Lobe.ai Review

Lobe Screenshot Transparent.png

Lobe.ai just released for open beta and the short story is that you should go try it out. I was lucky and got to test it in the closed beta so I figured i should review a short review.

Making AI more understandable and accessible for most people is something I spend a lot of time on and Lobe is without a doubt right down my alley. The tagline is “machine learning made simple” and that is exactly what they do.

Overall great tool and I see it as an actual advance in the AI technology by making AI and deep learning models even more accessible than the AutoML wave is already doing.

So what is Lobe.ai exactly?

Lobe.ai is an Automl tool. That means that you can make AI without coding. In Lobe’s case they work with image classification only. So in short you give Lobe a set of images with labels and Lobe will automatically find the most optimal model to classify the images.


Lobe is also acquired by Microsoft. I think that’s a pretty smart move by Microsoft. The big clouds can be difficult to get started with and especially Microsoft's current AutoML solutions is first of all only tabular data but also requires a good degree of technical skills to get started.

It’s free. I don’t really understand the business model yet, but so far the software is free. That is pretty cool but I’m still curious about how the plan on getting revenue to keep up the good work.

Features

Image classification

So far Lobe only has one main feature and that’s training and image classification network. And it does that pretty well. In all the tests I have done I have gotten decent results with only very little training data.

Speed

The speed is insane. The models are being trained in something that seems like a minut. That’s a really cool feature. You can also decide to train it for longer to get better accuracy.

Export

You can export the model to CoreML, TensorFlow, TensorFlow Lite and they also provide a local API. 

Use Cases

I’m planning to use Lobe for both hobby and commercial projects. For commercial use I’m going to use it for the main three purposes:

Producing models

Since the quality is good and the export possibilities are ready for production I see no reason not to use this for production purposes when helping clients with AI projects. You might think it’s better to hand build models for commercial use, but my honest experience is that many simple problems should be solved with the simplest solution first. You might stay with a model build with Lobe for at least the first few iterations of a project and sometimes forever.

Teaching 

As I’m teaching people about applied AI, Lobe is going to be one of my go to tools from now on. It makes AI development very tangible and accessible and you can play around with it to get a feeling about AI without having to code. When project and product managers get to try developing models themself I expect a lot more understanding of edge cases and unforeseen problems.

Selling

When trying to convince a potential customer that they should invest in AI development you easily run into decision makers that have no understanding about AI. By showing Lobe and doing live tests I hope to be able to make the discussion more leveled since there’s a chance we are now talking about the same thing.

Compared with other AutoML solutions

The bad:

Less insights 

In short you don’t get any model analysis like you would with Kortical for example.

Less options

As mentioned Lobe only offers image classification. Compared to Google Automl, that does that and objectregocnition, text, tabular, video and so on, it is still limited in use cases.

The good:

It’s Easy

This is the whole core selling point for Lobe and it does it perfectly. Lobe is so easy to use that it could easily be used for teaching 3rd graders. 

It’s Fast

The model building is so fast that you can barely get a glass of water while training. 

The average:

Quality

When I compared a model I build in Google AutoML to one I build in Lobe, Google seemed to be a bit better but not by far. That being said the Google model took me 3 hours to train vs. minutes with Lobe.

Future possibilities

For me to see Lobe.ai can go in two different directions in the future. They can either go for making a bigger part of the pipeline and let you build small apps on top of the models or they can go for more types of models such as tabular models or text classification. Both directions could be pretty interesting and whatever direction they go for I’m looking forward to testing it out.

Conclusion

In conclusion Lobe.ai is a great step forward for accessible AI and already in it’s beta it’s very impressive and surely will be the first in a new niche of AI. 

It doesn’t get easier than this and with the export functionality it’s actually a good candidate for many commercial products.

Make sure you test it out, even if it’s just for fun.

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