September 15, 2019

The Latest: Red could help AI be more precise; community stars; one CSV codec to rule them all?

Hello to all the great makers, doers and creative people who are using Red, helping the Red Language grow and improve! As always, there's a standing invitation for you to join us on Gitter, Telegram or Github (if you haven't already) to ask questions and tell us about your Red-powered projects.

Here are some recent highlights we’d like to share with you:

1. Tickets Get Priority

In the last month, our core team has closed a large number of tickets.We’d like to thank community members rgchris, giesse, and dumblob who are just a few of the passionate contributors putting Red through its paces and providing feedback as fixes and changes occur. @WArP ran the numbers for us, showing a cyclical growth pattern linking bursts of closed issues and some serious Red progress, and September’s not even done yet!...:

2. CSV Codec Available

Our newly updated CSV codec has been merged in the master branch and is now a part of the nightly (or automatic) build here. It is in an experimental phase, and we want your feedback.

Should the standard codec only support block results, so it’s as simple as possible? Or do people want and need record and column formats as well (using the load-csv/to-csv helper funcs, rather than load/as)? Including those features as standard means they’re always available, rather than moving them to an extended CSV module; but the downside is added size to the base Red binary.

Applause goes to @rebolek’s excellent organization and his wiki on the codec, which explains the various ways in which Red can represent data matrices. He writes, “Choosing the right format depends on a lot of circumstances, for example, memory usage - column store is more efficient if you have more rows than columns. The bigger the difference, the more efficient.”

You can judge their efficiency here, where @rebolek has laid out the compile time, size and speed of each version, including encapping and lite. Be sure to get the latest build, and chat with everyone on Gitter to tell us what you think.

3. Red has reached 4K stars on GitHub!

We’re truly grateful for all the interest and support, and we are proud of the way our growth has been powered by this community.

4. AI + Red Lang Stack: Precision Tuning With Local OR Web-Based Datasets

In conversation with @ameridroid:
“Presently, it seems like most AI systems available today either allow building an AI from scratch using low level code (difficult and time-consuming), *OR* using a pre-built AI system that doesn't allow any fine-tuning or low-level programming...with the advent of NPUs (Neural Processing Units) akin to CPUs and GPUs, an AI toolkit would allow specifying what type of AI we want to perform (facial, image or speech recognition, generic neural net for specialized AI functions, etc.), the training data (images, audio, etc.) and then allow us to send it the input data stream and receive an output data stream…[using Red] would also allow us to integrate with the AI system at a low level if we have specific needs not addressed by the higher-level funcs. Red dialects would be a good way to define the AI functionality that's desired (a lot like VID does for graphics), but also allow the AI components, like the learning dataset or output data stream sanitization routines, to be fine-tuned via functions. Red can already work on web-based data using 'read or 'load, or work on local data in the same way; the learning data for a particular AI task could be located on the web or on the local machine. That's not easily possible with a lot of the AI solutions available today.”

Check back in the next few days for an update from @dockimbel!

Ideas, contributions, feedback? Leave a comment here, or c’mon over and join our conversation on TelegramGitter, or Github.


  1. Red is following another new topic to try to raise money again? You guys got money from the ICO, why not just finish what you promised? Where is the red-c3? Following those new topic just make this project a to-VC startup.

  2. The AI project is a community member's, not Team Red. And, after a delay, Red/C3 is again under active development.

  3. quick question, do we have an estimate when Red will be reaching ver 1.0?

  4. No, because "1.0" is an arbitrary moniker and we try not to pre-announce things too much. We've learned that doesn't work well. :^) The best thing to do is monitor development as it proceeds.

    1. I go to the Roadmap from time to time, and also the Trello to see how things are progressing. Does not seem to be much progress, also the way the Trello is organized today, you cannot see which one is progressing except by opening every single card and look at comments.
      Can I propose something about the Trello use? , would it be possible to have a TODO list, In Progress list, and Completed list using Trello i.e a Kanban and moves the card as it progresses. It makes it easier for people to see what is being done and general progress.
      Have a great day.

    2. We don't keep up with Trello on a regular basis. Too many tools and channels. The best ways to monitor progress are to follow things on Gitter, where the main public chat lives, or read the blog posts when they come out, which says what has been done, and sometimes looks forward a bit.

  5. ICOs are fine and digital money is here to stay. But with growing computational power, neural networks and deep learning are seeing a resurgence, with more and more companies jumping to the field. The thing is that languages like Python enjoy important libraries to perform the statistical and linear algebra equations required (and have deep learning algorithm templates readily available on line). I'm guessing that new programmers would rather adopt those languages in order to become employable or just keep current. In short, I think that Red could greatly facilitate adoption and spread if it embraces AI, either by creating a DSL or by just being able to provide comparable libraries (and algorithms). This AI thing is not a fad (check it out), and products develop because they have demand (check around!). Now, that is simple math. Don't leave it for tomorrow.

    Brother Damian

    1. Thanks for the comment Damian. Libraries will come, of course. The math may be simple, but we have to add other formulae like "Developers don't pay for languages, even if widely adopted.", "Where do our AI experts come from to design these new elements." and, of course, "Time travel." so we can get it all done. :^)

  6. Today there is a big support provided for customers in every industry capitalize on advancements in AI. How much help will come from smart machines and robots?


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