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Lobe – Deep Learning Made Simple

lobe.ai

61–70 of 74 posts

Re: Lobe – Deep Learning Made Simple

#64
Awesomely done ! What i really like is that, in addition to the ease of deploying a model, this product also lets you visualize the activations of the neural network. I mean you could build the visualizations in Jupyter but the ease of toggling the layers, such as switching of Max-Pool etc is super helpful for understanding how neural nets work.

Re: Lobe – Deep Learning Made Simple

#65
post #64

Awesomely done ! What i really like is that, in addition to the ease of deploying a model, this product also lets you visualize the activations of the neural network. I mean you could build the visualizations in Jupyter but the ease of toggling the layers, such as switching of Max-Pool etc is super helpful for understanding how neural nets work.

Yeah we definitely agree! Thanks for the kind words.

Re: Lobe – Deep Learning Made Simple

#66
post #54

I think there are something like this, don't know what the difference, can someone give a compare: deep learning studio: http://deepcognition.ai/ knime: https://www.knime.com/ (have deep learning plugin) runwayml: https://runwayml.com/ (in beta, did not open for public)

knime and deep learning studio look like tools for ML experts and I am not sure what runwayml does. Lobe appears to be something that a software engineer could use but they don't necessarily need to be a ML expert. We will see if Lobe delivers on that promise, but I think that is the difference.

Knime is very similar concept giving you access to building blocks like models, evaluators, input transformers, etc. so that you can make arbitrary ML pipelines. It doesn't have the slick drag'n'drop of input data. Instead you use an input building block and point it to a data store of some sort (text files, images, database, etc.). Also, it doesn't generally output models for direct use in other applications but you can output using PMML. Knime is also very useful for analysts, data scientists, etc. who aren't software engineers. Lobe has run with the concept pioneered earlier by folks like Knime, RapidMiner, WEKA, etc. They've simplified the process of quickly getting a working model by constraining on one model type and one input type. If your use case matches, it's a great innovation. If not, per usual, no free lunch.

Re: Lobe – Deep Learning Made Simple

#68

Hey everyone! One of the cofounders of Lobe here - let us know if you have any questions.

I didn't see any information on pricing. I'm sure this may be a bit premature to ask, but any indications on the pricing model (or models considered) may help people who take a look at it. Similar question on licensing and usage options too (seems like there are two usage modes, one where your server does the computation with inputs provided in near real-time and another where the trained information is downloaded and imported into an app more like a static asset/model).

Re: Lobe – Deep Learning Made Simple

#69
I'm blown away by the effectiveness of the whole product. While being approachable for beginners, it seems to allow experts to tweak at will. It's a massive "tour de force".

The marketplace play mentioned in other comments seems like a thing to try. I confirm I would pay for querying predictions through the API.

Such a polished product for 3 folks. Kudos!

Re: Lobe – Deep Learning Made Simple

#70
post #40

This reminds me of Unreal's blueprints. You could get a surprising amount of work done just via blueprints and not touch C++ code. You'd have to balance the input and output connection's granularity - too many would put off users, too few would make users feel restricted. If you manage to find a sweet spot, or let the user pick the level of expertise, and reveal them accordingly, it would be perfect. I really like ho…

Great description of the balance of features between super-users and beginners interested in frictionless AI tooling based on their level of experience. I've used the example of the settings, preferences and pre-built sketches within the Processing, P5js and Arduino IDE's to imagine what an AI model manager might look like if it followed this tone. Do you have any other examples of products that meet the requirements of both beginners and super-users?
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