Hello from Sina from Brussels, a vibrant new member of your community!

Introduce Yourself
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Hello everyone :wave: ,
I’m Sina.
:earth_asia: I’m from Brussels, Tehran, and Shiraz
:now: Working on my startup, Lutino.io
:map: How I found Logseq: Through a brilliant friend of mine and noticed in potential in producing structured content, even to the level of OWL2 ontologies, while staying connected with the power of Shell. I’m looking into how to better integrate Logseq with the command line so I can have full immersion between the power of Unix scripting and the command line and the power of Web and integrations that are enabled via APIs, as they grew to be more and more commonplace. But command line stays the only interface for many decent pieces of software and exclusively so, due to the non-relevance of a graphical user interfaces, again mainly due to the cost of development, which in fact Logseq can also help bring down but that’s for another day.

Nice to meet you all. I have a number of good proposals in shaping the framework for the potential that Logseq has. One of the things that I find fascinating with Logseq is the ability to commodotise the production of data and not just any data, data in a connected graph. At the same time, it’s its commitment to privacy-first and the fact that their version is actually provable. Although, I can be critical of the iCloud-only on Apple devices, which sort of forces certain users into uploading their content, unencrypted (i may be wrong about this) on Apple’s controlled cloud.

But its use of Electron is a brilliant choice of architecture. With this kind of architecture[^1], a plugin developer can theoretically give the assurance to its users that their stuff is solely stored on their local storage. Because at the end of the day, this is what this game comes down to. It’s the assurance and trust you can gain from your user so they are not worried about privacy when they interact with software you have written for them, at the end of the day, to make their lives better, as opposed to the somewhat common practice of stealing people’s data to enrich other AI models, which they would then sell for profit. I’m saying, Logseq’s arch should be able to address that concern, fully because it can guarantee off-the-grid processing, Edge computing, as it were.

[^1]: and it being open as open as Logseq is being, which is great, by the way.

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Nice to meet you @sindoc! Welcome!

noticed in potential in producing structured content, even to the level of OWL2 ontologies, while staying connected with the power of Shell.

I’m also a newcomer here, but that sounds good to me. I think both are key points. Let’s see together how this evolves.

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Thanks for raising your hand. Describe your interest more. I’m looking to be able to use Logseq as a semantic modeling tool so I can maintain a bunch of master data and reference data and their relationships in Logseq and generate OWL2, which in turn will be used in the production of nuanced data products.

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Well, my idea has to do with redefining various aspects, but to give you an idea, imagine that with the graph that you are creating (obviously structured) you are feeding an AI that serves as an interface where the division between documenting and consulting disappears, where everything is just experience.

Now imagine the possibilities at a collective, political level. Where making an intelligent collective decision through a collective political process supposes or is synonymous with the creation of free knowledge that is modular and modulable, which becomes part of the heritage of the universal pro-commons.

It’s just a metaphor, surely it can be explained from a point of view with less Silicon Valley techno-optimist smell, but as an introduction it may serve.

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I do get what you’re saying. The immersion between input and output works breathtakingly fluidly in Logseq, because it makes it so cheap to create, as fast as you create on the command-line and emacs, in fact, which are platforms with good track record of attracting the types of people that build sophisticated structures. Take XML authoring practice that evolved into YAML for instance. Well, Logseq could (also) be a Yaml editor and in a way, it almost is. One could argue that Markdown was also a response to difficulty authoring XML and JSON. I would personally favour RDF/XML or something like that as the backend language, or some serialisation strategy that stays loyal to Logseq’s simplicity, yet is capable of taking full advantage of the vast capabilities provided by OWL2.

When you put it in social context, well my belief is that platforms such as Logseq can serve as a way for independent organisms to converse effectively, at a level that has not yet been seen. What you’re after though, is what Elon Musk is trying to do with Twitter. So in all honesty, you may want to put your efforts in guiding that work. Twitter already gives you something super big, which is the global commoditisation of humans voting. Millions can systematically vote on a clearly-defined topic. Of course, the big issue there is fraud/duplicate detection and false identities, robots and what not. Getting rid of those is the big chuck of the work. The interesting fact about this is that one of the first tech companies that actually had to deal with this issue of fraud detection was, none other than PayPal led by Elon himself. I’m not an Elon fan or anything, merely trying to explain his way of thinking and stuff he may have planned for us. But mainly, how his work is close to what you are stating in your comment. Since you’re an artist by the way, thanks for sharing that info, you could start thinking about ways in which you can connect the power of Wikipedia/DBpedia to Twitter. There might be Logseq in between or not. But that’s the kind of thinking that allows to create order out of chaos, to create waves like cryptos do. Anyway, too deep for a Monday morning. But I’m here to help if you want to explore and I see that you have already created a thread. I’ll try to look into it further, too.

UPDATE: I wish Logseq’s core contributors also participated in this topic. I don’t know them unfortunately, but I’d like nothing more than to pick their mind on some of the adjacent markets they are exploring. At the end of the day, they are open source with investment from respected VCs, so I’m sure they might consider opinions of their community members. At the same time, I wonder where the strategic conversations take place, which to a degree, for me, also determines the level of openness they plan to implement in the mid term. And Discord cannot be the answer, I’m sorry. Synchronous communication for such deep convos are counterproductive to say the least.

UPDATE (completely off topic but since the thought arose from this thread, I decided to share it but it is not directly related to Logseq, per se, so apologies for being off topic):

One strategy that could help with fraud detection is to embrace the concept of a robot and start defining their status on something like Twitter. I mean, we’re starting to have people going around risking their well-paid jobs to say that a certain robot is sentient. Some things ought to be changing as a response to that. And recognising robots and being able to tell their lineage for the purposes of bookkeeping. Their lineage is key, this way we can count them appropriately. Some semantic work on reasoning about data. It’s been my job, only for the past 12 years.

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I haven’t come here to talk about my book (I don’t have any), but for allusions, allow me to clarify this point a bit (I hope I don’t bother anyone, I still don’t know the policy regarding noise in this forum, despite being a thread to make yourself known, and despite being the thread to meet another person, I consider that, in some way, this dialogue contributes to getting to know both, him and myself. In any case, do not hesitate to express your opinion about this).

My motivations are born from a vision, from a plausible future in which I think I can make my small contribution to make it possible, starting from the basis that it is desirable, but feeling proud to have been part of it.

A vision that has a strong ethical component. A commitment to the reduction of human suffering and the protection of the environment, which, in my opinion, would be synonymous with an intelligent society.

I believe that many of the cadences of this society are due to the fact that political debates, both regarding those promoted by the mass media, and those that occur in high spheres at the geopolitical level, are poor debates, at an expressly low intellectual level, totally manipulated and with malevolent intentions, surreptitiously and Machiavellian.

The master’s tools will not dismantle the master’s house. That is why I believe that the revolution that changes this widespread paradigm of self-destruction will appear as a logical consequence of the acquisition of a certain level of individual and collective sovereignty, both of thought and of resources (technological or natural), which would surely describe a fractal geometry in its different layers.

Therefore, when I talk about feeding an AI with our graph, I do not leave aside the concept of privacy first. On the contrary. I mean an algorithm and a graph in which we are root.

Perhaps with another example it will be better understood. Imagine the point where the Logseq community uses Logseq to both document and manage their workflow or to reach a consensus on what are the best decisions to make (which would be a political aspect, as is the decision to license its code with the current license). Imagine that its political ontology is being defined as consensus is reached. Imagine what role AI technology could play, both at the level of group dynamics and detection of patterns and profiles, as well as in the sense of raising the level of abstraction of the debates that take place. I am talking about a synchronized growth, or symbiotic, of the collective and the unindividual as being part of it.

But also on an individual, or even intimate level. I think of the possible contribution of the technology of algorithms as a resource to delegate non-creative tasks, as a resource to be able to glimpse order at a higher level of abstraction, as the reflection of a projection on a surface with properties that make it possible to glimpse something that has always been there.

And I also think that it can contribute to the aspect of the nature of the story, of how the positions between interlocutors are defined. It is not about arguing giving free rein to our most primal emotions and impulses, and then having an AI say who is right. It has to do with, knowingly, the language used is of a higher level of abstraction, more formal, precisely so that it is correctly parsed and inserted, forcing this dynamic of intervention to better structure the ideas before intervening and to manage each one its own contradictions (fallacies and errors) in a more optimal way.

The issue of user interfaces, better another day.