Fritz AI allows developers to use mobile-optimized machine learning (ML) algorithms to create custom ML models (without code) for use in their apps.
In this article, we’ll walk you through the process of creating an image labeling ML model that can identify different car logos, and then integrating the model into an iOS app.
Continue reading “Implementing a Fritz AI Machine Learning Model in an iOS app”
In this article, we’ll discuss some foundational concepts in machine learning (ML) that are particularly important for mobile developers interested in working with ML.
Continue reading “Introduction to Machine Learning for iOS Developers”
In order to work with Fritz AI in Flutter, you’ll need some knowledge on how to write native Java/Kotlin code in Flutter. At the moment, there is no native plugin for working with Fritz AI in Flutter, however, since Flutter allows one to write native code, Fritz AI can still be integrated into Flutter. Let’s look at how the image labeling* API from Fritz can be integrated.
Katrina Iosia used to own a cake decorating business. Now, she creates even more tantalizing creations on Snapchat. The New Zealand born Niuean lens creator’s work, often inspired by the ocean, spans physical sculptures and mixed reality, with exhibitions in galleries and on the street.
Fascinated by her immensely creative work, I reached out to learn more about the artist.
Continue reading “Snapchat Lens Creator Spotlight: Katrina Iosia”
Every single one of us will intermittently try to conjure the right word for a given moment, pausing mid-sentence to try and remember it. For example, forgetting the name of a place caused this hesitation:
We can all relate to this, but as cognition declines, these pauses become more common and more pronounced.
Today we’re excited to introduce the Fritz AI Dataset Generator, a new component of Fritz AI Studio, designed to break down a major barrier between developers and the creation of incredible machine learning-powered mobile applications.
That barrier is data acquisition. Despite advances in neural network architectures and their optimizations for mobile deployment, there often isn’t enough available high-quality data on which to train those models.
Continue reading “Introducing the Fritz AI Dataset Generator for Mobile Machine Learning”
In this article, we’re going to see inout in action, work with value types, see how to use mutation tracking to our advantage, and explore the law of exclusivity.
Continue reading “Exclusivity and Mutation Tracking in Swift: Value vs Reference types”
Mobile development provides opportunities for ideas and solutions to find their ways into the pockets of millions of users. As phones become more powerful, the possibilities expand exponentially.
That’s why I’m so excited about SwiftUI. Apple’s adoption of declarative and reactive UI design makes it easier for anyone to create great looking and powerful iOS apps.
Continue reading “SwiftUI: A New Starting Point for iOS Development”
I’m not going to lie, I spent way too much time playing with the various lenses Atit Kharel has shared with the world. He made it possible to go from my kitchen in Massachusetts to the Sydney Harbour Bridge in one step — how cool is that?!
From RC cars to learning a new language, I was struck by the variety of lenses Atit has made. I asked him a few questions to learn more about his process.
Continue reading “Snapchat Lens Creator Spotlight: Atit Kharel”
The Not Hotdog app from HBO’s Silicon Valley has become one of the most iconic joke apps in tech. Like most things in the show, there is grain of truth to the fictitious app that makes it actually plausible.
With Not Hotdog, HBO went a step further—they actually built the thing. If you ever need help to figure out if something is a hotdog, head over the app store.
Continue reading “[Hacker Noon] Building Not Hotdog with Turi Create and Core ML — in an afternoon”
![[Hacker Noon] Building Not Hotdog with Turi Create and Core ML — in an afternoon](https://fritz.ai/wp-content/uploads/2023/12/1USfNLnUUtAAPl3nFwCGFBQ.webp)