Edge AI Just Got Faster
When Meta released LLaMA back in February, many of us were excited to see a high-quality Large Language Model (LLM) become available for public access. Many of us who signed up however, had difficulties getting LLaMA to run on our edge and personal computer devices. One month ago, Georgi Gerganov started the llama.cpp project to provide a solution to this, and since then his project has been one o
An oral history of Bank Python November 2021 The strange world of Python, as used by big investment banks High finance is a foreign country; they do things differently there Today will I take you through the keyhole to look at a group of software systems not well known to the public, which I call "Bank Python". Bank Python implementations are effectively proprietary forks of the entire Python ecos
Note: See the accompanying GitHub repo for this blogpost here. ChatGPT has taken the world by storm. Millions are using it. But while it’s great for general purpose knowledge, it only knows information about what it has been trained on, which is pre-2021 generally available internet data. It doesn’t know about your private data, it doesn’t know about recent sources of data. Wouldn’t it be useful i
Getting started What is NumPy? Installation NumPy quickstart NumPy: the absolute basics for beginners Fundamentals and usage NumPy fundamentals NumPy for MATLAB users NumPy tutorials NumPy how-tos Advanced usage and interoperability Using NumPy C-API F2PY user guide and reference manual Under-the-hood documentation for developers Interoperability with NumPy Extras Glossary Release notes 2.5.0 2.4.
38TB of data accidentally exposed by Microsoft AI researchers | Wiz Blog
38TB of data accidentally exposed by Microsoft AI researchers Wiz Research found a data exposure incident on Microsoft’s AI GitHub repository, including over 30,000 internal Microsoft Teams messages – all caused by one misconfigured SAS token Executive summary Microsoft’s AI research team, while publishing a bucket of open-source training data on GitHub, accidentally exposed 38 terabytes of additi
A typical PyTorch training program on 8 GPUs with 4 dataloaderworkers per GPU would create at least processes.A naive use of PyTorch dataset and dataloader can easilyreplicate your dataset's RAM usage by 40 times. This issue has probably affected everyone who has done anything nontrivial with PyTorch.In this post, we will explain why it happens, and how to avoid the 40x RAM usage. All code example
1. はじめに こんにちは、morioka12 です。 本稿では、CTFtime のイベントに記載されている2022年に開催された CTF のイベントで、Cloud に関する問題をピックアップして攻撃手法やセキュリティ視点での特徴について紹介します。 また、昨年の2021年版は以下で紹介していますので、良ければこちらもご覧ください。 昨年のブログでは、各サービスにセキュリティ的な視点で紹介しましたが、今回は説明が重複するため、各問題に焦点を当てて大まかに紹介します。 scgajge12.hatenablog.com 1. はじめに 1.1 調査対象 2. Cloud 環境におけるセキュリティ視点 2.1 脆弱性攻撃によるクレデンシャルの取得 Amazon EC2 AWS Lambda 2.2 設定不備やハードコーディングによるクレデンシャルの取得 Amazon S3 Amazon RDS
New research, tooling, and partnerships for more secure AI and machine learning | Microsoft Security Blog
Today we’re on the verge of a monumental shift in the technology landscape that will forever change the security community. AI and machine learning may embody the most consequential technology advances of our lifetime, bringing huge opportunities to build, discover, and create a better world. Brad Smith recently pointed out that 2023 will likely mark the inflection point for AI going mainstream, t
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An oral history of Bank Python
Tutorial: ChatGPT Over Your Data
NumPy 2.0.0 Release Notes — NumPy v2.5.dev0 Manual
Demystify RAM Usage in Multi-Process Data Loaders
CTF Cloud 問題の攻撃手法まとめ(2022年版) - blog of morioka12