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-[[!meta title="A.I. that Helps Play the Game of Your Life - Andrew J. Dougherty"]]
-
-- 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.