Super psyched to watch Space come to fruition. 
Can’t wait to see how Mudita puts their twist on web based services.
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Thanks again for the answer. Did those invites go out yet? I haven’t received mine. Thank you!
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@urszula @Wojciech_Cichon any news when the next features will be implemented into Space? Really looking forward to this.
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We’re working on additional apps in the background, while we’re regularly releasing updates for Mudita Storage. We’re happy to hear that you’re waiting for more 
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I love the simplicity and ease-of-use of the Mudita Storage beta – including the ability to share the URLs to photos or folders!
Questions:
- Will there be an option to increase its capacity beyond 2 GB?
- Will there be (eventually) an Android app for viewing folders and media?
I ask the second question because this could be a useful competitor to the Amazon Photos app (e.g., for Android), which lets members of a household use their smartphones to access photos stored on the household’s Amazon Drive account.
I prefer to view cloud-stored photos on a computer, but I know of households in which smartphone addicts prefer to use an app to find and display the household’s photos.
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Yes, there will be an option to increase the capacity. For now, we’re considering how to upload files and back up photos on Android using Mudita Storage. What potential other features you would find useful in a stand-alone Mudita Storage app ?
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I may not be the best person to ask, given that I am moving away from Android and to the Mudita Pure. But, I have heard Android users of the Amazon Photos app wish that they could look up photos by content – e.g., “Show me the photos that I have taken of my garden … or of my house … or of my car.” – instead of by file name.
Thank you for the update about storage capacity!
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This implies that people want to have algorithms working through their images and categorizing them. If we could do this job locally without having access to the data on their phones that would actually be a zero-knowledge approach. Everything else would include Mudita’s eventual algorithms working on people’s data in the cloud, which is exactly what we’re trying to be an alternative to.
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Not sure why anyone would want this! The user would be giving up an immense amount of privacy (and control over their information) for such a minuscule convenience. Gives me the heebie-jeebies!
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Yes, the ML algorithm would have to be trained and used locally on the cellphone to avoid invading the user’s privacy. I’m not saying that this is what I would want; I’m simply saying that I have heard Amazon Photos app users complain that they cannot look up photos by categories such as trees, dogs, etc., an activity that implies machine learning – something that requires more computing power than is available now on most smartphones.
@mindful321 I think I agree with you. Although I can see why people would like this convenience, it does open the door to misuse. I’m not sure I would be comfortable with a company scanning & organizing my pictures.
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Agreed, @urszula! I would accept this only if the code for machine-learning model/algorithm resided on my cellphone or computer and all training and use of the ML model occurred there, with no sharing of the model with a company. Having used a personal computer to train an ML model to distinguish photos of bolts from photos of screws (as my graduation project while earning a “Machine Learning Engineer” nanodegree from Udacity.com a few years ago), I know well that the training phase can be QUITE computationally intensive.
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Another way to distribute it not reliant on Apple App Store or Google Play Store? F-Droid is what most people in the free, open source software community use, for Android.
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@kirkmahoneyphd Since the training phase is so expensive, doesn’t it make sense to reuse the models as much as possible once they have been trained? Since that’s not as expensive.
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@sandra: Yes. Ideally one would perform the training phase – and updates to the training – on a computer and not on a phone … and then use the trained model – and updates to the trained model – on the phone.
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I did some work on a customized GPT-2 a while back. But creating the original GPT-2 took the equivalent energy of many flights.
So what I mean is, even more ideally: train one model and then use it on many devices.
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I love this functionality. One example from my life: I wanted to show someone picture of pack of specific brand of rice I like and I remember that I took picture of it long time ago. I have thousands of pictures on Google Photos, and hate tagging anything (too much time needed). I started search with simple rice and I got 3 pictures back: two pictures of paella from 4 years ago and one picture of pack of rice (that I wanted) from over one year ago. Without this I would not found it in any acceptable time and waste a bandwidth scrolling pictures for a long time (and any bandwidth is generating carbon, for example how much carbon is generated when opening mudita.com).
I understand that this feature could be misused but for me it’s big quality of life improvement.
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@Dobroslaw_Zybort I understand the use scenarios; especially dealing with advancements in Accessibility functionality. Personally though, I find most people veer towards the lazy/convenience side of things over privacy/independence, and that is what is eery to me. Tagging photos is such a simple process, takes a minuscule amount of time. Also, maybe if there where more friction you would take less photos. How often do you go back and review your thousands of pictures? It’s just more data for google. They say that people spend more money using credit cards than they would if purchasing with cash due to the lack of ‘friction’; I am convinced the same principal applies with a variety of things. If you were tempted to take a photo of a sunset but made it a rule that you tag ever photo once taken, and at this particular time you didn’t believe it would be worth the effort to tag it right now, then maybe you would rethink taking the photo, keep your phone in your pocket (preventing the inevitable notifications check) and enjoy the sunset with the loved one you were with, therefore creating a moment the two of you shared the most beautiful sunset together.
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