Lobe

🟠Possibly Dead

Lobe is a free desktop application for training image-classification models without writing code. Users label image examples, train locally, test predictions, and export models for use in applications.

No-code machine-learning builderVisit website β†’

Why Abandoned

Microsoft acquired Lobe in 2018 and released a free public preview in 2020. The official site still describes the app, but its linked desktop installers return errors and the GitHub repository shows no recent release activity, so its current support status is unclear.

🩺 Health Signals

No checks have been run on this tool yet.

πŸ“… Timeline

2018-05-07

Lobe unveiled

2018-09-13

Microsoft acquired Lobe

2020-10-26

Public preview launched

2021-05-18

Model export expanded

πŸ”„ Alternatives to Lobe

❓ Frequently Asked Questions

What is Lobe AI?

Lobe is a no-code desktop tool for creating image-classification machine-learning models from labeled examples. Training occurs on the user's computer, and completed models can be exported for use in applications.

Is Lobe AI free?

Microsoft launched Lobe's public preview as a free application. However, the current availability of working official downloads is uncertain, so prospective users should verify the download links on Lobe's website.

Does Lobe require coding?

No coding is required to import and label images, train a classifier, or test predictions in Lobe. Programming may still be needed to integrate an exported model into a separate product.

What machine-learning tasks does Lobe support?

The publicly released Lobe application focused on image classification: assigning an image to one of several user-defined labels. Earlier descriptions discussed broader ambitions, but the released desktop product centered on classification.

Is Lobe AI still available and supported?

Its lifecycle is unclear. The official website remains online, but its desktop download links appear unavailable and public development activity is limited; Lobe is therefore best treated as possibly inactive rather than definitively shut down.