Skip to main content

Yankees’ Bats Are Too Much for the Red Sox in London


By JAMES WAGNER from NYT Sports https://ift.tt/2JisjXj

Comments

Popular posts from this blog

New top story on Hacker News: Ask HN: Is the EULA on my new $30k RED cinema camera legal?

Ask HN: Is the EULA on my new $30k RED cinema camera legal? 70 by red_throwaway | 77 comments on Hacker News. TLDR: I bought a $30K professional cinema camera that doesn't work unless I sign away my rights to privacy and possibly the video content I make with it ( at least it seems ) Over the past few years my photography business has seen a surge in demand for ultra high quality video production work. In an effort to meet this demand, I picked up one of RED Digital Cinema's newest pro camera bodies, the RED V-RAPTOR. Considering this camera is used by professional filmmakers to create films destined for cinemas, it's not surprising that it came with a $30k price tag. After unboxing and assembling it, I power the camera on and the first thing I see is a wall of legal text on the embedded LCD. Turns out it's a "Software License Agreement" that I'm required to consent to using the on-camera menu buttons before any of the camera's functionality becomes

New top story on Hacker News: Show HN: Eva AI-Relational Database System for Faster AI-Powered Applications

Show HN: Eva AI-Relational Database System for Faster AI-Powered Applications 28 by jarulraj | 0 comments on Hacker News. Hi friends, We are building EVA, an AI-Relational database system with first-class support for deep learning models. Our goal with EVA is to create a platform that supports AI-powered multi-modal database applications operating on structured (tables, feature vectors, etc.) and unstructured data (videos, podcasts, pdf, etc.) with deep learning models. EVA comes with a wide range of models for analyzing unstructured data, including models for object detection, OCR, text summarization, audio speech recognition, and more. The key feature of EVA is its AI-centric query optimizer. This optimizer is designed to speed up AI-powered applications using a collection of optimizations inspired by relational database systems. Two of the most important optimizations are: + Caching: EVA automatically reuses previous query results (e.g., inference results), eliminating redundant