Details
Die zweite Stunde vom Treffen der Open Hard- und Software-Entwickler*innen im Berliner Bum in Kreuzberg.
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Details
Die zweite Stunde vom Treffen der Open Hard- und Software-Entwickler*innen im Berliner Bum in Kreuzberg.
Comment
Die zweite Stunde vom Treffen der Open Hard- und Software-Entwickler*innen im Berliner Bum in Kreuzberg.
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seine Ideen zu entwickeln. Kannst du das empfehlen? Kann man damit einfach selber loslegen, 3D-Druck? Oder sollte man lieber vielleicht in so einen Makerspace wie hierher kommen? Also Makerspace, was gut mit Makerspace ist, gibt es eine Community, man kann die Leute fragen. Das ist nicht so kompliziert, auch zu Hause. Ich habe auch einen Drucker zu Hause. Aber hier, wenn es Probleme gibt, kann man die anderen Leute fragen und das ist sehr nutzvoll. Und es gibt auch hier zum Beispiel diesen riesigen Drucker, der ist sehr teuer. Natürlich, man kann das kaufen, aber das ist gut, wenn man die Möglichkeit und etwas anderes macht. Das ist viel einfacher hier zu haben als zu Hause. Und warum fängt man an mit dem Hobby? Oder was ist so schön an dem Hobby 3D-Drucken? Wie hast vielleicht sogar du den Zugang dazu bekommen? Also für mich, das ist mein Beruf. Das ist auch ein Hobby. Mein Beruf ist mein Hobby. Aber ja, mit 3D-Druck kann man Teile reparieren, wieder bauen. Ich sage immer noch, Make don't buy. Heute ist es relativ einfach, neue Teile selbst zu entwickeln und dann zu den 3D-Druckern zu schicken. Das ist relativ günstig heute und einfach und schnell. Das ist 3D-Druck. Und wir schauen gleich nochmal weiter, was ihr heute noch hier gemacht habt. Ich sage nur Laser-Cutting. 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I will talk a tiny bit about Nextcloud because it's important for the context of everything. So, my name is Frank Kalniczek. I do open source for 25 years. Yes, I'm old. Lots of different roles. I was a part in the TDE community actually for a long time. I'm helping a little bit with W3C, with standardization for example, XPCPUP API. I'm working with the United Nations on their open source program, but I'm here, of course, as the founding CEO of Nextcloud. So, for the context, it's actually important to tell you a little bit about Nextcloud, because then you know about the motivation of what we are doing here. Who in this room knows Nextcloud? Okay, then. It can be very quick. So, the motivation when I started it many, many years ago was that I thought that we really need to have an alternative to these big tech companies. Because all these companies, Google, Microsoft, Dropbox, Slack, Zoom, and so on, they all provide a great service, but it's all proprietary software and it's running like as a software, as a service from some hosting center somewhere else. You don't really have it under control. So, the motivation was that we really need to have an open source alternative that we can also host and run the way we want to give you the freedom and privacy you expect. So, this is also why Nextcloud is structured in this way, that we have these four core products. There's like Nextcloud File, which is a replacement to Google Drive or OneDrive for Microsoft or Dropbox. There's Talk on chat and video conferencing, very similar to Teams or Slack or Zoom. Groupware or Mail, Calendar, and Contact, and Office Document Editing. The main difference, as I said, is, of course, that Nextcloud can be hosted wherever you want. Lots of people write on their Raspberry Pi at home, for example, that's possible, or some other hub that they choose. So, it's fully decentralized and fully open. A little bit through the features, but most of you know it already. This is the interface of Nextcloud File. You can upload, download files, share it with other people, search it, tag it, delete, undelete, and so on. So, it has all the usual features you know and expect. This is Nextcloud Talk for chat and video conferencing. Again, nice group chat interface. You can put your files in, work on it together, do polls, watch videos together, all the things you expect. For example, also Maps, so you can post a map into the chat and everybody else can see it. So, it's very convenient. Of course, you can press the Start Call button, and then it turns into a video call, and you can do a video call with your friends and family. Again, we are one of the very, very few solutions where all this works completely locally with your device. Nothing is leaking anywhere else. There are mobile apps. Of course, for the file access, but also for the chat and video conferencing, push notifications, everything you expect. There's a calendar. Of course, you can use it yourself or share the calendar with other people. You can access it and sync it through your phones and other devices. There's a connector to Exchange. If you still have a company with an old Exchange server, you can still use it as a backend. It's very, very popular. And there's a mail interface where you can work with your mail, very similar to Gmail, for example, with all the usual features like browsing, inbox, encryption of mails, and so on. The last but not least, of course, Next.office for editing office documents in the browser alone or collaboratively together with others. There's also nice integration. For example, you can have a video call and a chat session while you work together in a document. So this is what we developed the last few years. I would say that we are the alternative to these American big companies. Everything is open source. You can host it yourself and give it freedom. And we have a nice community and lots of happy users. And life was good. And this was end of last year. And then we had, of course, the AI revolution. And to be totally honest, I got a little bit of a depression last year, end of last year, because I thought, okay, this is nothing we can really compete with. Now we have all these great collaboration tools, but it's big tech companies that really have so much resources, so many hosting centers with lots of GPUs, there's really nothing we can do to compete. And even if we can compete, of course, there are lots of ethical questions connected to AI. And AI can be a very powerful and helpful tool to make your life easier, to like automate boring things, but as you all know, there's also a bit of the dark side of it, because there are lots of problems also attached to it. Again, we had these two problems. Can we do it in the first place at all? And also, do we actually want to do it? Because what about the problems? A lot of big companies, they are blocking chat GPT, for example. Samsung, or Apple, or Goldman Sachs, many others, because they're really afraid of the problems that come with these AI tools. For example, there might be wrong information coming from there, or it actually might be deep data. So, for example, people from Airbus are afraid that if they use chat GPT to discuss some documents, then this is used as training data, and then someone from Boeing is using the system, somehow getting answers based on the documents from other people. So that's really a problem. So there's a lot of problems attached to AI. Which led us, at the beginning of this year, to start an initiative around ethical AI. Because we really want to provide powerful tools to our users, but hopefully without problems. That's, of course, the question, okay, what is ethical AI in the first place? It's a big word, right? Technology is complicated. What is it? If you're looking in the press, that's very easy to identify some problems that people have. For example, the whole question about discrimination. So this is a big problem in AI. For example, if you go into Dali or Stable Diffusion or something, and you type in, hey, generate a photo of a doctor, it's most likely a white man. So there's a lot of bias in there. And that's, of course, a problem. Second, there's the whole question around CO2 footprint. I mean, all these huge solar farms, they really produce a lot of CO2 because of the huge energy consumption. And really, what does this mean for our future if we do everything with AI in the future? So what does this mean for the planet? Then the privacy question, already raised, what a challenge that your data might be leaking to other people, like, intentionally or not intentionally. But that's obviously a big question. And the last point, of course, is, is it actually freely available? I mean, can really everybody on the planet use this system, or do you really have to be a customer? Do we have to pay money to Microsoft or Google for these services? And is it really freely available the way open source should be? So we condensed these problems into those three requirements, and then we developed this traffic system here. So the first requirement for a ethical AI, in our opinion, is that the code should be open source, because only then you can optimize it and run it locally. Second requirement is that the model should be freely available, because then you can run local and not in the cloud somewhere. Third requirement is that training data should be freely available, because only then you can check if there's bias in there, you can detect it, and you can fix it and improve it. So in our opinion, these are the requirements for an ethical AI. In Nextcloud, we give the people the flexibility to use what they want. For example, in the settings screen, you can choose a translation system, for example, you can say, hey, I want to use ChatGT, or I want to use a locally run model. If you want to do speech-to-text, it's the same. So Nextcloud is all about giving people the choice, so they can use the systems they want. But obviously, we focus on truly locally running open-source AI. So this is what we focus on, and this is what we do. So I'm really happy that in the last few months, we developed the Nextcloud Assistant, and this is an assistant that is built inside Nextcloud, it's using a large language model, it's fully open-source, and it runs completely local. This is quite nice and powerful, it has lots of features, for example, speech-to-text, image recognition, face detection, detection of blocking behavior, and many other things. I want to go through some details now, to show you a little bit more what it does. First of all, you can obviously press the button on top, you get an assistant, and you can chat and ask questions and generate all kinds of content. But the real powerful thing is when it's embedded into other things. For example, here you have an email client, and let's say you want to write an email, then you can just say, hey, let's generate an email for a birthday party or something, and it generates an email for you, directly to the mail client. If you want to work with text, you can just mark any text in Nextcloud, and here on the side you can say, generate a headline, summarize it, translate it, or do many other things. So if you want to generate a contract or bigger text in Nextcloud Office, you can also do that, and directly generate it in your Office document, and you can use it directly. You can do image generation, for example here in the chat, let's say you have a brainstorming with your colleagues, and then you can say, hey, I want to visualize something, and you can give a prompt, and then of course, it's just a click, generate a photo, and it's directly inside the chat. If you want to dictate something, you want to maybe use dictating mails, there's a built-in dictation system, speech-to-text system, you can just dictate it, and try to dictate your document. You also use this for video calls, so let's say you have a video call with your colleague, then you can generate a transcript of your video call automatically, and share it with everybody, and it can also be summarized if you don't have the time to read everything, so that's fully integrated. And of course, the Nextcloud Assistant can also be used for chatting, so let's say you're in a chat interface, you can just say, hey, I want to organize an event like that, a trade show, and you ask the Assistant, and the Assistant responds back with all the important information in the chat group. If you're getting lots of emails, that's a nice feature, where you get a summary of your mail threads on top of the mail, let's say there's a really long summary, a very long mail thread, where a lot of people are discussing things, you don't have time to read everything, you can just look at the summary, and generate it on top. We have a system that analyzes the logging behavior, and it basically can send you notification if someone logs in in the middle of the night from a different continent, something else appears, and you just get a nice notification, and again, that's a machine learning model running completely local. And the last example I have here, it can also look into documents, document classification. For example, it can detect if a document contains, like, bank information or social security numbers or other things, and then a document can be flagged and have special rules, for example, that cannot be shared outside the organization. So the summary is, ethical AI is possible, you need to understand what you're doing, if you send all your data to chatGTT, you might have a problem, but if you have a model that runs completely local, with transparent training data and everything else, then this is actually possible. So, no data leakage is needed, as you can, Big Tech is not the only organization who can do that, we can do it too, the open source community, there are a lot of things that are possible. The CO2 footprint can be under control, because you can actually run it locally, you can measure it, you can improve it, no one knows what's happening in the data center from Microsoft to Google, but here you have it under control. The bias can be minimized, with freely available training data, very important. But I also think that a definition of open source should evolve, because a lot of people are throwing away the term open source AI without actually knowing what it means. So this is something that we all together have to work on. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Danke. Danke. Danke. Danke. Danke. Danke. Danke. Danke. Danke. Danke. Danke. Danke. Danke. Danke. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you.
