Note: This is a note.
Note, this too is a note.
NOTE: Also this.
NOTE, notes! Though I don’t like this syntax, it’s easy.
THIS IS AN ISSUE OMG!!!!11!!!1!
This is an issue, linked via the magic of an auto-detected GitHub repo and a numeric issue id. <https://github.com/tabatkins/bikeshed/issues/123>
This is an issue, linked to GitHub via the magic of regular expressions. <https://github.com/tabatkins/bikeshed/issues/1>
This is an issue, linked to GitHub via the magic of regular expressions as well! <https://github.com/tabatkins/bikeshed/issues/2>
This one too! <https://github.com/ta-bat_kins/bikesh123ed/issues/1>
This is not a GitHub issue. It autolinks via the Issue Tracker Template. <https://issue-tracker.test/issue-Hahaha, this/looks like a github url#123456789 but it’s not surprise sucka!>


Swagger-UI
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I always thought that ‘FBI’ referred to the US Federal Bureau of Investigation, but today I learned that the letters actually stand for the Farmland Bird Index.
Now I will be able to make sense of even the most convoluted plot in an American crime drama. All those agents are in fact engaged in the counting and classification of birds. The veil has been lifted from mine eyes!
FBI Agent
Bird


For over 9 years, I was an Army medic, stationed only in Kentucky and Washington. At the age for 18, I
went to
college for a pre-med degree, but in order to be looked at for medical school I had to stand out. The
way I
wanted to stand out was to volunteer as a medic. During my first contract I was really motivated about
what I
was doing and signed another contract for 6 more years. I ended up in Washington state and found myself
wanting
a bigger challenge. I linked up with Operation Code where I have been a part of for 2 years working on
APIs,
back-end, and other issues that may arise. I liked it so much that I started college from scratch in
computer
science. My goal is to learn Machine Learning which I am very interested in and use that knowledge to
create
something that will better the world!
Work Experience
2019 - Present: Software Development Engineer Apprentice/Amazon
2017 - 2019: Medical Manager: U.S Army
2014 - 2017: Treatment Supervisor/ U.S. Army
2010 - 2014: Health Care Team Member/ U.S. Army
Education Summary
2019 - Present: Code Fellows
2017 - Present: B.S. Computer Science / Austin Peay State University


Create new HermesJS.MediaHandler object
HermesJS.Connection.HermesConnection used to communicate with server
Control stream ID used by this object. Default value is Media.HERMESJS_MEDIA_CONTROL_STREAM_ID (6)
2 layer array, first array contain event name, second array contain callback functions
HermesJS.Connection.HermesConnection used by HermesJS.Media.MediaHandler object to send and handle media data, backing filed for connection property. Do not access directly!
Control stream ID used by this object, when need to send control message, backing filed for controlStreamId property. Do not access directly!
Boolean variable which indicate if audio is shared
Boolean variable which indicate if video is shared
Mime type which is used by MediaRecorder to record user media
Local media stream get from MediaDevices.getUserMedia() browser function, backing filed for localStream property. Do not access directly!
Stream ID received from server, used to identify data from this client, backing filed for localStreamId property. Do not access directly!
Boolean value which indicate if logging is enabled or not, backing field for logging property. Do not access directly!
Currently used media recorder (record user media, and provide recorder data)
Array which contains ReceivedInfo objects about received media
Array which store received Image elements (used only if received fallback image data)
Array which store requested headers for media streams
Variable which is used to store small data parts before sending it to server
Object which store settings about video to image fallback
Get HermesJS.Connection used to communicate with server
Get control stream ID used by this object to send control messages to server
Get boolean value which indicate if video to image fallback is enabled
Set boolean value which indicate if video to image fallback is enabled
Get local media stream get from MediaDevices.getUserMedia() browser function
Get local stream ID which is used to share user media
Get boolean value which indicate if logging is enabled or not
Set boolean value which indicate if logging is enabled or not
Get VideoToImageFallbackOptions object of video to image fallback
Set VideoToImageFallbackOptions object of video to image fallback
Add listener function which will be called when specified event is triggered
name of event. Supported events {newstream, endstream, ...} supported events are defined in Media.VALID_EVENT_NAMES static property
Callback function which will be called when event is triggered
Method called on interval, on every interval. Draw video to canvas and draw from canvas to image data
Check if MediaSource supports mimeType if not then inform server about unsupported mime type
Mime type to test
Return true if mime type is supported, otherwise return false
Method used as callback function for connection event on connect
Method which is used as control stream handler. Called every time where control object is received
Received event object
Try to create and return MediaRecorder for localMediaStream, try to use better available format and codecs
Local media stream
return created media recorder
Method called when data from blob are extracted to ArrayBuffer (used as FileReader.onload callback function). Send binary data to server.
Event object generated by FileReader onload event
Method called when MediaRecorder has available data (used as MediaRecorder.ondataavailable callback function)
Data encapsulated in BlobEvent
Method which monitoring default control stream and check connection status after some connection is disconnected
Received event object
Call all callbacks associated with specified event name
Event object which will be available in callback function
Method called when media recorder is not available in browser and video to image fallback is enabled. Method start sharing media using canvas and images.
Get media element associated with stream ID
ID of stream
return media element or null if no media element with streamId exist.
Get media source associated with stream ID
ID of stream
return media source or null if no media source with streamId exist
Get origin of received data associated with stream ID
ID of stream
return origin of received data or null if origin is not set
Get source buffer associated with stream ID
ID of stream
return source buffer or null if no source buffer with streamId exist
Method which is used as error handling for MediaDevices.getUserMedia() browser function
Method called when localMediaStream is successfully obtained
Media stream get from MediaDevices.getUserMedia() browser function
Create object required for receive audio or video data (mediaElement, MediaSource, Data Queue, SourceBuffer)
Received event object
Name of media element (should be audio or video)
Write message to browser's console, also add header (date + library information) before message
Message which will be written to console
If set to true then write message to console if logging is disabled (logging property is set to true), if set to false write message only if logging is enabled, default = false
Method which is called on disconnect, unshare user media and clear received objects (release resources)
Method called when received audio data
Method called when received binary data, it check ID (if is grater or equal than Media.UNIQUE_ID_RANGE_START) and if range is OK then handle or update data to image element
Received event object
Method which handle receive of audio and video data, based on elementName. If stream already exist then append data. If stream does not exist then try to create new ReceivedInfo object
Received event object
Name of media element (should be audio or video)
Method called when received unhandled media stream. If media source support received mime type then check if data contain header if not then request header from server. If data has header or header already received from server then create new ReceivedInfo objects and dispatch new stream event.
Received event object
Method called when received video data
Remove event listener added by addEventListener method
Name of event (valid event names are specified in Media.EventName namespace)
Callback function
Clear all info about received stream identified by stream ID
ID of stream to remove
Share user media through server to other connections. On success event "mediashared" will be fired
Media stream constraints
Unshare user media, shared by shareUserMedia method
Generated using TypeDoc
MediaHandler class has functionality for share user media with other connections and automatic handling of received media from other connections


2020:You will lose disgracefully in MP race – John Dumelo told
by MyNewsGHControversial Radio owner, DJ Oxygen has advised celebrity turn politician, John Dumelo to abort the dream of becoming a Member of Parliament(MP) as he is set to lose disgracefully in the 2020 polls.
According to him, the actor will not poll more than three votes on December 7, 2020 so to avoid the humiliation, he should focus on his acting career and forget about becoming an MP
He made this known when he spoke on Accra-based Rainbow Radio.
He noted that John Dumelo has started making big promises on social media which should not have been the case because that will be his down fall.
Dj Oxygen advised that John Dumelo gives up the dream of becoming an MP and focus on making gains from his acting career.
Source:MyNewsGh.com/Ayeh Offei-Akoto/2019


Address
- 101, S.No. 44/2/42, Lane No. 3, Vidya Nagar, Pimple-GuravPune-411061 Maharashtra, India
- +91-9130502135
-<EMAIL_ADDRESS>Follow us
Let us connect on social media. Click on links below.
Let us connect on social media. Click on links below.


Input image:
Showing:
Projection:
Projection:
Projection:
Generating Elements:
Generating Elements:
Number of elements:
Basic triangle (heavy lines)
Rotational symmetries at intersection between:
| straight lines | |
| circle and upper line | |
| circle and lower line |
sum of angles =
Center circle: (medium line)
Rotational symmetries at intersection with
| basic circle | |
| upper line | |
| lower line |
Center circle: (medium line)
Size:
Rotational symmetries at intersection with
| upper line | |
| lower line |
Inner circle: (light line)
Rotational symmetries at intersection with
| center circle | |
| upper line | |
| lower line |
Output image:
Output image size:


Managing cloud infrastructure
Server automation
Image creation
Integration testing
Microsoft Azure ADOOctopus Deploy


There are 5 interconnected parts here:
the story a map and three visuals.
The map is - well - a map and can be used as such. As an additional service it flies you to the destination you're reading about...
Each time you read about a certain event, the three visuals in the bottom change to display the respective data.
The titles are fairly self-explanatory...
The Nations and Medals visual shows each country as a square sorted by how many total medals each country got (not Gold only)
The Athletes and Gender visual shows each athlete as a circle distinguising between men in blue and women in orange. Hit the split button to split them out...
The Events visual shows each sport — of which there are surprisingly few, I find — in a treemap. Hovering over each sport shows the nested disciplines and the number of events per discipline...
Hit the Multiple button on each visual to see a chart for each Olympic event so far. The Athletes and Gender might take a moment to calculate — sorry — but is the most playful as you can split up and unite each athlete ball. Much fun!
If you want to browse yourself or just want to get to that one event hit that little triangle in the north-west. Double-click the triangle to make the menu sticky...
Optimised for Chrome version 55 or higher. Apologies, but this might not work elsewhere...


Debugging
Projected Time
1.5 to 2 hours
- 12 minutes for a video walkthrough of slides
- 45 minutes for Independent Practice #1
- 30 minutes combined for Independent Practice #2 & Group Practice #1
Prerequisites
Motivation
- Debugging is the art of finding errors/bugs in programs and determining how to correct them. Things will go wrong during programming, even for experienced software engineers.
- It is ideally part of the testing process but in reality, it is done at every step of programming. Coders should debug the smallest of their modules before moving on. This decreases the number of errors thrown up during the testing phase and reduces testing time and effort significantly (reference from tutorialspoint).
Which companies use debugging? Everyone because all companies want their product to be bugs/errors free.
Objectives
Participants will be able to:
- Understand the various kinds of errors that may arise
- Use
console.log()
statements to verify logic and output at different points in the code
- Use the rubber duck technique to talk through the troublesome code
- Debug their JS code using Chrome Developer Tools
Specific Things to Learn
- Types of errors
- Good debugging strategies
- Bad debugging strategies
Materials
Lesson
General Tips for Debugging (with VS Code)
- When VS Code shows you a red squiggly underline then it’s trying to help you so I insist you pay attention to the message.
- If the red squiggly underline is under something that’s clearly correct, like
color: red;
in a CSS file, then first check if it really is correct.
- Pattern matching — It is a mechanism for checking a value against a pattern. In debugging you use pattern matching (built into VS Code) to match the syntax you write with the correct syntax which helps you to figure out errors in your code. For example, suppose you want to change the color of a text in CSS and you write
colour: blue;
then VS Code uses its pattern matching mechanism to match it against correct syntax and give you an error “check property spelling” as the correct form is color: blue;
.
- When you make a change on a file, and then visually when you refresh your page you don’t see any changes then I suggest you go through the following points:
- Check whether you saved the file.
- If you forget then I suggest you add autosave in VS Code.
- It will help you save the latest changes even if you forget.
- (How to add autosave in VS Code)
- Make a temporary, very obvious change on your HTML page.
- Such as write some text in the top of the
body
or a prominent heading then save the file and reload the browser.
- Check whether you can see the text.
- If you can’t see the new text, maybe you have the wrong file open, or the file didn’t save, or something else very strange is happening.
- Make a temporary, very obvious change to your CSS file.
- such as add
color: red;
to something extremely obvious like body
or h1
then save and reload the browser.
- Check whether the thing you expected to turn red actually turns red.
- If it doesn’t, maybe the CSS file isn’t getting loaded properly or check for syntax errors earlier in your CSS file that may render the rest of your CSS file inoperable.
- Such as :
- Are you missing a semicolon?
- Did you use
=
instead of :
accidentally?
- Are you missing a quotation mark in a font declaration, so your CSS file thinks there’s a really long string somewhere?
- Are your curly braces correctly matched and closed?
Common Mistakes / Misconceptions
“Dang it, I got a bug. Let me ask for help right away.” At Techtonica, you should spend at least 20 minutes debugging on your own before asking someone else for help. This is to give yourself the learning opportunity that happens when you struggle, and also to protect other people’s time. Once you’re in a work setting, ask your manager or teammates how long they expect you to puzzle through something on your own before asking for help.
“I don’t want anyone to know that I’m struggling with this, even if I have to waste several hours figuring this out on my own.” Most managers and colleagues expect that Junior Software Engineers will still need a lot of training and do not expect you to know everything. Learning how to ask strong questions makes you come across as competent and curious, even when you aren’t sure about how to do something.
“Getting a bug is a personal failure.” Nothing is personal with how computers execute your code. Even experienced software engineers get bugs. No one is perfect!
Independent Practice
Techtonica staff will assign pairs. In pairs, work through the Get Started with Debugging JavaScript with Chrome Dev Tools (tutorial).
On their own, each participant writes a program of their choosing using REPL.it and places at least 1 bug in it.
Group Practice
- To go with #2 from the Independent Practice: Techtonica staff will assign pairs. Try to debug the program your partner wrote in REPL.it. Swap pairs at least 2 more times so everyone has multiple opportunities to debug someone else’s code.
Supplemental Resources
- https://dzone.com - if StackOverflow & medium had a baby - basically a really well-organized library of technical resources, in-depth subject guides, ref cards/cheat sheets and more. The key is that they bring a teaching + journalistic approach which is fantastic.
- Debugging Tips and Tricks by Sarah Drasner
Check for Understanding
In a roundtable discussion format, participants share the kinds of bugs they encountered in each other’s code, how they were able to identify those bugs, and what they did to fix them.
Answer the following questions:
- What is debugging?
- What are bad strategies to implement while you are debugging your code? good?
- What is a breakpoint and what is it used for?
- Why should you tell a rubber duck about your programming problem?


Mission: Impossible A Film Review By Michael Redman Copyright 1996 By Michael Redman
** (out of ****)
Supposedly based on the television series from the late sixties and early seventies, this film directed by Brian De Palma is only barely. It does have the series title, a character's name (although certainly not the _same_ character) and some hi-tech gobligoop, but that's all that connects it to the original.
The series featured a team that pulled off a complex operation each episode that featured disguises, split-second timing and usually completed its task without anyone from the outside knowing what had happened.

The first few minutes lull the audience into a false sense of a Mission: Impossible film with a group assigned to catch the thief of a NOC list naming undercover agents. Unfortunately for the team and the film, most of them shortly meet an untimely demise including Emilio Estevez, easily the most interesting Mission member.
The only survivors are Cruise and Emmanuelle Beart ("Manon Of The Spring"), an actress of skill but in a fairly worthless role here. The spy bosses have known for some time that there was a mole on the team and since Cruise survived, decide that it is him. Cruise and Beart have to go after the bad guys while ducking the good guys. Any of this sound familiar?
The film is an action movie disguised as a mystery in the guise of Mission: Impossible. And not a very good one of any of them. The few action scenes are physically impossible although well paced. The mystery is easily solved moments after it is posed. The one remaining M:I character, Jim Phelps (Jon Voight, originally Peter Graves) has nothing in common with the original. Fans of the series will not recognize much.
Cruise's boyish appeal complete with trademarked grins doesn't play very well. Bond he ain't. Besides the disappearing and uncredited Estevez, there are only two actors with much charisma. Veteran actress Vanessa Redgrave shines in what is an unusual role in films: an extremely sexual older woman. Oddly cast, big tough-looking Ving Rhames ("Pulp Fiction") is fascinating as the kind-hearted but devious computer hacker.
Selling out even at mid-afternoon matinees, the movie has enough explosions to rake in the big bucks for Paramount and make it a summer blockbuster. If you're looking for quality though, you might want to save your money.
[This appeared in the 5/25/96 "Bloomington Voice", Bloomington, Indiana. Michael Redman can be contacted at<EMAIL_ADDRESS>--<EMAIL_ADDRESS>This week's film review at http://www.bvoice.com/ Film reviews archive at http://us.imdb.com/M/reviews_by?Michael%20Redman
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Learning Manipulation-Invariant Image Similarity for Detecting Re-Use of Images in Scientific Publications
Code (GitHub) | Paper (arXiv) | Database (DropBox)
For questions and feedback, contact Marcelo.


🎭 Arya's Art Manager 🎭
Wines Movies NPR Tiny Desks TV Shows Books GitHub ->
Means of Ascent
Robert A. Caro
The 2nd volume in Caro's series traces LBJ's
Senatorial election of 1948 against Coke Stevenson. I
think the thing that will stick with me is Caro's
description of Stevenson. The contrast of his
sincerity with Johnson's ruthlessness strikes me as
the titular battle between lofty ideals and cold
pragmatism; one in which I am deeply invested within.
Valuable lessons should be learnt from the electoral
loss (theft) of the 1948 election; and I intend to
think about them in further detail. Unrelated, but
Stevenson's building of his ranch is b a s e d.


Even as he returned to the Inner City on foot, Mat was far from certain that what he intended would actually work. It would, if what he had been told was true, but it was the truth of that he was not sure of. He avoided the oval plaza in front of the Palace, but wandered around the sides of the huge structure and its grounds, along streets that curved with the contours of the hills. The golden domes of the Palace glittered, mockingly out of reach. He had made his way almost all the way around, nearly back to the plaza, when he saw it. A steep slope thick with low flowers, rising from the street to a white wall of rough stone. Several leafy tree limbs stuck over the top of the wall, and he could see the tops of others beyond, in a garden of the Royal Palace.
A wall made to look like a cliff, he thought, and a garden on the other side. Maybe Rand was telling the truth.
A casual look both ways showed him he had the curving street to himself for the moment. He would have to hurry; the curves did not allow him to see very far; someone could come along any moment. He scrambled up the slope on all fours, careless of how his boots ripped holes in the banks of red and white blossoms. The rough stone of the wall gave plenty of fingerholds, and ridges and knobs provided toeholds even for a man in boots.
Careless of them to make it so easy, he thought as he climbed. For a moment the climbing took him back home with Rand and Perrin, to a journey they had made beyond the Sand Hills, into the edge of the Mountains of Mist. When they returned to Emond’s Field, they had all caught the fury from everyone who could lay hands on them—him worst of all; everyone assumed it had been his idea—but for three days they had climbed the cliffs, and slept under the sky, and eaten eggs filched from redcrests’ nests, and plump, gray-winged grouse fetched with an arrow, or a stone from a sling, and rabbits caught with snares, all the while laughing about how they were not afraid of the mountains’ bad luck and how they might find a treasure.  He thought it looked like an ear, even if Rand and Perrin did not, and Tam al’Thor had said it might be.
His fingers slipped out of a shallow groove, his balance shifted and he lost the toehold under his left foot. With a gasp, he barely caught hold of the top of the wall, and pulled himself up the rest of the way. For a moment he lay there, breathing hard. It would not have been that long a fall, but enough to break his head. Fool, letting my mind wander like that. Nearly killed myself on those cliffs that way. That was all a long time ago. His mother had likely thrown all those things out already, anyway. With one last look each way to make sure no one had seen him—the curving length of street below was still empty—he dropped inside the Palace grounds.
It was a large garden, with flagstoned walks through expanses of grass among the trees, and grapevines thick on arbors over the walks. And everywhere, flowers. White blossoms covering the pear trees, and white and pink dotting the apple trees. Roses in every color, and bright golden sunburst, and purple Emond’s Glory, and many he could not identify. Some he was not sure could be real. One had odd blossoms in scarlet and gold that looked almost like birds, and another seemed no different from a sunflower except that its yellow flowers were two feet and more across and stood on stalks as tall as an Ogier.
Boots crunched on flagstone, and he crouched low behind a bush against the wall as two guardsmen marched past, their long, white collars hanging over their breastplates. They never glanced his way, and he grinned to himself. Luck.
He slipped through the garden like a shadow, as if stalking rabbits, freezing by a bush or hard against a tree trunk when he heard boots. Two more pairs of soldiers strode by along the paths, the second close enough for him to have taken two steps and goosed them. As they vanished among the flowers and trees, he plucked a deep red starblaze and stuck the wavy-petaled flower in his hair with a grin. This was as much fun as stealing applecakes at Sunday, and easier.
It was not long before he found himself against the white wall of the Palace itself, and began sliding along it behind a row of flowering white roses on slatted frames, searching for a door. There were plenty of wide, arched windows just over his head, but he thought it might be a bit harder to explain being found climbing in through a window than walking down a hall. Two more soldiers appeared, and he froze; they would pass within three paces of him. He could hear voices from the window over his head, two men, just loud enough for him to make out the words.
“—on their way to Tear, Great Master.” The man sounded frightened and obsequious.
“Let them ruin his plans, if they can.” This voice was deeper and stronger, a man used to command. “It will serve him right if three untrained girls can foil him.  Is there any word of the boy?  He has vanished. But, Great Master, one of the girls is Morgase’s nit.”
Mat half turned, then caught himself. The soldiers were coming closer; they did not appear to have seen his start through the thickly woven rose stems. Move, you fools!  He had lost some of the conversation.
“—has been far too impatient since regaining his freedom,” the deep voice was saying. “He never realized the best plans take time to mature. He wants the world in a day, and Callandor besides. The Great Lord take him! He may seize the girl and try to make some use of her. And that might strain my own plans.”
“As you say, Great Master. Shall I order her brought out of Tear?”
“No. The fool would take it as a move against him, if he knew. And who can say what he chooses to watch aside from the sword? See that she dies quietly, Comar. Let her death attract no notice at all.” His laughter was a rich rumble.  This may all be just as well. Let it be done quickly. Quickly, before he has time to take her himself.”
The two soldiers were almost abreast of him; Mat tried to will their feet to move faster.
“Great Master,” the other man said uncertainly, “that may be difficult. We know she is on her way to Tear, but the vessel she traveled on was found at Aringill, and all three of them had left it earlier. We do not know whether she has taken another ship, or is riding south. And it may not be easy to find her once she reaches Tear, Great Master. Perhaps if you—”
“Are there none but fools in the world, now?” the deep voice said harshly. “Do you think I could move in Tear without him knowing? I do not mean to fight him, not now, not yet. Bring me the girl’s head, Comar. Bring me all three heads, or you will pray for me to take yours!”
“Yes, Great Master. It shall be as you say. Yes. Yes.”
The soldiers crunched past, never looking to either side. Mat only waited for their backs to pass before leaping up to catch the broad stone windowsill and pull himself high enough to see through the window.
He barely noticed the fringed Tarabon carpet on the floor, worth a fat purse of silver. One of the broad, carved doors was swinging shut. A tall man, with wide shoulders and a deep chest straining the green silk of his silver-embroidered coat, was staring at the door with dark blue eyes.  All in all, he looked a hard man, and one used to giving orders.
“Yes, Great Master,” he said suddenly, and Mat almost lost his grip on the sill. He had thought this must be the man with the deep voice, but it was the cringing voice he heard. Not cringing now, but still the same. “It shall be as you say, Great Master,” the man said bitterly. “I will cut the three wenches’ heads off myself. As soon as I can find them!” He strode through the door, and Mat let himself back down.
For a moment he crouched there behind the rose frames. Someone in the Palace wanted Elayne dead, and had thrown in Egwene and Nynaeve as afterthoughts. What under the Light are they doing, going to Tear? It had to be them.
He pulled the Daughter-Heir’s letter out of the lining of his coat and frowned at it. Maybe, with this in his hand, Morgase would believe him. He could describe one of the men. But the time for skulking was past; the big fellow could be off to Tear before he even found Morgase, and whatever she did then, there was no guarantee it could stop him.
Taking a deep breath, Mat wiggled between two of the rose frames at the cost of only a few pricks and snags from the thorns, and started down the flagstone path after the soldiers. He held Elayne’s letter out in front of him so the golden lily seal was plainly visible, and went over in his mind exactly what he meant to say. When he had been sneaking about, guardsmen kept popping up like mushrooms after rain, but now he walked almost the length of the garden without seeing even one. He passed several doors. It would not be so good to enter the Palace without permission—the Guards might do nasty things first and listen after—but he was beginning to think about going through a door when it opened and a helmetless young officer with one golden knot on his shoulder strode out.
The man’s hand immediately went to his sword hilt, and he had a foot of steel bared before Mat could push the letter toward him. “Elayne, the Daughter-Heir, sends this letter to her mother, Queen Morgase, Captain.” He held the letter so the lily seal was prominent.
The officer’s dark eyes flickered to either side, as if searching for other people, without really ever leaving Mat. “How did you come into this garden?” He did not draw his sword further, but he did not sheath it, either. “Elber is on the main gates.  Mat cursed his tongue, but the officer gave a sharp nod; he almost smiled, too, but it did not seem to lessen his vigilance, or his suspicion. “He grew angry when he learned I had come from Tar Valon, and he wouldn’t even give me a chance to show the letter or mention the Daughter-Heir’s name. He said he would arrest me if I did not go, so I climbed the wall. I promised I would deliver this to Queen Morgase herself, you see, Captain. I promised it, and I always keep my promises.  “It should be built three times so high.” He eyed Mat. “Guardsman-lieutenant, not captain. I am Guardsman-lieutenant Tallanvor. I recognize the Daughter-Heir’s seal.” His sword finally slid all the way back into the sheath. He stretched out a hand; not his sword hand. “Give me the letter, and I will take it to the Queen. After I show you out. Some would not be so gentle at finding you walking about loose.”
“I promised to put it in her hands myself,” Mat said. Light, I never thought they might not let me give it to her. “I did promise. To the Daughter-Heir.”
Mat hardly realized Tallanvor’s hand was moving before the officer’s sword was resting against his neck. “I will take you to the Queen, countryman,” Tallanvor said softly. “But know that I can take your head before you blink if you so much as think of harming her.”
Mat put on his best grin. That slightly curved blade felt sharp on the side of his neck. “I am a loyal Andorman,” he said, “and a faithful subject of the Queen, the Light illumine her. Why, if I had been here during the winter, I’d have followed Lord Gaebril for sure.”
Tallanvor gave him a tight-mouthed stare, then finally took his sword away. Mat swallowed and stopped himself from touching his throat to see if he had been cut.
“Take the flower out of your hair,” Tallanvor said as he sheathed his blade. “Do you think you came here courting?”
Mat snatched the starblaze blossom out of his hair and followed the officer. Bloody fool, putting a flower in my hair. I have to stop playing the fool, now.
It was not so much following, really, for Tallanvor kept an eye on him even while he led the way. The result was an odd sort of procession, with the officer to one side of him and ahead, but half turned in case Mat tried anything. For his part, Mat attempted to look as innocent as a babe splashing in his bathwater.
The colorful tapestries on the walls had earned their weavers silver, and so had the rugs on the white tile floors, even here in the halls. Gold and silver stood everywhere, plates and platters, bowls and cups, on chests and low cabinets of polished wood, as fine as anything he had seen in the Tower. Servants darted everywhere, in red livery with white collars and cuffs and the White Lion of Andor on their breasts. He found himself wondering if Morgase played at dice. Wool-headed thought. Queens don’t toss dice.  He indulged himself in a small fancy of being made a lord; surely the man who revealed a plot to murder the Daughter-Heir could expect some such reward.
Tallanvor led him down so many corridors and across so many courtyards that he was beginning to wonder if he could find his way out again without help, when suddenly one of the courts had more than servants in it. A columned walk surrounded the court, with a round pool in the middle with white and yellow fish swimming beneath lilypads and floating white waterlilies. Men in colorful coats embroidered in gold or silver, women with wide dresses worked even more elaborately, stood attendance on a woman with red-gold hair who sat on the raised rim of the pool, trailing her fingers in the water and staring sadly at the fish that rose to her fingertips in hopes of food. A Great Serpent ring encircled the third finger of her left hand. A tall, dark man stood at her shoulder, the red silk of his coat almost hidden by the gold leaves and scrolls worked on it, but it was the woman who held Mat’s eye.
He did not need the wreath of finely made golden roses in her hair, or the stole hanging over her dress of white slashed with red, the red length of the stole embroidered with the Lions of Andor, to know he was looking at Morgase, by the Grace of the Light, Queen of Andor, Defender of the Realm, Protector of the People, High Seat of House Trakand. She had Elayne’s face and beauty, but it was what Elayne would have when she had ripened. Every other woman in the courtyard faded into the background by her very presence.
I’d dance a jig with her, and steal a kiss in the moonlight, too, no matter how old she is. He shook himself. Remember exactly who she is!
Tallanvor went to one knee, a fist pressed to the white stone of the courtyard. “My Queen, I bring a messenger who bears a letter from the Lady Elayne.”
Mat eyed the man’s posture, then contented himself with a deep bow.  He held out the letter as he bowed, so the golden yellow wax of the seal was visible. Once she reads it, and knows Elayne is all right, I will tell her. Morgase turned her deep blue eyes on him. Light! As soon as she’s in a good mood.
“You bring a letter from my scapegrace child?” Her voice was cold, but with an edge that spoke of heat ready to rise. “That must mean she is alive, at least! Where is she?”
“In Tar Valon, my Queen,” he managed to get out. Light, wouldn’t I like to see a staring match between her and the Amyrlin. On second thought, he decided he would rather not. “At least, she was when I left.”
Morgase waved a hand impatiently, and Tallanvor rose to take the letter from Mat and hand it to her. For a moment she frowned at the lily seal, then broke it with a sharp twist of her wrists. She murmured to herself as she read, shaking her head at every other line. “She can say no more, can she?” she muttered. “We shall see whether she holds to that . . . ” Abruptly her face brightened. “Gaebril, she has been raised to the Accepted. Less than a year in the Tower, and raised already.” The smile went as suddenly as it had come, and her mouth tightened. “When I put my hands on the wretched child, she will wish she were still a novice.”
Light, Mat thought, will nothing put her in a good mood? He decided he was just going to have to say it out, but he wished she did not look as if she meant to cut someone’s head off. “My Queen, by chance I overheard—”
“Be silent, boy,” the dark man in the gold-encrusted coat said calmly. He was a handsome man, almost as good-looking as Galad and nearly as youthful-seeming, despite the white streaking his temples, but built on a bigger scale, with more than Rand’s height and very nearly Perrin’s shoulders. “We will hear what you have to say in a moment.” He reached over Morgase’s shoulder and plucked the letter out of her hand. Her glare turned on him—Mat could see her temper heating—but the dark man laid a strong hand on her shoulder, never taking his eyes off what he was reading, and Morgase’s anger melted. “It seems she has left the Tower again,” he said. “On the service of the Amyrlin Seat. The woman oversteps herself again, Morgase.”
Mat had no trouble holding his tongue. Luck. It was stuck to the roof of his mouth. Sometimes I don’t know if it’s good or bad. The dark man was the owner of the deep voice, the “Great Master” who wanted Elayne’s head. She called him Gaebril. Her advisor wants to murder Elayne? Light! And Morgase was staring up at him like an adoring dog with her master’s hand on her shoulder.
 The man had a forceful gaze, and a look of knowing. “What can you tell us of this, boy?”
“Nothing . . . uh . . . my Lord.” Mat cleared his throat; the man’s stare was worse than the Amyrlin’s. “I went to Tar Valon to see my sister. She’s a novice. Else Grinwell. I’m Thom Grinwell, my Lord. The Lady Elayne learned I was meaning to see Caemlyn on my way back home—I’m from Comfrey, my Lord; a little village north of Baerlon; I’d never seen any place bigger than Baerlon before I went to Tar Valon—and she—the Lady Elayne, I mean—gave me that letter to bring.” He thought Morgase had glanced at him when he said he came from north of Baerlon, but he knew there was a village called Comfrey there; he remembered hearing it mentioned.
Gaebril nodded, but he said, “Do you know where Elayne was going, boy? Or on what business? Speak the truth, and you have nothing to fear. Lie, and you will be put to the question.”
Mat did not have to pretend a worried frown. “My Lord, I only saw the Daughter-Heir the once. She gave me the letter—and a gold mark!—and told me to bring it to the Queen. I know no more of what is in it than I’ve heard here.” Gaebril appeared to consider it, with no sign on that dark face of whether he believed a word or not.
“No, Gaebril,” Morgase said suddenly. “Too many have been put to the question. I can see the need as you have shown it to me, but not for this. Not a boy who only brought a letter whose contents he does not know.”
“As my Queen commands, so shall it be,” the dark man said. The tone was respectful, but he touched her cheek in a way that made color come to her face and her lips part as if she expected a kiss.
Morgase drew an unsteady breath. “Tell me, Thom Grinwell, did my daughter look well when you saw her?”
“Yes, my Queen. She smiled, and laughed, and showed a saucy tongue—I mean . . . ”
Morgase laughed softly at the look on his face. “Do not be afraid, young man. Elayne does have a saucy tongue, far too often for her own good. I am happy she is well.” Those blue eyes studied him deeply. “A young man who has left his small village often finds it difficult to return to it. I think you will travel far before you see Comfrey again. Perhaps you will even return to Tar Valon. If you do, and if you see my daughter, tell her that what is said in anger is often repented. I will not remove her from the White Tower before time. Tell her that I often think of my own time there, and miss the quiet talks with Sheriam in her study. Tell her that I said that, Thom Grinwell.”
Mat shrugged uncomfortably. “Yes, my Queen. But . . . uh . . . I do not mean to go to Tar Valon again. Once in any man’s life is enough. My da needs me to help work the farm. My sisters will be stuck with the milking, with me gone.”
Gaebril laughed, a deep rumble of amusement. “Are you anxious then to milk cows, boy? Perhaps you should see something of the world before it changes. Here!” He produced a purse and tossed it; Mat felt coins through the wash-leather when he caught it. “If Elayne can give you a gold mark for carrying her letter, I will give you ten for bringing it safely.  Mat lifted the purse and managed a weak grin. “Thank you, my Lord.”
But the dark man had already waved him away and turned to Morgase with his fists on his hips. “I think the time has come, Morgase, to lance that festering sore on the border of Andor. By your marriage to Taringail Damodred, you have a claim to the Sun Throne. The Queen’s Guards can make that claim as strong as any. Perhaps I can even aid them, in some small way. Hear me.”
Tallanvor touched Mat on the arm, and they backed away, bowing. Mat did not think anyone noticed. Gaebril was still speaking, and every lord and lady seemed to hang on his words. Morgase was frowning as she listened, yet she nodded as much as any other.


OKC Central Live Chat recap: Streetcars waive fares for next 7 weekends
by Steve LackmeyerThe Oklahoman's Steve Lackmeyer fielded questions from readers during this week's OKC Central Live Chat. You can join Steve most Fridays at 9:30 a.m. to add your questions and comments about ongoing developments around Oklahoma City.
Below is an unedited transcript of today's discussion.
I’m excited for the free streetcar weekend starting today through the end of the year. How is this being funded? Any talk about making this permanent? Would a corporate sponsor with naming rights be a possibility, has this been considered?
The OKC Streetcar is offering free weekend rides (Fri., Sat., Sun.) from Nov. 22-Jan. 5 as part of its participation in the Downtown In December program and a way to support the businesses and destinations along the loops. EMBARK is working with Houck Transit Advertising to secure sponsorships to support the ongoing operation of the Streetcar. Currently there are 20 platform sponsors. An overall naming-rights sponsor is an option that is being pursued. EMBARK’s Board of Trustees sets fares. Permanent free transit services would be a policy change and would include dialogue between EMBARK’s Board of Trustees, City Hall, and City Council.
Any idea when the Streetcar stops will be completed? They all have the temporary yellow construction netting where vertical rails should be. They've been an eyesore since the Streetcar opened a year ago.
According to Michael Scroggins with EMBARK, the MAPS office just reported that the contract would go before Council in December. Work should start in early February and wrap-up by early June.
Do you know how much, if any, success Leadership Square has had in leasing the space previously occupied by Enable?
Mark Beffort, co-owner, reports one of the six floors previously leased by Enable has been leased with deals working for another three of those floors. The rest of Leadership Square is fully leased.
Built in 1984, Leadership Square is still one of downtown's most desirable (if not the most desirable) properties thanks to its design, public space and amenities, and ongoing investment in keeping the building up to Class A standards.
Is Devon currently paying a lease to the BOK Park Plaza building? I recall they had originally intended to occupy space but don't know if they signed a lease and are currently trying to sublet or not.
That's the big question. They did a deal when they were growing at a rapid pace to lease 250,000 square feet of the tower — space they've never occupied as the industry changed and the workforce was reduced through a series of layoffs.
I've asked previously whether BOK leased space from the building owner, Hines, or whether the company leased part of the Devon space. I never got an answer. I suspect BOK leased from Hines as that deal was part of the overall plan for building the tower.
Whats next in the Plaza District?
Jeff and Aimee Struble are converting a duplex into an Air BnB and their social media has posted that their restaurant, Aurora, is about to reopen.
Hypothetically, if MAPS 4 doesn't get passed, what steps can the council take to reintroduce these projects? Is the 1 cent sales tax still the best option for doing these large capital projects?
If MAPS 4 fails, I suspect that will be the end of the MAPS brand. You would have trouble getting a campaign funded for just the social service issues, and some of the other issues would struggle as well.
There has been a lot more activity happening in the Ironworks area (west of Western, south of Linwood Blvd.) What do you foresee happening in this area?
We're first going to see a split in the naming of this area, with the east half ending up as the "Sunshine District" while the west part will remain known as the 'Ironworks District."
I find it a bit crazy, but also reflective of the area's momentum, that such a split on branding is already occurring for this area that only a few years ago was considered a long ways off before being viable.
Go figure.
I also believe what happens next with the old Nuway Laundry complex at NW 6 and Western will give us a big indicator of how quickly this area is set to develop.
The function of Starbucks on 23rd Street = Good. The design of Stabucks on 23rd Street = Bad. I urge the developer to rethink their drive thru layout.
The developer, Ryan McNeill, has included several site layouts he looked at before coming to the one being proposed.
I spoke to Ryan, and he's indicating he will be visiting with neighbors and taking community feedback into consideration before moving forward.
Now is the time for all concerned to look at the site and suggest ideas on how to make this property less suburban in design. It does seem to have a lot of parking. I suspect the answer lies in reconciling the location of the drive-thru lane with the opportunity to create an extended street-front patio extending the built presence facing NW 23.
Related Photos


Welcome to the game! Repeat back the pattern by pressing buttons. Beat all 8 levels before the time bar is full! Be careful - You only get 3 mistakes.


About Us
The Internet of Things(IOT) was a concept that physical objects are seamlessly integrated into the information network. SenseBox is founded to make the Internet of Things an order of magnitude easier to develop and use. SenseBox, included a cloud platform called SenseCloud and a physical interface called SenseHub, is a service for users, developers and companies are connecting devices and apps to securely store and easily exchange sensor-derived data to the web through API.
Vision
The team of SenseBox believes that Internet of Things is the next evolution of the Internet. The Internet of Things as well as many portable sensors from open hardwares become more popular and important in this post-PC era. There are a lot of sensory data from many portable sensors and smart phones. SenseBox is committed in making the storage and process of those data easily and securely. Last but not least, the team of SenseBox also think the big data is also future of the internet. Through analysis and use of the big data as well as crowdsourcing application developments, we could improve our life with the help of internet of things .
Features
The services of SenseBox has following features:
- Threshold triggered mechanism on SenseCloud
- Data management according to geolocation and time
- Open data and Collaboration
- Code-less deployment and developer friendly
- Two-way data transfer and control function
- Social network Integration
- Hackable hardware friendly platform


MadEvent Card for u d > u d a a / h
Created:
Unknown
Process:
u d > u d a a / h
QCD=99
QED=99
NP=0
Model:
EWdim6-full
Links
Status
Process Information
Generation Complete
Code Download
Available
On-line Event Generation
Only available from the web
Results and Event Database
No runs available
Notes:
Last Update:
Sun Mar 31 23:29:59 UTC 2019


Cross River automated cocoa processing factory ready for commissioning
by Temisan AmoyeBy Emma Una, Calabar
Cross River Cocoa Processing Factory located in Ikom is scheduled to begin a test run early next year following ninety-five percent work completion by the contracting firm A A Universal
This was disclosed by the Permanent Secretary, Ministry of Agriculture, Pastor Godsgift Ugbe who undertook an inspection visit to the factory on Wednesday
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He processes are being put in place including the procurement and testing of the cocoa beans for test running to take place which will herald the subsequent commissioning of the factory.
The Permanent Secretary said the factory which is the biggest in the subregion will process ten tons of cocoa per hour and add value to the crop to make it meet international standard.
“Prior to this, cocoa which has been a cash crop has not attained the maximum value in this environment to both the framers and marketers participating in the cultivation and sale of the crop that is the reason the state government thought it wise to establish this factory which will go a long way in improving the value per each yield”.
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Ugbe said the state produces enough cocoa to feed the factory for steady maximum processing of cocoa into quality chocolate bars, beverages, and alcoholic items.
” There is enough cocoa in the state as both the central and northern parts of the state produces the crop and there are many government-owned cocoa estates which churn out huge volumes of cocoa annually to feed the factory “.
He said plans are afoot by the requisite ministries to begin the recruitment of necessary staff to handle both the factory and administrative work at the factory.


The author of this site could never have done all of this without help from the internet. This page lists some of the contributors that have made this all possible.
Sotirios Keros: a physician, financial planner, and co-founder of the not-for-profit Doctored Money. Sotirios contributed heavily to the design and correctness of the calculations this tool makes.
Steve Nicolai: a semi-retired telecom software engineer. Steve contributed the implementation of social security credits.
If you would like to contribute, the project is on github at: Gregable/social-security-tools . Please file issues in the Issue Tracker .


The multi sports fitness trend is based on an impulse-response model by
Dr. Eric W. Banister
in 1975 and
Andrew R. Coggan later. The following reference has been used:
Modeling Human
Performance, fellrnr.com.
Since strava only provides fitness, fatigue, form for cycling. Here you will be able to view your
fitness trend using all activities where you held a heart rate monitor. It's an improved feature which
where missing, not a duplicate!

Please read
Frequently Asked Questions
Beta feature:
Report Bug
Multi sports fitness trend is calculated from your various heart rate stress. A heart rate stress is
represented by an value called
TRaining IMPulse or
TRIMP.
Training Impulse concept has been developed by Dr. Eric W. Banister. Basically, it represents the amount
of
heart stress
during an activity: the longer you go at full
throttle during an activity, the more
TRIMP of activity goes up!
Show me TRIMP
maths...
Where
(For Mens) or
(For Womens)
And
HRR = Heart Rate Reserve = Heart
effort level according to heart capacity defined by
TRIMP has both a positive and a negative effect. The positive effect is called fitness,
and the negative
effect is called fatigue. Fitness and fatigue can combined to provide a value
of
form or Performance.
(Are you a cyclist?)If you own a power meter and you activated the cycling power meter option in
the feature, then the "Power Stress
Score (PSS)" will be used instead of TRIMP on cycling activities. "Power Stress Score" is used in
computation only if available.
Show me "Power Stress
Score" maths...
(Are you a swimmer?)
A "Swimming Stress Score" (Swim SS) can be computed for each of your swim activities if your "Swimming Functional Threshold Pace" (Swim FTP) has been entered inside athlete settings and you enabled swimming stress score option.
No heart rate monitor is required. Even a swimming manual activity will be handled by the system.
Learn more from TrainingPeaks.
Note: Strava do not support HR data for swimming activities at the moment (on march 2017). In the case where you have HRM while swimming and strava finally support HR data then TRIMP value will be used instead of Swim SS.
Show me "Swimming Stress
Score" maths...
The Fitness, Fatigue and Form graph and table is based off an impulse-response model first developed
by Dr. Eric W. Banister in 1975.
It was later redefined by
Andrew R. Coggan.
This model will show you:
- Your Fitness based on your chronic load
- Your Fatigue based on your acute load
- Your Form or stress balance
Explanations...
-
The Fitness curve is the long-term average daily training
load.
Default period is fixed to 42 days (or six weeks), so it will take ~6 weeks for your
Fitness
to be accurate. It's basically the foundations, the potential availability of the
athlete... You can't get into big rides/runs or races without a minimum of fitness acquired. If
that curve is too
regular or too flat, it is not usually a sign of good training.
-
The Fatigue curve is the short-term average daily training
load.
Same way than Fitness but
default period is fixed to 7 days (one week). Conceptually, fatigue is easy to understand: It's
the
tired feelings which limits your performance. This curve varies much faster than Fitness
curve. On Fatigue
curve, you can see the fatigue climbing sharply in response where you performed workouts with a
high
stress. But also go down quickly as you take few days off.
-
The Form curve is simply the difference between Fitness and
Fatigue, it's the right balance of stress you should look at to avoid over training for
example.
Form = Fitness - Fatigue
When:
- +25 < Form : Transition zone. Athlete is on form. Case where athlete has an
extended break. (e.g. illness, injury or end of the season).
- +5 < Form < +25 : Freshness Zone. Athlete is on form. Ready for a race.
- -10 < Form < +5 : Neutral Zone. Zone reached typically when athlete is in a rest
or recovery week. After a race or hard training period.
- -30 < Form < -10 : Optimal Training Zone.
- Form < -30 : Over Load Zone. Athlete is on overload or over-training phase. They
should take a rest!
Read more from joefrielsblog.com.
Be fit doesn't mean you are ready to race at your higher level. A negative Form would
reveal that you are carrying fatigue and are not on form. By resting you can
remove fatigue faster than you lose fitness and come into form for your race day (or punish
friend day... ;))!


Exploring vagueness: the underlying theses in artificial intelligence
How close can we get to a goal that can’t be precisely described? This idea may seem odd at first, but many of the concepts we daily think of cannot be defined accurately. Being like so, how can one ensure to have actually achieved such a goal?
Consider an individual looking to get healthier. At first thought, his conception of well-being is likely a poorly defined notion instead of a thorough combination of bodily measurements, such as blood pressure or respiratory capacity. Even if it was, he would come to realize that health cannot be completely outlined by these, as they overlook other aspects of health, such as mental sanity.
The broader a concept seems, the harder it is to come up with a comprehensive definition for it, let alone ways to measure it. Still, this all may come across as far too overcritical, since we rarely mull over such problems in our daily lives. In practice, we avoid these dilemmas projecting our goal onto a concrete achievement or feature that could be indicative of this same objective. In our example, perhaps getting healthier may come as a consequence of eating vegetables every day, getting 8 hours of sleep, or even running that half-marathon at the end of the year.
In the scientific community, however, precise definitions matter. Furthermore, if we venture ourselves in this task collectively, how can we ensure that our notions and expectations converge? In these vague circumstances, reaching common ground is not only pragmatic but crucial. With a layer of optimism, the hope is to perpetually refine these agreed-upon goals and definitions under the scientific method, even though we may not be yet qualified to properly define this.
As in many other fields, there seems to be a taxonomical gray area within artificial intelligence. This and some of its associated terms have lost their original meaning due to the rapid wear and tear in light of the breakthroughs in deep learning over the past decade, and the inflated expectations that have followed. Professor Michael Jordan goes as far as arguing that these recent advancements are not considered part of artificial intelligence anymore. Jordan claims that current machine learning and deep learning are more focused on an engineering aspect instead of pursuing the original goal of AI.
The field of artificial intelligence has evolved from isolated research streams, including the early blueprints where current neural network models originated from (Buchanan (2005)). The term Artificial Intelligence (AI) was famously coined by John McCarthy for the Dartmouth convention, a two-month workshop dedicated to discussing crucial questions on this then-emerging-yet-to-be-defined field (McCarthy et. al (1955)). The name was chosen by McCarthy as a way to accommodate and conciliate these research angles around the theme at the time.
According to McCarthy, Artificial Intelligence is the science and engineering of making intelligent machines, especially intelligent computer programs. By investigating and precisely describing the features of intelligence, McCarthy believed that these could be then replicated by machines. This perspective, however, leads us to a tricky debate: what constitutes intelligence?
Intelligence
Intelligence is such a far-reaching concept that its definition remains unsettled. In 1921, in an attempt to technically outline it, the Journal of Educational Psychology asked fourteen experts on the field to present their definitions of intelligence. As expected, there were fourteen distinct definitions. As one theorist on intelligence, R. Sternberg, points out: “there seem to be almost as many definitions of intelligence as there were experts asked to define it” (Legg and Hunter (2006)).
Having learned or ability to learn to adjust oneself to the environment
(S. S. Colvin)
The capacity to learn or to profit by experience
(W. F. Dearborn)
Some definitions extracted from the Journal of Educational Psychology (Pfeifer and Scheier (1999))
Intelligence is a descriptive term, hence it assigns a certain set of characteristics to a group or individual. So being, it is fairly unlikely to accommodate multiple angles into a single definition. To some, intelligence is in the collective behavior demonstrated by colonies of bees and ants; to others in particular aspects of human intelligence, such as creativity, the ability to speak, or even on how some intelligent features could be artificially recreated.
Nevertheless, this ambivalence didn’t restrain researchers from claiming progress in AI. For decades, the game of chess was considered the pinnacle of the human intellect. Building a machine that could defeat world-class contenders was in the scope of engineers and scientists as to prove that intelligent machines could be built. In 1997, IBM organized a historic rematch between the world chess champion Garry Kasparov and the supercomputer named Deep Blue over a six-game match. In the previous year, Kasparov defeated Deep Blue, winning four out of six games. However, in the following encounter, the system had an unprecedented victory, landing two wins and three draws. This was a symbolic event, showcasing several advances that enabled a system to beat the greatest chess player of all time.
Kasparov against Deep Blue, 1997
However, a large part of the academic community remained skeptical, portraying the victory as the result of a dumb system with amazing processing speed in contrast with Kasparov’s far greater intellect. This was partially true. The system developed by IBM had several chess strategies stored, built upon consulting chess masters multiple times. This allowed the system to cut corners when searching for the right move. Yet, this search was only made possible by the Deep Blue’s remarkable capacity to explore up to 200 million positions per second (Press (2018)).
As many critics claim that such a system was unintelligent, they wrongfully make of this concept a dichotomy: either you have intelligence or not. But intelligence is more of a spectrum than a predicate. This becomes more noticeable when we introduce a reference: are rats intelligent? Of course not as much as humans, but definitely more than ants. Despite using it qualitatively, when we say a person is intelligent, we normally mean that this individual has an above-average level of intelligence.
As we can observe, there’s little hope of an agreement over an all-inclusive terminology. Nevertheless, almost all definitions of intelligence seem to share a common factor: to exploit the ruling conditions and explore better alternatives. These two processes can be perceived as the ability to actively adapt, either to a ruling or emerging pattern, while preserving a certain structure, what Ashby (1960) refers to as maintaining homeostasis.
Many of the modern techniques we use today within artificial intelligence, and in particular machine learning, make use of algorithms that modify parameters and adapt to the desired task. But even decades before the Dartmouth convention, some fields already attempted to understand and emulate intelligence using adaptable systems. One field, in particular, named connectionism consisted of representing mental phenomena throughout emerging patterns in the brain. This is the cornerstone in which modern neural networks are based on.
Theories of mind and artificial intelligence
The research streams around artificial intelligence generally involved much more than attempting to engineer intelligent systems. These encompassed not only computer science but cognitive psychology, neuroscience, and philosophy.
For centuries, thinkers were interested in understanding the relationship between mind and body. Humans are remarkably aware of the manifestations in our minds. With constructs such as beliefs, desires, actions, emotions, and so forth, we are capable of not describing our mental states, but to attribute these to other individuals. Do these mental states have physical manifestations as well? This question is famously known as the Mind-body problem and the theories around this topic are gathered in the field of philosophy of mind.
Despite modern evidence suggesting the connection between brain and mind, this question remained fairly open up until the last centuries. With modern scientific advancements, this problem began to involve much more than philosophy. From these interactions, the field cognitive science emerged, focused on investigating the mind and its processes.
Cognitive science had a crucial role in the development of AI, from which two major branches unfolded: connectionism and symbolicism. Despite not being mutually exclusive, these two approaches practically formed a feud in artificial intelligence. Nevertheless, both seem to be rooted in the same theory of functionalism.
In philosophy of mind, one of the predominant theories of the last century titled identity of thought interpreted each mental state as a manifestation of a specific event in the brain. Hence, these biological activities were seen as the connection between the mind and the physical domain. This view implied that either a mental state is unique, or, for this to be experienced by others, these must have an identical organic structure.
As this view seemed too tight and unrealistic, the functionalist theory offered an alternative: instead of tying each mental state to a biological counterpart, it proposed identifying these by their corresponding functions (Piccini (2004)). If a mental state such as fear could be defined as producing concern for harm and the desire to either fight or flight an enemy. It does not matter if this is achieved through biological elements, as long as it produces the desired effect (Carneades.org (2016)).
What implications of functionalism brought to AI? This perspective entails the following: intelligent behavior does not need to be carried out in the exact structure as we have in our brains. As long as the same results are attained, we can achieve the level of intelligence desired using a surrogate model. Hence, in theory, intelligence can be achieved at the algorithmic level using machines.
Symbolicism
Although functionalism implies that intelligence may be attained apart from biological structures, a clear proxy to this task is understanding how we humans think. Thought can be understood in many forms, fluctuating in a biological to philosophical scale. In the most abstract state, we see thought as the interaction between concepts. And according to the language of thought hypothesis, these relationships follow a syntax, just like language.
In symbolicism, this syntax is described according to laws of thought, a set of axioms dating back to Aristotle. Many centuries later, this syntax was revisited by Leibniz, who was fixated into formalizing these ideas in mathematical terms. By doing so, he believed that we could evaluate the trueness in statements in the same way we perform calculations, by verifying if these were mathematically sound. The building blocks laid by Leibniz are known today as the algebra of concepts (Zalta (2000)).
The formulation of symbols in Symbolicism can be traced back to the Leibnizian notion of a concept. A concept is an abstract body that encompasses all the properties necessarily implied by an object. For instance, the concept of an apple encodes the characteristic of being a fruit that grows on trees.
(apple
(isa fruit),
(color red); (color green),
(origin tree)
);
Symbolic representation of an apple
Apples have attributes and relationships, some distinct and others unchangeable: apples can be red or green, but all of them are fruits. These characteristics are best expressed by a configuration proposed by Kant called schemas, which allows us to classify different symbols and make inferences based on their features. For instance, we can logically differentiate beets from apples based on their different schemas: despite possibly having the same color, apples are fruits that grow on trees as beets are vegetables that grow in soil.
The ideas of Leibniz were later rediscovered by George Boole in the 19th century and were a centerpiece for computer logic (Peckhaus (2018)). The computational models that unfolded that century placed Symbolicism, also known as classical AI or GOFAI (Good Old-Fashioned Artificial Intelligence), as the ruling paradigm artificial intelligence for more than 40 years. According to the physical symbol system hypothesis formulated by Newell and Simon, symbolic AI provided sufficient conditions for achieving a “general intelligent system”1.
1 For this and other contributions, the authors have received a Turing award in 1975. However, this hypothesis is widely contested, for several reasons, not to mention the vagueness in the definition of intelligence. The authors even later recognized that it may not hold. For a more thorough investigation, see Nilsson (2007)
Reasoning is an important feature of intelligence and thus has always been of great interest in the AI community. Symbolicism has shared great success in these tasks. For instance, one well-celebrated type of implementation called Expert System assembles knowledge of a particular subject, making specialized logical inferences. Upon analyzing an incoming patient with fever, a medical expert system could determine that the patient has some sort of infection, and, based on additional symptoms and logical rules, assert by what type of disease the patient might be afflicted.
As in medicine and other risky applications, symbolic systems offered a great advantage. Not only they could automate some of the jobs, but since readable symbols were used throughout the whole solving procedure, these could be easily inspected by human experts for a second opinion. But what would happen if our input was not symbolic? This was where things started to break down.
Interacting with data extracted from the real world and not some enclosed model was a great challenge for symbolic systems. Let us consider the task of identifying a position in space using cameras. This task was part of a project named Shakey, a collective endeavor conducted by 13 researchers at Stanford, aimed to combine several modules in artificial intelligence into a single robot. The input consisted of a large collection of pixels for a particular instant in time. Based on certain mapped patterns across an enclosed space, Shakey ought to recognize its location within the environment.
Example of the process flow from input to the high-level representation. (Stanford (1972))
Once the camera captures a region of interest, it conducts a series of preprocessing states to extract the relevant features (in this case the lines of the image). Then, this intermediate representation is compared to each pattern in the system’s internal collection that maps a particular landmark, like a corner of a room as the figure demonstrates (Rosen and Nilsson (1967)).
Although having a good performance in controlled environments, such as in Shakey, this technique is unsuited for practical applications. Real-world settings are not only prone to noisy recordings but, many of these require immediate feedback. In contrast, the techniques used to transform the high dimensional input into symbolic representations were not only computationally demanding but difficult to parallelize, as showcased by Shakey’s “excruciating slow operation” (Copeland (2020)). What’s more, these inference systems were not robust enough against noisy data. To make matters worse, the deal-breaker for symbolic AI was the inability to learn based on observations. During the late past century, learning became a central piece of intelligence, as a self-correcting mechanism. And without any human intervention, these systems could not improve their actions.
Symbolicism is still widely used today. So much so, that in search problems, where multiple configurations must be evaluated (e.g. in chess), the symbolic paradigm offers a clear advantage over sub-symbolic representations. On the other hand, in recently popularized applications, such as natural language processing and computer vision, distributed representations make connectionism much more suited for handling multi-dimensional inputs and computing in parallel.
Perhaps the motive of dispute between connectionists and symbolists is rooted in placing points of view as opposite sides of a spectrum. In symbolic AI, we have rich, symbolic concepts that are naturally coherent to humans. Alternatively, connectionism makes use of small fragments of information, that only when combined compose an intelligible concept. Symbolicism typically works with binary data and hard, logical constraints as connectionism deals with continuous numbers and soft, probabilistic constraints.
However, as we hover over details, these differences become blurrier. Not only there are systems on both sides that don’t fully comply with these definitions. But at the implementation level, symbols and schemas can also be seen as distributed representations, constituted of streams of binary values. At the same time, the probabilistic operations within connectionism are a mere product of pseudo-random number generators, a product of logical, deterministic devices. Even the first conception of a connectionist model on a computer, the McCulloch-Pitts neuron - more alike symbolic systems - was used to solve propositional logic.
Despite these imprecise distinctions, the connectionism paradigm received a lot of pushback during the second half of the twentieth century. But as a consequence of all symbolic shortcomings, the paradigm of sub-symbolic artificial intelligence swooped into popularity, bolstered by the wave of recent successes in connectionism.
Connectionism
Connectionist models are built on interconnected units, called neurons, which can be assembled in various arrangements, composing the so-called neural networks. Depending on the incoming stimuli, these neurons dispatch values or not, thus creating a representation based on the overall firing pattern.
Toy illustration of a distributed representation of apples, beets and their corresponding features, showcased by the connections between each node
For instance, the representation of apples could indicate the activation of the neurons tree
(grows on trees), green
or red
(color), and fruit
. This pattern of discharges is analytically achieved by a set of parameters uniting the nodes, as well as non-linear operations called activation functions, responsible for firing each unit.
Unlike symbolic AI, this paradigm approaches intelligence from a biological aspect. Prototypical models are often linked to organic counterparts, which, at least to a certain extent, served as inspiration for contemporary architectures. Connectionist modeling was a research stream in computer science only claimed during the 1960s, by Frank Rosenblatt, in association with the cognitive science theory that carries the same name (Copeland (2020)).
The early influences of connectionism and date back to the 1850s, with Herbert Spencer’s Principles of Psychology. In this, Spencer alludes to how intelligence can be seen as the successive association of psychological states, which are driven by the connections between such states. In the following decades, William James outlined the mechanisms that indicated how these states could associate, an idea which would be later formalized by Donald Hebb in the 1950s.
Despite today’s historical remarks, the works of Spencer and James were seen as mere speculation at the time. Considered the father of the field, Edward Thorndike, a student of James, was the first to proclaim himself as a “connectionist”. Thorndike, expanded the hypothesis of James to the biological sphere, suggesting that learning was somehow encoded in the connections between neurons. He also suggested these associations could take place upon external reinforcements. This idea was based on the preceding school of behaviorism, more specifically by the work of Pavlov. In this, he demonstrates the processes of excitation and inhibition, outlining the formation of conditioned reflexes, an adaptation of the brain upon a certain pattern, in the eyes of Thorndike (Walker (1992)).
Illustration of the classical conditioning experiment conducted by Pavlov in 1897.
Researchers in computer science later took inspiration from these ideas to develop computational neural network models and their adaptation mechanisms. However, connectionism in computer science has then strayed from its homonym. This paradigm can now be more seen as a functionalist perspective as it neglects the biological correspondence in search of a generalized view of intelligence.
In terms of accomplishment, connectionism in computer science has witnessed many successes in the last decade. Reviving the contested feat of Deep Blue, researchers at DeepMind have developed a system named Alpha Zero, that not only beat its predecessor, but it did so by its own experience, only playing with itself. Since the victory over Kasparov, researchers raised the stakes in search of more challenging feats. In 2015, the DeepMind’s AlphaGo defeated Lee Sedol, considered one of the greatest players at the game of Go, an immensely more complex challenge than chess (DeepMind (2020)).
Despite some push-back against the distancing between the ongoing advancement of neural networks and cognitive science, these fields have been more popular than ever. Not only, neural networks are being used to strengthen cognitive hypothesis2, but these have sprawled and engaged other well-established disciplines on solving standing challenges.
Due to the viewpoint of intelligence centered around learning, the most sought feature in applications is the ability to generalize, i.e. to transfer experience beyond known instances to novel situations. In this perspective, the circumstances and reasons why deep learning models can do so remain unsettled, despite some advancement brought forward by the current statistical learning theory stream 3.
2 See Banino et. al (2018)
3 See Poggio et. al (2020)
Our current capabilities remain limited, and a question that lingers is how far are we from understanding intelligence, or even from reaching it computationally on a human level? Most likely very far, despite the widespread optimism surrounding deep learning, there are several visible limitations to the current settings. However, a good indication of headway is to not only achieve tangible milestones but also to continuously uncover misconceptions. As biological and philosophical novelties, the ongoing engineering experimentation can also help to shed light on these. And as we validate conceptions from multiple angles, the closer we move towards a comprehensive understanding of intelligence.
References
- Buchanan, B. G. (2005). A (Very) Brief History of Artificial Intelligence. AI Magazine, 26(4), 53. doi:10.1609/aimag.v26i4.1848
- McCarthy, J., Minsky, M. L., Rochester, N. and Shannon, C.E. (1955). A proposal for the Dartmouth summer research project on Artificial Intelligence. Retrieved April 13, 2020, from http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html
- Legg, S. and Hunter, M. (2006). A Collection of Definitions of Intelligence
- Pfeifer, R., & Scheier, C. (1999). Understanding intelligence. MIT Press.
- Press, G. (2018). The Brute Force Of IBM Deep Blue And Google DeepMind. Forbes Media. Retrieved April 13, 2020, from https://www.forbes.com/sites/gilpress/2018/02/07/the-brute-force-of-deep-blue-and-deep-learning/
- Ashby, W. R. (1960). Design for a brain: The origin of adaptive behavior. (2d ed). Wiley;
- Sarıhan, I. (2017). Chapter 2 - Philosophical Puzzles Evade Empirical Evidence: Some Thoughts and Clarifications Regarding the Relation Between Brain Sciences and Philosophy of Mind. In J. Leefmann & E. Hildt (Eds.), The Human Sciences after the Decade of the Brain (pp. 14–23). Academic Press. doi:10.1016/B978-0-12-804205-2.00002-1
- Piccinini, G. (2004). The First Computational Theory of Mind and Brain: A Close Look at Mcculloch and Pitts’s “Logical Calculus of Ideas Immanent in Nervous Activity.” Synthese, 141(2), 175–215. doi:10.1023/B:SYNT.0000043018.52445.3e
- Carneades.org. (2016). What is Functionalism? (Philosophy of Mind). Retrieved April 13, 2020, from https://www.youtube.com/watch?v=a5AwaFsp5Os
- Zalta, E. N. (2000). A (Leibnizian) Theory of Concepts. Logical Analysis and History of Philosophy, 3, 137–183.
- Peckhaus, V. (2018). Leibniz’s Influence on 19th Century Logic. The Stanford Encyclopedia of Philosophy
- Newell, Allen; Simon, H. A. (1976), "Computer Science as Empirical Inquiry: Symbols and Search", Communications of the ACM, 19 (3): 113–126, doi:10.1145/360018.360022
- Nilsson, N. J. (2007). The Physical Symbol System Hypothesis: Status and Prospects. In M. Lungarella, F. Iida, J. Bongard, & R. Pfeifer (Eds.), 50 Years of Artificial Intelligence: Essays Dedicated to the 50th Anniversary of Artificial Intelligence (pp. 9–17). Springer. doi:10.1007/978-3-540-77296-5_2
- Stanford University Libraries (2016). Shakey: Experiments in Robot Planning and Learning (1972). Retrieved April 13, 2020, from https://www.youtube.com/watch?v=GmU7SimFkpU
- Rosen, C. A. and Nilsson, N. J. (1967). Application of Intelligent Automata to Reconnaissance. Third Interim Report. Stanford Research Institute.
- Copeland, B.J. (2020). Artificial Intelligence | Definition, Examples, and Applications. Encyclopedia Britannica. Retrieved April 13, 2020, from https://www.britannica.com/technology/artificial-intelligence
- Walker, S. F. (1992) A brief history of connectionism and its psychological implications. In Clark, A. and Lutz, R. (eds) Connectionism in Context. Berlin: Springer-Verlag. 123-144
- DeepMind (2020). AlphaGo: The story so far. Retrieved April 13, 2020, from https://deepmind.com/research/case-studies/alphago-the-story-so-far
- Banino, A., Barry, C., Uria, B., Blundell, C., Lillicrap, T., Mirowski, P., Pritzel, A., Chadwick, M. J., Degris, T., Modayil, J., Wayne, G., Soyer, H., Viola, F., Zhang, B., Goroshin, R., Rabinowitz, N., Pascanu, R., Beattie, C., Petersen, S., Kumaran, D. (2018). Vector-based navigation using grid-like representations in artificial agents. Nature, 557(7705), 429–433. doi:10.1038/s41586-018-0102-6
- Poggio, T., Liao, Q., & Banburski, A. (2020). Complexity control by gradient descent in deep networks. Nature Communications, 11(1), 1–5. doi:10.1038/s41467-020-14663-9


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