Software Engineering Daily

At the first Software Engineering Daily Meetup, the speakers explored a range of topics. A few weeks ago, we published Courtland Allen’s talk about how to build a small software business. In today’s episode, we are publishing Haseeb Qureshi’s talk, called “Everything That Rises Must Converge: Why Engineers Disagree About Everything (And Why Fraudsters Do Too).” This talk explores philosophy, poker, software engineering, fraud, and a basket of other topics.Continue reading...

Security vulnerabilities are an important concern in systems. When we specify that we want certain information hidden, for example our phone number or our date of birth, we expect the system to hide the information. However, this doesn’t always happen due to human error in the code because programmers have to write checks and filters across the program. In this episode, Edaena Salinas interviews Jean Yang, Assistant Professor at theContinue reading...

Expectations for mobile apps have gone up steadily since the iPhone was released. But the choice of databases built for mobile apps has remained limited mostly to SQLite. RealmDB was created as a new option for mobile developers on iOS, Android, or any other mobile platform.   Realm is not just a database. It is a database platform, offering a variety of systems such as authentication, sync, and an eventContinue reading...

Online advertising is a system of transactions that involve many different players. The user visits a publisher’s website; the publisher notifies an exchange that the user is on the website; the exchange presents an opportunity to a marketplace that can buy that opportunity to show the end user the ad. And this a simple example. The transactions in online advertising are as opaque and rife with fraud as Wall Street–butContinue reading...

The impact of artificial intelligence on our everyday lives will be so profound that our modern institutions will change completely. Employment, government, romance, social norms–all of these things will be upended. To see the signs of this coming, you no longer have to read science fiction. Every week, there are blog posts, news stories, and videos chronicling our strange, exciting time. Rob May is an investor in artificial intelligence companiesContinue reading...

If you wanted to build a machine learning model to understand human health, where would you get the data? A hospital database would be useful, but privacy laws make it difficult to disclose that patient data to the public. In order to publicize the data safely, you would have to anonymize it, so that a patient’s identity could not be derived from data about that patient–and true anonymization is notoriouslyContinue reading...

Machine learning frameworks like Torch and TensorFlow have made the job of a machine learning engineer much easier. But machine learning is still hard. Debugging a machine learning model is a slow, messy process. A bug in a machine learning model does not always mean a complete failure. Your model could continue to deliver usable results even in the presence of a mistaken implementation. Perhaps you made a mistake whenContinue reading...

Data scientists need flexible interfaces for displaying and manipulating data sets. Data engineers need to be able to visualize how their data pipelines wire together databases and data processing frameworks. DevOps engineers need dashboards to understand their monitoring data at a high level. All of these programmers are building data applications. Data applications let us visualize and manipulate data sets effectively. In today’s episode, Dave King joins the show toContinue reading...

Infrastructure is a term that can mean many different things: your physical computer, the data center of your Amazon EC2 cluster, the virtualization layer, the container layer–on and on. In today’s episode, podcasters Chris Wahl and Ethan Banks discuss the past, present, and future of infrastructure with me. Ethan and Chris host Datanauts, a podcast about infrastructure. In each episode, Datanauts goes deep on a topic such as networking, serverless,Continue reading...

Deep learning uses neural networks to identify patterns. Neural networks allow us to sequence “layers” of computing, with each layer using learning algorithms such as unsupervised learning, supervised learning, and reinforcement learning. Deep learning has taken off in the last few years, but it has been around for much longer. Adam Gibson founded Skymind, the company behind Deeplearning4j. Deeplearning4j is a distributed deep learning library for Scala and Java. ItContinue reading...