445 karma · joined January 12, 2017
https://arstechnica.com/science/2019/10/neanderthal-glue-was...
However the gist is over 8 years old and there doesnt seem to be a public repository for the language available.
Edit: add NIal repo link
I think the hope with both OpenSPIM and mesoSPIM initiatives is by getting design information out and plans out as open source, the community has a reference system they can experiment with and find mechanisms that work to help bring the price of the systems down. Typically, most expensive parts are things like cameras and detection objectives. If you can scrounge parts, find alternative units (cheaper cameras etc.) you can find means to significantly reduce cost. Similarly, if you are trying to push the boundaries - you can see where you can gain potential advantage by substituting sub-systems for greater resolution units etc.
My hope is that through community initiatives like OpenSPIM and MesoSPIM, the community can reduce costs of these systems by an order of magnitude over the coming years, while at the same time, using similar reference systems other leading teams can push the boundaries and highlight what is possible.
Its especially great that the team are actively building a community around the project for exchange of ideas between lightsheet developers and end users.
For anyone interested and wanting to deep dive for example on parts list or laser selection recommend reading the wiki here: https://github.com/mesoSPIM/mesoSPIM-hardware-documentation/...
Very cool project - thanks X for posting this.
0. Decide how you want to license codebase and how much you care about post-release adoption.
1. Write enough documentation to understand what the project is and can be used for (i.e. an edited version of what you have already posted)
2. Minimal demo project / app that the can be build so a prospective user can understand the application / library (probably updated example you already have)
3. Clear repeatable build instructions for demo app/ lib etc
4. License and Copyrights clearly stated and in codebase.
5. One or two paragraph guidance on contributing to the project or using the project.
6. Plan on where to announce, announcement msg and follow up so you can monitor interest.
7. If you decide you do care about adoption, plan on some regular but minimal effort after release to write updates/project blogs so folks can see what is happening and encourage interest. *i.e. dont just throw it public, do no marketing or launch effort and expect people to magically find it and adopt it - some sustenance effort will be necessary. If you don’t care, but just want to release it so its out there – then this step is obviously not necessary.
Finally, perhaps, an alternate way to get people interested in Lucidity and demonstrate Lucidity's benefits would be to package up Lucidity and look to contribute new features / functionality that leverage a subset of Lucidity to an existing project that would benefit from those Lucidity's features.
Whatever you decide, Good luck.
There is clearly some interest in this area e.g. DS-PITON project (See https://bit.ly/35Eq35R) or the Jive project for java (https://cse.buffalo.edu/jive/). Another would be Glamours Toolkit for Pharo Smalltalk (https://gtoolkit.com/) - though it has a larger scope.
If you do not have time or funds to continue it in its current form and you do not have any 3rd party at this point interested in sponsoring development in some form, and you cannot see how to leverage it in the future - what do you have to lose by open sourcing it?
At worst - it languishes, and no one uses it but it will give you a referenceable open source project for your CV that may help attract work in this or a related area.
At best, the project sees adoption and opens new opportunities for you.
Given the quality on display in the articles and videos I would expect the project to get some interest especially amongst IDE and program visualization communities.
If you do decide to open source the project be careful on licensing choice (to encourage adoption in a manner you want) and copyright notices to ensure you are associated with it. Do expect to have to invest a little time in documentation and code clean up before making it available - but think of that as future advertising for your own capabilities.
Good luck
One of the interesting additions over plain Oberon is the concept and support for active cells. Active Cells provide an abstract mechanism to define systems composed of computing elements that exchange information over message channels. Not new to anyone familiar with Go Channels etc buts its one of the nice things in Active oberon and provides support for both Actor models, concurrency and parallel programming.
How this applies to scalable systems and custom FPGA hardware is described in an older paper - see https://inf.ethz.ch/personal/felixf/pdfs/2012_ActiveCells.pd...
In addition to cells there is math support for tensors (via Math Array) and matlab like array processing as well.
From a language implementation perspective it provides quite a lot in a relatively small, clean and easy to follow code base.
https://mstoeckl.com/notes/gsoc/blog.html
They are definitely worth going through and Manuel Stoeckl deserves a lot of good karma for taking this on.
Birthday AMA - is very interesting - both the discussion of computational intelligence as part of language design at the start but especially the wide range of questions asked and answered.
The live CEOing vids are also an interesting insight for those interested in how wolfram and mathematica are developed.
re: NeilV - Braitenberg "Vehicles" book - enough goodness cannot be said about that book. It seems deceptively simple but its a wonderful place to start thinking about and being inspired to building simple beasties.
As should Grey walter's wonderful tortoise: http://www.bristol.ac.uk/news/2008/212017945378.html
Regarding Open source / sponsorship / support: - Andrew I will follow up directly via email over weekend.
Are you still considering open sourcing Sciter? I personally hope so - but also know how much is involved in going down that path.
The term has been widely used in manufacturing since then and has been a key sales messaging for companies like IBM, Dassault Systems, Siemens amongst others. United Technologies for example have been demonstrating digital twin concepts for routing in flight engine telematics into 3D virtual engine simulations for trouble shooting and maintenance since 2005.
The term regularly crops up in manufacturing, maintenance, smart cities, IoT and more recently AI related proposals and projects and generally means a virtual simulation that uses real data to simulate a complex system.
As pointed out by many over the years - the concepts are also described by Prof.David Gelernter in his book 'MIrror Worlds: Or the Day Software Puts the Universe in a Shoebox...How It Will Happen and What It Will Mean' first ipublished in 1991.
SO perhaps less bizarre and more just less familiar on HN.
If you have not read the books they are a really good practical introductions to building interpreters and compilers.