Gretel AI Beta² Reviews

Amazon Rekognition Reviews

Gretel AI Beta² mentions (5)

• Assessing the Quality of Synthetic Data with Data-centric AI

  If you are working with synthetic data and would like to learn more, check out the blogpost that demonstrates how to automatically detect issues in synthetic customer reviews data generated from the http://Gretel.ai LLM synthetic data generator. Source: 12 months ago

• Synthetic Data

  I was chatting with the founder of GretelAI recently and learned a lot about the area of synthetic data. Source: over 1 year ago

• Generating Synthetic Data from Prod systems into Dev/UAT

  The requirement is to build out synthetic data with very similar size and shape to our production data and ideally have a framework to do this, maybe at some level use our data and "de-productionize" it. gretel.ai looks like it may be a fit, but from what I see I need to upload production data to their environment and that's a no-go. Source: over 1 year ago

• Ask HN: Will AI-generated images flooding the web pollute future training data?

  > https://gretel.ai/ Where were you the last decade of my professional life? I couldn’t find anyone to take my money for exactly this. - Source: Hacker News / almost 2 years ago

• Ask HN: Will AI-generated images flooding the web pollute future training data?

  [2] https://gretel.ai/blog/how-to-safely-work-with-another-companys-data. - Source: Hacker News / almost 2 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 / 3 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 / 11 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: 12 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: over 1 year ago