Ask Sendai

A team of researchers at the MIT Computer Science & Artificial Intelligence Lab (CSAIL) recently released a framework called TextFooler which successfully tricked state-of-the-art NLP models (such as BERT) into making incorrect predictions. Source: infoq.com

Best practices have emerged around “microservice” architecture and “12-factor app” design. As cloud, containers, and container orchestrators (.g. Kubernetes) have become popular, new solutions to address common integration principles have emerged. This article discusses the approach of using ‘mecha’ components to provide enterprise integration pattern functionality for microservices. Source: infoq.com

At Spotify, we believe strongly in data-informed decision making. Whether we’re considering a big shift in our product strategy or we’re making a relatively quick decision about which track to add to one of our editorially-programmed playlists, data provides a foundation for sound decision making. An insight is a conclusion drawn from data that can help influence decisions and drive change. To enable Spotifiers to make faster, smarter decisions, we’ve developed a suite of internal products to accelerate the production and consumption of insights.

When Sanketh and I set out to raise our seed round for Smartcar, we found several pitch decks from consumer startups, however we struggled to find any from B2B or developer-focused companies. To give back to the startup community, we are making our original pitch deck (with a few retractions) that got us a $2 million seed round from Andreessen Horowitz available to everyone. Sanketh and I set out to build an app for our car in 2014.

Git has a handy feature when it comes to preventing accidental file check-ins when the files are meant to stay local. The obvious candidates are compiled binaries when you only want to check in the source code. Other candidates are files with local configurations. One can put all of those files and paths into a .gitignore file in the project. To persist those changes (and to share the common file contents with collaborators on the project), one usually adds the .

A passenger opens the app, requests a ride, and just a few minutes later there is a car with a friendly driver in front of them. They may know this driver went through a background check and other vetting; however, many might not realize all the complexity in the on-boarding process. Driver and vehicle requirements vary substantially across markets (and even at very proximate locations) due to varying market dynamics and government regulations.

Spotify built its business on flawless content delivery. Our streaming platform serves up more than 50 million tracks (plus an array of images and other assets) to more than 230 million monthly active users around the world — making us one of the world’s leading streaming services. With content that feels instant and immersive, we help our customers have the best experience possible with their favorite artists. Behind the scenes, our technology has evolved over time to achieve our user experience goals.

Google’s AI tool for developers won’t add gender labels to images anymore, saying a person’s gender can’t be determined just by appearance. The company emailed developers about the change to its Cloud Vision API tool, which developers use to analyze images and identify faces, landmarks, explicit content, and other recognizable features. Source: theverge.com

Thomas Kurian runs cloud computing at Google, which appears to be rethinking open-source foundations. Google has been one of big tech’s biggest supporters of open-source software. But customers, partners and members of the open-source community say the company is shifting its priorities. Consider the case of the open-source project Istio, whose future was thrown into question late last year. Istio is a ‘service mesh,’ a tool that helps technology organizations manage application strategies built around microservices.

Over the years at Capital One, the Spark framework evolved into the technology of choice for high volume real-time streaming and batch needs. After noticing some pains that come with operating the Spark infrastructure, the team decided to find a simpler, low maintenance yet highly scalable pattern and designed a Serverless Streaming solution around it: Apache Spark. Ever wonder what it was like to wait for a monthly statement to arrive to find any erroneous transactions on your account?