Image Classification Benchmark: Google, AWS, Hugging Face & Nyckel

We benchmark Nyckel against leading AutoML providers using several public datasets. We evaluate performance, training time, latency, throughput, and developer experience.

Andrew Tate

Posted May 2023

Posts

Introducing Invoke Capture - Automatically Gather Important Data to Improve Your Model

A machine learning model is only as good as the data it is trained on. At Nyckel, our goal is to give you have the tools to keep your data fresh, correct, and up to date. To this end, we are excited to introduce invoke capture - automatically and intelligently capture important data to improve your model.

Oscar Beijbom

Posted Sep 2023

AI Image Detector: Can You Use Image Classification to Spot the Fakes?

Thanks to recent advancements in AI, we’ve seen remarkable quality improvements in AI-generated images. However, these improvements have also led to growing concerns about identifying authentic and trustworthy images. This article explores if we can create an AI image detector with Nyckel image classification.

Becca Miller

Posted Sep 2023

End-to-End AutoML: Your AutoML Platform Should Span the Entire ML Development Lifecycle

AutoML platforms automate the work required to train an ML model. However, training a model is a small part of the ML development lifecycle. An end-to-end AutoML platform that handles all aspects of ML development can provide significant benefits.

George Mathew

Posted Jun 2023

What's Best for Content Moderation? Blacklists vs. Pre-Trained ML vs. Custom ML (A Benchmark)

In this post, we compare the accuracy of various content moderation approaches — blacklists, pre-trained ML models, and custom-trained ML models — on a public Kaggle dataset.

George Mathew

Posted Apr 2023

Why Narrow AI is Better Than GPT-4 For Machine Learning-Driven Decisions

GPT-4 is impressive. Yet, there are better tools available (including Nyckel) that are tailored to the unique needs of software developers and product teams who need an API for machine learning-driven decision making.

Oscar Beijbom

Posted Apr 2023

Are Bounding Boxes Necessary for Object Detection?

Bounding boxes are usually used to annotate data for object detection. However, they are hard to annotate and are not required for all object detection use cases. In this post, we examine where bounding boxes are unnecessary and compare them to center points, which are significantly easier to annotate.

George Mathew

Posted Mar 2023

Machine Learning is Still Too Hard for Software Engineers

Machine Learning has made huge strides in the last few decades, but it remains largely inaccessible to the average developer. This post examines some of the reasons why.

George Mathew

Posted Jan 2022

Hierarchical Image Classification vs. Flat Classification: What Does Your ML Task Need?

In this article, we explain the differences between hierarchical and flat image classification and make the case for why a flat structure is often the better choice for many use cases.

Oscar Beijbom

Posted Aug 2023

9 Must-Have Features for Your AutoML Platform: A Comprehensive Guide

AutoML involves more than just training a model; it should span the entire ML development pipeline. In this post, we explore what features and functionality you should look for in an AutoML platform.

George Mathew

Posted Aug 2023

5 Image Classification Examples (+ Datasets To Build Functions With Nyckel)

The sky is (almost) the limit when it comes to applications of image classification. We share 5 unique image classification examples to get you thinking about how you could classify images with machine learning in your own business.

Nyckel

Posted Aug 2023

Discriminative vs. Generative AI: Which Should You Build Into Your Product?

If you’re considering building AI into your product, it’s important to know the difference between generative and discriminative AI. We dive into the differences and the pros and cons of each.

Oscar Beijbom

Posted Jul 2023

What is AutoML? A Comprehensive Guide & What It Means for Product Teams

In this post we look at AutoML, explain what it is and how it works, and discuss how it can help product teams build AI-enabled products and features.

George Mathew

Posted Jun 2023

Guide to Computer Vision for Non-ML Experts

In this guide, we help you understand what you actually need to know about computer vision, so you can evaluate the available CV SaaS solutions and choose the one that’s best for your use case.

Nyckel

Posted Jun 2023

Pet Media Group saves $120k annually with AI content moderation

Nyckel’s API docs were super straightforward to use. Our first custom content moderation model was live within a day. — Eyass Shakrah, Co-Founder, Pet Media Group

Nyckel

Posted Jun 2023

Computer Vision SaaS Landscape: Comparison of the Top 9 Players

In this article, we compare the functionality, amount of time it takes to set up a model, performance, positioning, and pricing of the nine leading computer vision SaaS players. Results show significant variations across accuracy, user experience, and pricing structures.

John Weston

Posted May 2023

Google Cloud Vision API Class List: Can We Reverse-Engineer to Find the List?

Google's pre-trained computer vision model, Cloud Vision API, tags images with labels based on image contents. However, Google hasn't published the complete list of class labels. In this post, we try to reverse-engineer this list.

George Mathew

Posted Apr 2023

How to Classify Time Series Signals With Computer Vision: Kaggle Whale Example

Classifying time-series signals is a surprising and cool use-case of image classification. In this post, we show you one way to do that, by solving the kaggle whale sound classification challenge using image classification.

George Mathew

Posted Mar 2023

Glossary of Computer Vision Function Types

Computer vision can be a reliable way to search, identify, and categorize many images in a matter of moments. We define various types of computer vision to get you a better sense of how much you can do with it.

Nyckel

Posted Mar 2023

9 Ways to Use a Data Engine to Improve Your ML Model

You can improve ML systems in two ways: better models or better data. This article looks at how to improve your data by finding and annotating hard-to-classify cases.

Oscar Beijbom

Posted Mar 2023

A Quick Guide to Semantic Image Search (with Examples)

Search engines continue to get better at understanding what exactly we’re looking for when we search. Today, this also includes when we search image databases. Learn about semantic image search and how companies can use it to support a better user experience.

Nyckel

Posted Feb 2023

Pulse for Good Uses ML to Turn Cumbersome System into Showstopping Product Feature

Nyckel was so remarkably easy. My two other co-founders, who aren’t technical, were able to jump in and quickly annotate the customer feedback by its type and sentiment to train the model. – Blake Kohler, CEO, Pulse for Good

Oscar Beijbom

Posted Feb 2023

Gardyn Reduces Workload by 70%, Grows 2x After Implementing Computer Vision

Because of the way Nyckel does things, the model trains immediately. This was rather shocking and awesome! The time between me seeing Nyckel on a Google search and having a model was a few minutes. - Sunil Rawal, AI Lead, Gardyn

George Mathew

Posted Feb 2023

What Features Does Your Manual Content Moderation Tool Need?

Automated content moderation helps you review large volumes of UGC quickly and efficiently. But even the most sophisticated tools aren’t perfect and still require some level of manual review. We outline the features to consider adding to your manual content moderation tool.

Dan Ott

Posted Jan 2023

The Ever-Growing Landscape of Content Moderation AI Platforms

There’s a wider variety than ever of content moderation AI services available. Knowing your exact needs will help you find the platform that’s right for your specific business needs.

George Mathew

Posted Jan 2023

How Reddit Could Use Machine Learning to Better Moderate Subreddits

Subreddit moderators don’t have an easy job. We experimented to see how Reddit could use to Nyckel to moderate r/EarthPorn images quickly and effectively.

Dan Ott

Posted Dec 2022

Service Oriented Design Applies to ML Too

The way we’re building ML solutions today runs contrary to system design best practices. Thinking holistically about ML as a service yields designs that are cleaner technically and better organizationally.

Dan Ott

Posted Dec 2022

Multi-Class Classification vs. Multi-Label Classification: Key Differences & How to Choose

One of the first steps before creating a new classification function is to decide whether to use multi-class classification or multi-label classification. In this article, we’ll cover the differences between the two types of classification and help you choose which approach makes the most sense for your problem.

Oscar Beijbom

Posted Nov 2022

Smarter, Faster, Automated Image Organization

Nyckel's real-time API for custom machine learning is a game-changing to for digital asset management. Here is why.

Oscar Beijbom

Posted Nov 2022

Best practices for AI content moderation

How do you train, configure, integrate, and monitor an AI-based content moderation system such that it gives your users the best experience while protecting your bottom line?

Oscar Beijbom

Posted Nov 2022

How to Approach Multilingual Content Moderation

A lot of the internet's content is in non-mainstream languages. We look at some things to consider when building content moderation models for multi-lingual content.

George Mathew

Posted Nov 2022

Why Content Moderation is Important for Your Business

Some examples of how content moderation can benefit your business in unexpected ways.

George Mathew

Posted Nov 2022

What is class-balance drift, and why does it matter for content moderation?

Class-balance drift can degrade your auto content-moderation system. We look at what it is, how to track it, and what to do when it occurs.

Oscar Beijbom

Posted Oct 2022

How What’s That Charge 4x’d It's Revenue Using Nyckel Auto-Moderation

AI-powered auto-moderation allowed quicker release of more content to our public repository of credit card charges, driving a 4x increase in Ad revenue. – Jeremy Schneider, Co-founder, WTC

Oscar Beijbom

Posted Oct 2022

Same Same But Different: Content Moderation at Facebook, Twitter, TikTok, and Reddit

The four platforms have different ways of balancing free speech against misinformation. We take a close look at their methods.

Oscar Beijbom

Posted Oct 2022

Whac-a-Spammer - How to Deal with Bots on Your Site

Bots posting content to your site can be a scourge. Stay one step ahead of them with these tips, tools, and tricks.

Dan Ott

Posted Oct 2022

The Long Tail of Content Moderation Use-Cases

Beyond Spam, NSFW and violence are a long tail of situations that require content moderation across gaming, dating, e-commerce and children's platforms.

Oscar Beijbom

Posted Sep 2022

What is Content Moderation?

Content Moderation is critical when hosting user generated content. We break down the basic concepts and solutions.

Oscar Beijbom

Posted Sep 2022

4 Steps to Improved Content Moderation

Progress through blacklists and pre-trained AI's to full custom-AI content moderation.

Oscar Beijbom

Posted Sep 2022

Building a Recommender system using the Nyckel API.

We break down the components of a Recommender system and show how ot set this up using the Nyckel API.

Oscar Beijbom

Posted Sep 2022

Content Moderation using SurgeAI's Toxicity Dataset

Train a text classification model for content moderation using SurgeAI's toxicity dataset.

George Mathew

Posted Sep 2022

How SPYSCAPE Added Magic Into Their AR Game Using Nyckel

Literally over the space of ten minutes, I created a Nyckel account, threw some random images at it… and it blew my mind! It was spooky-accurate! – Gwyn Morfey, SPYSCAPE Tech Lead

Oscar Beijbom

Posted Aug 2022

Taimi Reduces Content Moderation Time by 3x, Experiences 10x Cost Reduction With Nyckel

Our average moderation time went down by three times, auto moderation coverage increased four times, and accuracy imporoved to 96%! – Vladislav Yavorskyi, Moderation Manager, Taimi

Oscar Beijbom

Posted Aug 2022

How Startup Accelerator Gust Trained a Custom Spam Filter using Nyckel

It was wonderful and saved us a ton of time. We finally got rid of spam profiles that were draining our site ranking, bothering customers, and giving us a general headache! – Peter Swan, CEO, Gust

Oscar Beijbom

Posted Aug 2022

IAB Classification of Text and Images Using Machine Learning

IAB is a content taxonomy that is used by content publishers to organize their content in a consistent way. In this post we show you how to classify text and image content into IAB categories without any labeled data.

George Mathew

Posted Jul 2022

A Quick Look at Text Search Functions

See some of the creative ways to add smarts to your application with Text Search

Dan Ott

Posted May 2022

Custom AI-Assisted Content Moderation

Online communities need content moderation to thrive, but the diversity of the internet is not fully served by general purpose content moderation APIs. We lay out the need for custom AI-assisted content moderation, look at what such a moderation pipeline would look like, and show how Nyckel makes it significantly easier to build such a pipeline.

George Mathew

Posted Apr 2022

ML is Just a Developer Tool

... at least for now

Dan Ott

Posted Apr 2022

Introducing Nyckel Image Search Functions

Nyckel Image Search functions enable cross-modal semantic search of images and text using the latest Deep Learning technology. Get started with a few simple API commands.

Oscar Beijbom

Posted Apr 2022

Machine Learning on Tabular Data with Nyckel

Nyckel releases a new feature to create Machine Learning models for tabular data in minutes.

George Mathew

Posted Jan 2022

Nyckel Accepted to Y Combinator (W22)

Nyckel has been accepted to Y Combinator batch of Winter 2022!

Oscar Beijbom

Posted Jan 2022

A top 3% score in the Kaggle Titanic Challenge using Transformers

In this post we show how to make a top 3% submission on the Kaggle Titanic Challenge using Transformers

Oscar Beijbom

Posted Oct 2021

Local Development and Validation of Nuget Packages

Learnings from setting up a local development workflow for developing and validating nuget packages

George Mathew

Posted Oct 2021

AutoML benchmark: Nyckel vs Google vs Huggingface

A comparison of accuracy, training times, and invoke latencies for three major AutoML engines

Oscar Beijbom

Posted Jun 2021

AutoML Comment Moderation in a Rails App

Using machine learning to help curate user content

Dan Ott

Posted May 2021

Add Image Classification Using Machine Learning to a Web App With a Single Line of Code

Inspired by a scene from HBO's Silicon Valley, I decided to build a website that identifies whether a photo is of a hot dog.

Jeremy Schneider

Posted Apr 2021

How to Add Custom Image Classification To Your Application Using Machine Learning (The Easy Way!)

It’s often valuable to be able to programmatically classify an image into a category. This post explains how you can use Nyckel to do that in minutes.

Jeremy Schneider

Posted Apr 2021