The default configuration in most databases is meant for broad compatibility rather than performance. Database tuning is a process in which the configurations of a database are modified to achieve optimal performance. Databases have hundreds of configuration knobs that control various factors, such as the amount of memory to use for caches or how often the data is written to the storage. The problem with these knobs is that they are not standardized (i.e., two databases may have a different name for the same knob),  not independent (i.e., changing one knob can impact others),  and not universal (i.e., what works for one application may be suboptimal for another).  In reality, information about the effects of the knobs typically comes only from (expensive) experience. OtterTune is automatic database tuning software that promises to overcome these problems. It uses machine learning to tune the configuration knobs of your database automatically to improve performance. In this episode, we interview Andy Pavlo. Andy is a Database Professor at Carnegie Mellon and Co-Founder of OtterTune. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Automatic Database Tuning with Andy Pavlo appeared first on Software Engineering Daily.

Originally published on January 1, 2022. Charlie Gerard is an incredibly productive developer.  In addition to being the author of Practical Machine Learning in JavaScript, her website charliegerard.dev has a long list of really interesting side projects exploring the intersection of human computer interaction, computer vision, interactivity, and art.  In this episode we touch on some of these projects and broadly explore how practical it is to bring interesting HCI concepts into one’s work. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Practical Machine Learning in JavaScript with Charlie Gerard appeared first on Software Engineering Daily.

At Lyft, Ketan Umare worked on Flyte, an orchestration system for machine learning. Flyte provides reliability and APIs for machine learning workflows, and is used at companies outside of Lyft such as Spotify. Since leaving Lyft, Ketan founded Union.ai, a company focused on productionizing Flyte as a service. He joins the show to talk about the architecture and usage of Flyte, as well as how he is formulating the company around it. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Union.ai with Ketan Umare appeared first on Software Engineering Daily.

Historically, search engines made money by showing sponsored ads alongside organic results. As the idiom goes, if you’re not paying for something, you are the product. Neeva is a new take on search engines. When you search at neeva.com, you get the type of result you’d expect from a search engine minus any advertising. In this episode, I speak with Darin Fisher, Software Engineer at Neeva. We discuss the motivation, implementation, and mobile experience for searching with Neeva. Sponsorship inquiries: sponsor@softwareengineeringdaily.com   The post Ad-free Search on Neeva with Darin Fisher appeared first on Software Engineering Daily.

Charlie Gerard is an incredibly productive developer.  In addition to being the author of Practical Machine Learning in JavaScript, her website charliegerard.dev has a long list of really interesting side projects exploring the intersection of human computer interaction, computer vision, interactivity, and art.  In this episode we touch on some of these projects and broadly explore how practical it is to bring interesting HCI concepts into one’s work. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Practical Machine Learning in JavaScript with Charlie Gerard appeared first on Software Engineering Daily.

Once a machine learning model is trained and validated, it often feels like a major milestone has been achieved.  In reality, it’s more like the first lap in a relay race.  Deploying ML to production bears many similarities to a typical software release process, but brings several novel challenges like failing to generalize as expected or model drift. AI Quality management is the biggest challenge in AI today.  In this episode, I interview Anupam Datta, the co-founder at TruEra.  TruEra has a solution aimed at helping with AI performance, monitoring, and model explainability.  We talk about some of the challenges of modern machine learning deployment in production and how companies are succeeding with ML Ops. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Responsibly Deploy AI in Production with Anupam Datta appeared first on Software Engineering Daily.

Machine learning models must first be trained.  That training results in a model which must be serialized or packaged up in some way as a deployment artifact.  A popular deployment path is using Tensorflow.js to take advantage of the portability of JavaScript, allowing your model to be run on a web server or client. Gant Laborde is Chief Innovation Officer at Infinite Red, a React Native consulting team and the author of Learning TensorFlow.js: Powerful Machine Learning in JavaScript from O’Reilly.  In this interview, we explore use cases for Tensorflow.js. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Learning Tensorflow.js with Gant Laborde appeared first on Software Engineering Daily.

Imagine a world where you own some sort of building whether that’s a grocery store, a restaurant, a factory… and you want to know how many people reside in each section of the store, or maybe how long did the average person wait to be seated or how long did it take the average factory worker to complete their assembly task. Currently today these systems are either not using AI and instead use a mix of sensors and buttons to track certain actions or they do use AI but in a way that’s highly specific to their use case and hard to easily modify for new use cases that come down the line. This is where BrainFrame comes in. BrainFrame is a tool that connects to all your on-prem cameras and lets you easily leverage AI models and business logic. Alex Thiele is the CTO of Aotu the company that makes BrainFrame and he joins me today to talk about BrainFrame and the vision for a future where computer vision can be run by anyone. This episode is hosted by David Cohen. David is a Software Engineering Lead at LinkedIn where he works on backend applications and APIs that power their enterprise data systems. In his free time, he is an AI enthusiast and enjoys talking about all things Software. You can contact him on LinkedIn or Twitter. Sponsorship inquiries: sponsor@softwareengineeringdaily.com Show Notes: BrainFrame OpenCV BrainFrame Capsules The post No Code AI for Video Analytics with Alex Thiele appeared first on Software Engineering Daily.

The dream of machines with artificial general intelligence is entirely plausible in the future, yet well beyond the reach of today’s cutting edge technology.  However, a virtual agent need not win in Alan Turing’s Imitation Game to be useful.  Modern technology can deliver on some of the promises of narrow intelligence for accomplishing specific tasks. PeopleReign has created a virtual agent for IT and HR employee service.  This agent’s goal is not to replace a human agent but to augment them by handling some requests and elegantly handing off to a human in other cases.  In this episode, I speak with Dan Turchin, CEO of PeopleReign about their virtual agent and the future of work. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Virtual Agents for IT and HR with Dan Turchin appeared first on Software Engineering Daily.

Interest in autonomous vehicles dates back to the 1920s. It wasn’t until the 1980s that the first truly autonomous vehicle prototypes began to appear. The first DARPA Grand Challenge took place in 2004 offering competitors $1 million dollars to complete a 150-mile course through the Mojave desert. The prize was not claimed. Since then, rapid progress has begun in autonomous driving fueled by advances in sensor technology, software, and the hardware which runs it. Infrastructure has become a serious consideration for autonomous vehicle companies. In this episode, I speak with Vinoj Kumar, VP of Infrastructure at Cruise, the San Francisco company building an all-electric self-driving rideshare and delivery service. They’re tackling the infinite longtail scenarios of city driving and helping Walmart with self-driving grocery delivery. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post Autonomous Driving Infrastructure with Vinoj Kumar appeared first on Software Engineering Daily.