The solution may be understandable and provably correct.
The "philosophy" behind this approach could be seen as that
human intelligence is rational, and can
be represented by logical systems incorporating truth maintenance.
The numeric parameters are modified by a large number (maybe millions) of interactions with the world
(e.g. the real world, or a software world).
The modifications make the program perform better.
They may continue for a long time until a high-performing program emerges.
This approach does not worry about contradictions in the program.
The program contains a vast number of rules which may contradict each other.
It makes ever-changing decisions about which rules to follow.
The solution may be hard to analyse.
It may be hard to know if the solution is optimal or always correct.
Standards are empirical: Is this program better than the alternatives?
The "philosophy" behind this approach could be seen as:
Whatever works, works, in evolution.
There is no particular reason for evolution to care about constructing logical systems.
Logic is done rarely, if at all, by most people.
The mind - even the mind of a logician - is a semi-rational competition of
multiple conflicting ideas, rules, thoughts, emotions and drives.
Including a struggle of the "memes"
that populate your brain
(using the pre-Internet definition of "meme").
A major theme in
"Artificial Life" research is simulating systems with large numbers of simple actors.
e.g. Swarms of insects. Schools of fish.
The immune system.
Such simulations can sometimes be applied to more intelligent actors.
e.g. Human crowd behaviour, or warfare, or economics.
Artificial Life demo: Conway's Game of Life.
A simulation of simple actors that can change neighbouring squares,
and yet one with amazingly complex dynamics.
Click to run World: The Game of Life at Ancient Brain.
Click "Randomize" and then "Play".
Spam detection software, running on the system "alpamayo.computing.dcu.ie", has
identified this incoming email as possible spam.
Content analysis details: (25.2 points, 2.0 required)
pts rule name description
---- ---------------------- --------------------------------------------------
1.0 FSL_XM_419 Old OE version in X-Mailer only seen in 419 spam
2.6 NSL_RCVD_FROM_USER Received from User
0.0 FSL_RCVD_USER FSL_RCVD_USER
2.4 TVD_PH_BODY_ACCOUNTS_PRE BODY: TVD_PH_BODY_ACCOUNTS_PRE
0.0 HTML_MESSAGE BODY: HTML included in message
0.8 BAYES_50 BODY: Bayes spam probability is 40 to 60%
[score: 0.4972]
0.0 T_OBFU_HTML_ATTACH BODY: HTML attachment with non-text MIME type
0.7 MIME_HTML_ONLY BODY: Message only has text/html MIME parts
0.8 FSL_UA FSL_UA
0.4 HTML_MIME_NO_HTML_TAG HTML-only message, but there is no HTML tag
0.1 FORGED_OUTLOOK_TAGS Outlook can't send HTML in this format
0.0 T_HTML_ATTACH HTML attachment to bypass scanning?
1.7 FROM_MISSP_MSFT From misspaced + supposed Microsoft tool
0.0 T_OBFU_ATTACH_MISSP Obfuscated attachment type and misspaced From
0.0 FSL_NEW_HELO_USER FSL_NEW_HELO_USER
1.9 AXB_XMAILER_MIMEOLE_OL_024C2 AXB_XMAILER_MIMEOLE_OL_024C2
2.6 MSOE_MID_WRONG_CASE MSOE_MID_WRONG_CASE
0.0 FORGED_OUTLOOK_HTML Outlook can't send HTML message only
3.7 FROM_MISSP_TO_UNDISC From misspaced, To undisclosed
2.0 FSL_MISSP_REPLYTO Mis-spaced from and Reply-to
1.0 FROM_MISSP_USER From misspaced, from "User"
1.6 FROM_MISSPACED From: missing whitespace
0.0 FROM_MISSP_REPLYTO From misspaced, has Reply-To
1.9 FORGED_MUA_OUTLOOK Forged mail pretending to be from MS Outlook
An example of computer vision plus
OCR plus machine translation plus "augmented reality".
The
Word Lens app.
Google bought Word Lens
and this functionality is incorporated into
the
Google Translate
app.
See videos.
Baron und Baronin Willy von Wattenwyl und ihre kinder Yvonne, Gérard und Sigismund
geben hiemit tiefbetrübt Nachricht von dem Ableben ihrer innigstgeliebten Mutter, Schwiegermutter, Grossmutter und Urgrossmutter, der hochwohlgeborenen Frau
Baronin von Stentzsch-Prittag geb. Margaret Livingston-Gibbon,
welche am 3. Januar 1911 nach kurzem Leiden in ihrem 93. Lebensjahre in Schloss Lannach bei Graz gottergeben entschlummerte.
Die teure Heimgegangene wird nach Graz zur Aufbahrung in der Leichenhalle des Evangelischen Friedhofes überführt, woselbst Donnerstag den 5. d. M. um 2 Uhr nachmittags die Einsegnung und hierauf die Bestattung im eigenen Grabe erfolgt.
Lannach, am 3. Januar 1911.
1911 death notice in my genealogy research.
Baron and Baroness Willy von Watteville and their children Yvonne, Gérard and Sigismund
hereby give deeply saddened by the death of their message innigstgeliebten mother, mother, grandmother and great-grandmother, the woman Highborne
Baroness von Stentzsch-Prittag born Margaret Livingston-Gibbon,
which asleep resignedly on January 3 in 1911 according to recently suffering in its 93rd year of life in Schloss Lannach near Graz.
The expensive home Gone is transferred to Graz for laying out in the morgue of the Protestant cemetery, woselbst Thursday 5th inst. By 2 clock in the afternoon, the blessing and then the burial in his own tomb done.
Lannach, on 3 January 1911th
Baron and Baroness Willy von Wattenwyl and their children Yvonne, Gérard and Sigismund
hereby give deeply grieved notice of the death of their dearly beloved mother, mother-in-law, grandmother and great-grandmother, the most noble lady
Baroness von Stentzsch-Prittag, formerly Margaret Livingston Gibbon,
who on 3 January 1911 after a short illness at the age of 93 years, in Lannach Castle near Graz, passed away.
The dear departed will be taken to Graz to lie in the mortuary of the Protestant cemetery, where on Thursday the 5th of the month at 2 o'clock in the afternoon the benediction and afterwards the burial in her own vault will take place.
Lannach, 3 January 1911.
The correct translation.
Baron and Baroness Willy von Wattenwyl and their children Yvonne, Gérard and Sigismund hereby announce with deep sadness the death of their dearly beloved mother, mother-in-law, grandmother and great-grandmother, the very well-born Baroness von Stentzsch-Prittag
née Margaret Livingston-Gibbon, who died on January 3rd. January 1911, after a short suffering, she fell asleep in devotion to God in Lannach Castle near Graz in her 93rd year of life.
The dearly departed woman will be transported to Graz to be laid out in the mortuary of the Evangelical Cemetery, where on Thursday the 5th of this year. M. at 2 o'clock in the afternoon the blessing and then the burial in his own grave takes place.
Lannach, January 3, 1911.
I went back to it in 2023 and Google now does this translation.
There are still some issues.
Some of the abbreviations and punctuation in the original may be old-fashioned and hence unexpected.
Discussion:
Do you find this machine translation impressive?
Or unimpressive?
Can you spot any specific language constructs the machine has trouble with?
Competitions
Competitions drive progress in AI since you can prove one system is better than another.
How do you prove that one language-using program (like a chatbot) is better than another?
Competitions are again a useful idea.
The Turing Test
is a thought experiment introduced at the dawn of AI to consider what intelligence is.
If you talk to a program for a while and think it is a human,
then does that mean it is intelligent?
If you cannot tell the difference, then on what grounds would you deny that the program is intelligent?
AI and board games is a classic arena for AI competitions.
Board games are very "computerisable".
To play football in the real world (or indeed chess in the real world)
we need robotic vision sensors trying to detect where the football / chess piece is,
and mapping what it sees to some model of the pitch / board.
But if we run a board game on computer, with no physical real-world component,
then we just tell the program where each chess piece is.
There is no sensing problem.
In a software-only world, the program can be given perfect inputs, with no noise or errors.
Though there may still be "hidden state".
(Inputs not given to the program.)
AI finally beating humans at chess
led to much discussion:
Deep Blue examines 200 million moves a second.
Which seems totally different to how humans do it.
It is often said that human chess experts examine at most 4 moves a second.
But, one argument goes, how do they know?
That's all the expert is conscious of,
but maybe his subconscious parallel pattern-matchers are examining hundreds of moves a second.
Or implicitly examining millions of moves a second
by passing the current board position through a neural machine that has the results of millions of past moves compiled into it.
Only the best of the subconscious matches get passed up to the conscious for heavy-duty analysis.
Recall the "symbol grounding" problem in our discussion of chatbots.
Is there any way to get a program that does "understand" the words it uses?
What would that even mean?
Would the program have to have a body and interact with the real world?
Or would it just need a better dictionary?
Ancient Brain
