cohenjacobd

fixed! a hacker news mod changed the title, not sure why at first

Thank you so much! We deeply explored how to make it easy for anyone to get started with machine learning. We looked at where people were spending the most time getting started and iterating on creating a custom machine learning model. This is why we expanded Lobe to focus on 3 fundamental steps:

1. Collecting & labeling images 2. Training your model and evaluating the results 3. Playing with your model and seeing how well its performing

no concerns here :)

hah! keep in mind the model will always make a prediction with one of the labels it is trained with for any image it is shown. You can add a "none" label and add images of things that are not banana, orange, apple, to learn the important features of a picture that make it a banana. if you are using your webcam, you can collect images of you, your office, backgrounds, etc

We do ping online to check if an app update is available! It checks the current app version and our hosted app version to see if we should show a notification that an update is available and a link to our website download.

We do not send any app analytics when it is turned off.

hey there! We have Android and iOS starter apps to make it easy to export a trained model and run it on your phone!

https://github.com/lobe

odd... I emailed Hacker News to ask.

Hey there! Thank you so much for the feedback, we are planning improvements like this.

Here's a few tips for now: 1. You can view by "Test Images" on the Train tab (view options). So you can see how well your model is performing on your test images (a random 20% split from all of your images). 2. You can test your model on the Play tab, by dragging in new images your model has not seen, to see how well it is performing. You can also tell Lobe if it was correct or not and iteratively improve your model.

Thanks for the feedback! We will be adding "Object Detection" next, which is identifying objects within an image and adding a bounding box around it. We are also exploring multi-label classification to classify an image as "dog" and "cat".

For Image Classification, that is a good approach is predicting if an image has both a cat and dog is important.

Not yet! We are starting in beta with image classification. We are working on adding more project templates in the future, and Lobe is designed upon the idea that machine learning should be made easy — no matter the problem type you are facing.

No gotcha! We're trying to fill a sweet spot for customers looking for a simple and quick way to get started with machine learning using their PCs or Macs without requiring any need for the cloud.

We're very much alive and doing well :)

We'd love to hear about any projects people are working on! We hope to see projects and ideas shared to our subreddit https://reddit.com/r/lobe

omg please make this project haha I love this - we'll make it a project highlight on our twitter @lobe_ai! And be a hit on our subreddit https://reddit.com/r/lobe

Hey there! I'd recommend using your webcam to quickly add images of things on your desk or in your house :) to get a feel for the magic of machine learning. Press and hold on the shutter button to take a burst of images and move the object around to get variety. Then use the Play tab to try it out and see live results from the model!

You will always be able to train custom machine learning models on your own computer for free with Lobe

Thanks! We hope the GitHub bootstraps help make it even easier to train a custom machine learning model and ship it in an app.

We're really excited to bring machine learning to more people and make it more accessible. What we are most excited about is empowering people to create custom machine learning models for specific and personal use-cases and solve problems in new and unique ways

Thanks for catching this! We're on it.