Stripe: Radar VS Amazon Rekognition

Stripe: Radar Reviews

Amazon Rekognition Reviews

Stripe: Radar mentions (6)

• Anyone here use Square? Or accept in person card payments [Please Click]

  Using Stripes Advanced Fraud protection to keep you and your money safe,. Source: over 1 year ago

• [Review][Negative] GunBrand.com

  They should use their credit card processor's fraud detection. For example, Stripe has Stripe Radar: https://stripe.com/radar. Source: almost 2 years ago

• When a customer does an unfair chargeback, what do they tell their card company?

  Stripe Radar is the main tool used to do this, you can check it out here to get more detail: https://stripe.com/radar. Source: over 2 years ago

• Don’t pay online with PayMaya.

  Usually, these online merchants (Netflix, Spotify, etc.) uses the same payment gateway. They're likely using Stripe. Once one merchant reports your card as "fraud" or detects unusual activity, it will be labeled as "high risk". Stripe will take note of that and will block the same card whenever it is used on other merchants. It's a security feature Stipe implements that work well for both the merchant and customer. Source: over 2 years ago

• I strongly feel Databricks will merge with PSTH I. Here's undiscussed evidence why.

  Stripe also has a division called Radar that would benefit from Databricks' expertise. However, does Stripe need to acquire/partner with Databricks for this or is just being a customer enough? Source: about 3 years ago

Amazon Rekognition mentions (33)

• Afraid of outgrowing AWS Rekognition? Try YOLO in Lambda.

  AWS Rekognition is a great choice for many types of real-world projects or just for testing an idea on your images. The issue eventually comes with its cost, unfortunately, which we will see later in a specific example. Don’t get me wrong, Rekognition is a great service and I love to use it for its simplicity and reliable performance on quite a few projects. - Source: dev.to / about 2 months ago

• Amazon Rekognition Custom Labels for Bears

  I don’t really want to spend so much time manually adjusting labels. For most machine learning, the next step would be to fine tune your model. You can essentially fine tune Amazon Rekognition by using Custom Labels. You can do this to make it better at detecting specific objects (like bears) or train it to detect new objects like your product or logo. It really depends on your application needs. - Source: dev.to / 10 months ago

• “During a gold rush, sell shovels.” What are the shovels in the AI rush?

  For instance, are you a company with lots of security cameras? Hire me to write a program that pipes your data into AWS rekognition and then shows you a dashboard of what happened on your cams today. Got a ton of products with no meta-description? Hire me to write a program that pipes your data into OpenAI, and then saves the generated description to your custom CMS. Source: 10 months ago

• Serverless Facial Recognition Voting Application Using AWS Services

  Amazon Rekognition: Used to index, detect faces in the picture, and compare faces when users try voting, it was the heart of the facial voting feature. - Source: dev.to / about 1 year ago

• Amazon Prime Video playback features

  Sure. But if you think generating thumbnails and detecting intros/credits takes a long time, wait until your computer is running machine learning/computer vision over your entire library. They also have to build and train that model which is no trivial task. And I know what you're thinking, why don't they just use Amazon's Rekognition service that does celebrity identification? Well, it's $0.10 per minute of... Source: about 1 year ago