方法｜mah_lab / 西見 公宏
OpenAIのGPT-4 APIのウェイティングリストに申し込むと、メールで以下のような内容が送られてきます。 While we ramp up, invites will be prioritized to developers who have previously build with the OpenAI API. You can also gain priority access if you contribute model evaluations to OpenAI Evals that get merged, as this will help us improve the models for everyone. OpenAI APIで開発したことがある開発者に優先的に招待します。また、OpenAI Evalsにモデル評価を投稿し、それがマージされた場合にも、優先的にアク
LangChain & GPT-4 for Code Understanding: Twitter Algorithm
Twitter open-sourced a part of its recommendation algorithm on March 31, 2023; we’re here for it. Read this article if you want to learn more about how to understand any codebase in seconds by using LangChain, LangChain’s Conversational Retriever Chain, Deep Lake, and GPT-4. As a bonus, you’ll also learn how the Twitter recommendation algorithm works and the top 10 tips for trending on Twitter in
Announcing New Tools for Building with Generative AI on AWS | Amazon Web Services
AWS Machine Learning Blog Announcing New Tools for Building with Generative AI on AWS The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of scalable compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are transforming their businesses. Just recently, generative AI app
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Machine Learning is …boring? - Blind
Getting Started With Embeddings
CMU Database Group
https://twitter.com/K_Ryuichirou/status/1654781736696582145
Automated Testing in Machine Learning Projects [Best Practices for MLOps]![Automated Testing in Machine Learning Projects [Best Practices for MLOps]](https://cdn-ak-scissors.b.st-hatena.com/image/square/ea026dd0c776a3fb1c2abc7cb26ed7747125ecd2/height=288;version=1;width=512/https%3A%2F%2Fneptune.ai%2Fwp-content%2Fuploads%2F2022%2F07%2Fblog_feature_image_008809_5_4_4_3.jpg)
https://arxiv.org/pdf/2210.03629.pdf