• What if you collect thousands of A.I. tools and apply them towards planning your life? That's exactly what FRDCSA has been working on for the last twenty years. Only soon, you can download a VM containing the core systems. In today's increasingly complex world, sometimes we can be blindsided by rules we didn't know existed. If you're living on the edge, this can be a disaster. What if all the rules that applied to us, from legal, to financial, to just basic common sense, were collected into a system that was capable of reasoning with them and planning with them. You could put your objectives into the system and it would factor in all these things and spit out a plan. Well that's just one of the many things that FRDCSA's Free Life Planner A.I. seeks to do.

  • A.I. is problem-solving, and software that can do this has to grow larger as problems and their complexity multiply. Over the last 20 years the FRDCSA project has collected thousands of codebases, and written hundreds of codebases, gluing everything together and making it available from within Emacs, Perl and Prolog. The Free Life Planner, FLP, takes this and applies it directly towards assisting users in their minute-to-minute, day-to-day, year-to-year lives.

  • Think of a massive collection like V'ger had in Star Trek: The Motion Picture, of things like strong game-playing systems like AlphaZero, but tailored to the specific problems people most often encounter with finances, meal-planning, transportation, health care, etc.

  • If you're interested in a personal A.I. assistant, stay tuned as we cover the Free Life Planner. But it is after all only one of over 600 custom codebases developed for FRDCSA. Soon, Panoply, the virtual machine distribution of FRDCSA, will be released for you to explore. So, let's have a look at some of what FRDCSA can do for you.

  • FRDCSA wants to help you solve as many problems as it can, treating the world as a game which it tries to win, by proofs that bad things don't happen. We know that if a set of problems constitutes t bits of information, and a set of programs contains less than t bits of information, then it is impossible to solve these problem from these programs. When it comes to AI, bigger is better. In 2002 this led me to Emacs, Perl, Debian and Cyc, and a growing list of over 100,000 external codebases. In fact, FRDCSA excels at finding and packaging software, and exposing APIs for reuse.

  • Someone once asked me, what does FRDCSA do? I couldn't give them an answer. I didn't know where to begin. There aren't any silver bullets to demonstrate. So where does Emacs fit in? It is the develop console, mission control, where most development and usage occurs. There are dozens of modes, thousands of key-bound functions. Let's look at some representative Emacs systems written because we couldn't find anything with similar capabilities.

  • This is UniLang, a multi-agent system facilitator, and a core FRDCSA system. UniLang let's all the systems talk to each other. For the Free Life Planner we want to spider the internet, to find, retrieve and index rules and software, to apply them towards improving the way we live on a daily basis. But to intelligently spider you need to be able to understand the text. Because lots of useful information on the internet is in text form, FRDCSA is heavily focused on natural language understanding.

  • This is NLU, it's a system based on semantically annotating text.

  • Okay, so our spider is helping us to locate rules. But what about software, we still need more software. New software is being written all the time, how do we gather it? IES is an information extraction system, it allows you to label text like software metadata using text properties, and then train a model and use it to label other text. This way we can extract information about software systems we want to acquire and package.

  • Okay great, we're getting more software, now what do we do? Let's go back to rules for a minute. We have a lot of text, but how do we translate it into a machine-readable format? That's where NLU-MF comes in. Okay we have rules in a machine readable format, but how do we know when they're applicable? We have to store the world-state somehow. Enter FreeKBS2, our free knowledge-based system, with persistent storage of rules and facts. It is a useful Emacs front-end for rapidly manipulating symbolic rules and facts and editing the knowledge-base.

  • So now we have some refined executable rules. How do we reason with these common sense rules? Enter the Cyc system, undoubtedly the world's largest, most sophisticated, common sense A.I.. But Cyc is proprietary. Well, thanks to Douglas Miles, the author of the free (libre) LogicMOO system, that's not a problem anymore. LogicMOO aims to be backward compatible with Cyc itself. Let's demonstrate our cyc-mode-2, which aims to create a deep channel between Emacs and LogicMOO.

  • Today's software is fantastic, but there's not a lot in the way of integrated approaches to planning one's life to improve the way we live on a daily basis. The version of Free Life Planner on the Panoply VM distribution currently does calendaring, recurrences, reminders, planning, scheduling and execution. But the good news is, we can make it a lot better. The potential for a rule-based crowd-sourced life planner is tremendous.

  • People finally started understanding better what FLP, and to some extent, FRDCSA, does when I wrote the following use case story. It's the homeless-story.html, I'll provide the link later. It's the story of a person facing homelessness who uses FLP to escape homelessness. I highly suggest you read it to familiarize yourself with the FLP. Some people think it is science-fiction, but I assure you this story is doable with the tools we've collected.

  • Okay, where are we? We have a rule-based system, but our software cannot do everything, no piece of software can. We have lists of software that the spider and IES got us. Retrieving it is easy, packaging it is hard. How do we package this software? Why not record ourselves packaging software to add data to the A.I. so it can learn how to make packages.

  • So we have lots of data about how to package, but now the system has to figure out how to make packages on its own. It needs to be able to think and plan. What's more, once the software is packaged, FLP has to figure out how to use that software. Enter the software robot called Prolog-Agent. Prolog-Agent is an intelligent agent under development that can control Emacs in order to achieve objectives, and will eventually be able to make use of recorded traces.

  • So now we have all these rules and software, but wouldn't it be nice if we could help teach the users some of the rules, and how to use the software. That's what CLEAR does. CLEAR is a great way to have books, manuals, websites, etc, read to you, allowing you to pause, quit, resume and filter out nonsense.

  • If you'd like to get a copy of Panoply when the public alpha is hopefully released in a few months, please email me. I will add your name to the mailinglist. But also, please join us at #frdcsa and/or #freelifeplanner on freenode. I would like you to try out the FRDCSA, familiarize yourself with it, and test it. Thank you so much for listening. Have a great day.