Our driving force is to make this technology as accessible as possible to as many people as possible. We believe that machine learning will be a huge new way that people interact with computers going forward to better their lives.
Lobe will always let you train custom machine learning for free on your computer. We hope this becomes a vibrant ecosystem, and the business model around the edges can come later for value-add services.
We believe there are several advantages of Lobe over tools like Google AutoML :) Lobe is making the entire process of creating custom machine learning accessible, from creating your dataset to training and playing with your model, to integrating it into apps:
* Easy to use - no coding, cloud configuration or machine learning experience required.
* Free & private - train for free on your own computer without uploading your data to the cloud. No accounts required.
* Ship anywhere - available for both Mac and Windows. Export your model and ship it on any platform you choose.
AutoML requires paid accounts with high friction setup and is focused on just training a model on your data. You would have to pay and retrain your model manually every time you want to make an iteration. Lobe gives fluidity with iterating and providing feedback to your model through Play.
No catch! We are first and foremost trying to make this technology accessible to as many people as possible, and we want to grow an ecosystem around it. Business models around that can come later.
Yep we are starting with image classification for this initial beta launch, but plan to expand to more data types and problem types in future releases! The vision is to make a tool usable by anyone to build custom machine learning
Hey Markus from Lobe here :) all images and labels stay private to your computer, we don't ever see any of it. We only collect some generic app usage data for telemetry if you opt-in to sharing analytics after installing Lobe.
Hi, Markus here from the Lobe team. The Lobe app is free and you will always be able to train for free on your computer! Our goal is to make machine learning accessible to anyone.
Yeah! Adam and I met at NIPS 2015 when I demoed a gui prototype for OpenDeep, talking about ways to let non-coders build neural nets. Around the same time, we saw that QC Brain video Mike posted and we all started talking and unifying around this vision of helping people who aren't experts get started with designing and adding intelligence to apps. From there we formed the vision for Lobe and the rest is history!
Our vision is to be the tool that starts with great settings for beginners but lets you graduate into the internals as you become more expert - at the lowest level you can interactively create computation graphs and see their results as you change settings, sort of like eager mode for ml frameworks on steroids (or other visual computation graph programs that designers use like Origami/Quartz Composer).
The lobes in the UI are all essentially functions that you double click into to see the graph they use, all the way down to the theory/math.
Yep growing as a platform is the vision! We are committed to accessibility for people using models/components vs. paying but good point about considering the opportunity cost of someone going to algorithmia with a model once it is trained.
We are focusing on free to access any model explicitly shared by the user and pay for training/deploy resources as a service, but might consider mixing in a paid route for users to monetize their unique trained models.
On Memory Construction and Retrieval for Personalized Conversational Agents https://arxiv.org/abs/2502.05589