#university — Public Fediverse posts

Tony Burke delivers overdue migration policy, but is it sturdy enough to withstand critics?

Tony Burke was late to the National Press Club to announce the government’s migration policy on Thursday. Six…
#NewsBeep #News #Australia #AU #family #Immigration #migration #OneNation #Policy #students #TonyBurke #university
https://www.newsbeep.com/au/895812/

Tony Burke delivers overdue migration policy, but is it sturdy enough to withstand critics?

Tony Burke was late to the National Press Club to announce the government’s migration policy on Thursday. Six…
#NewsBeep #News #Australia #AU #family #Immigration #migration #OneNation #Policy #students #TonyBurke #university
https://www.newsbeep.com/au/895812/

Tony Burke delivers overdue migration policy, but is it sturdy enough to withstand critics?

Tony Burke was late to the National Press Club to announce the government’s migration policy on Thursday. Six…
#Australia #AU #Austrlia #family #immigration #Migration #onenation #policy #students #tonyburke #university
https://www.europesays.com/australia/99146/

Does anyone know of any good flashcard websites like quizlet that dont force AI down your throat??

pls boost for reach!

#fuckai #education #university #study #studentlife #student

#University Rescinds Job Offer to #Activist Who Allegedly Wiped #phone Before #DHS Could #Search It
#security #privacy #4thamendment #border #rights

https://www.404media.co/university-rescinds-job-offer-to-activist-who-allegedly-wiped-phone-before-dhs-could-search-it/

#University Rescinds Job Offer to #Activist Who Allegedly Wiped #phone Before #DHS Could #Search It
#security #privacy #4thamendment #border #rights

https://www.404media.co/university-rescinds-job-offer-to-activist-who-allegedly-wiped-phone-before-dhs-could-search-it/

#University Rescinds Job Offer to #Activist Who Allegedly Wiped #phone Before #DHS Could #Search It
#security #privacy #4thamendment #border #rights

https://www.404media.co/university-rescinds-job-offer-to-activist-who-allegedly-wiped-phone-before-dhs-could-search-it/

#University Rescinds Job Offer to #Activist Who Allegedly Wiped #phone Before #DHS Could #Search It
#security #privacy #4thamendment #border #rights

https://www.404media.co/university-rescinds-job-offer-to-activist-who-allegedly-wiped-phone-before-dhs-could-search-it/

#University Rescinds Job Offer to #Activist Who Allegedly Wiped #phone Before #DHS Could #Search It
#security #privacy #4thamendment #border #rights

https://www.404media.co/university-rescinds-job-offer-to-activist-who-allegedly-wiped-phone-before-dhs-could-search-it/

‘It’s the End of the World as We Know It: So What Kind of AI Do We Actually Want?’ — the latest issue of the Open Humanities newsletter — went out today.

It features discussions of Cory Doctorow’s The Reverse Centaur’s Guide to Life After AI and Karen Hao’s Empire of AI, in the context of the recent warnings that there is a 10% chance AI could ‘kill all humans’ within the next ten years.

But rather than asking only whether AI might destroy us — or what we should do about it — the newsletter asks some slightly different questions: who benefits from persuading us that it might? And what happens when we stop allowing the AI industry to set the terms on which AI itself is discussed and regulated?

There are some pretty good previous issues of the newsletter too, if you missed them:

https://openhumanities.substack.com/p/its-the-end-of-the-world-as-we-know

#ai #human #capitalism #university #management

RE: https://kolektiva.social/@helynbasil/117285680898408003

MORE GOOD NEWS FOR HILEN @helynbasil‼️

SOMEONE ELSE DONATED 8 EUROS!!!

EVERY DONATION MAKES A DIFFERENCE‼️

https://gofund.me/2cfedb2dd

https://gaza-verified.org/people/@hely[email protected]/

#Gaza #Palestine #humanrights #humanity #fediforgaza #sharingiscaring #GazaMutualAid #humanitarianaid #savegaza #helpgaza #savelives #hope #education #university

celebrating the 1970s

#photography #architecture #geometry #university #Bielefeld

celebrating the 1970s

#photography #architecture #geometry #university #Bielefeld

celebrating the 1970s

#photography #architecture #geometry #university #Bielefeld

celebrating the 1970s

#photography #architecture #geometry #university #Bielefeld

celebrating the 1970s

#photography #architecture #geometry #university #Bielefeld

When will Ireland finally achieve full fossil fuel phase-out? – The Irish Times

Ireland is currently in the process of phasing out fossil fuels. Our usage of fossil fuels increased significantly…
#Ireland #IE #Europe #Europa #EU #climatechange #climate-change-advisory-council #darragh-o-brien #energycosts #ireland #oil #Russia #StraitofHormuz #sustainable-energy-authority-of-ireland-seai #ukrainecrisis #university-college-cork-ucc
https://www.europesays.com/3255748/

New Centre for Jewish Heritage at Tel Aviv University – J-Wire

A landmark building at Tel Aviv University is set to become a world-class centre for Jewish scholarship, education…
#Israel #News #donation #education #history #jewishheritage #jewishidentity #Jewishphilosophy #JewishStudies #ora #philanthropy #telaviv #TelAvivUniversity #university
https://www.europesays.com/3255823/

https://www.europesays.com/it/685235/ Dopo una notte in bianco, meglio un sonnellino o attività fisica? #aiutare #altra #attività #AttivitàFisica #breve #BreveSessione #BreveSessioneAttività #cervello #ciò #dicono #dormire #esercizio #Fisica #Health #informazioni #IT #Italia #Italy #McGill #McGillUniversity #mente #minuti #né #notte #possibile #riposo #risultati #Salute #scoperto #sonnellino #sonno #studio #university

https://www.europesays.com/ie/691849/ Satellites show Earth lost more than 12 trillion tons of ice from Greenland, Antarctica in 47 years #Antarctica #decade #Éire #FutureSeaLevelRise #Greenland #Ice #IceScientist #IE #Ireland #MajorIceSheet #ocean #otosaka #RecordSnowfall #Science #Study #StudyAuthor #ton #University #year

95 Percent of Faculty Dissatisfied With Trump’s Second Term, FAS Survey Finds

Ninety-five percent of faculty who responded to The Crimson’s annual Faculty of Arts and Sciences survey said they…
#UnitedStates #US #USA #DonaldTrump #faculty #fas #trump #university
https://www.europesays.com/3254383/

#terraPreta #permaCulture #permaCultura #permaKultur #fediTips

Some additional notes and observations
@HorcaDobleMango

#carbonActivado tanslates in german into #AktivKohle, that's the stuff you find in high quality filters, including filters for #fishTank's, #aquarium's and filres for drinking water as they have the capabilty to filter out all kind of chemicals from air and water. That's the same effect that carbon creates by storing chemical elements in it's space and structure in the soil for #plants and #microorganisms.

Creating carbon from wood by explosively cooling it down throwing it into water, transforming it into "active carbon" resolves the arduous task of creating carbon in an anaerobic setup, an interesting point because we could come up with some kind of #rocketStove with a continious feeding process, seperating glowing carbon from the rest, letting it somehow roll into a water recipient while using the heat created to warm up our houses in the winter. As of now not solved in this idea is what to do with the water steam that is produced, or even to think about some secondery use for that steam. These "ideas/considerations" are actually the result of:
* There is no waste, only primary materials
* Every element in a system has to fulfill at least two goals

What we couldn't find out into deep till now is a the issue that apparently carbon can be #hydrophobe or #hydrophilic and which process makes it hydrophillic. We guess that this is in part an important detail as the carbon harbors not only chemical elements but also is a kind of apartment building for microorganisms and their are probably different apartments for aerobic and anaerobic microorganisms.
Perhaps in the case of your soil some hydrophobic carbon could be even the better option.

Our question about the kind of soil, in part depending of the region you are from, is due to the observations that carbon to create terra preta is very usefull for old leached soils like those of the #Amazon basin, #SouthAmerica and #Africa in particular, as well as probably for example the sandy soils of #Brandenburg and #Mecklenburg-Vorpommern or regions of Spain, while the benefits in soils like Hessen, Western Germany in general and most likely the whole of central europe aren't that extraordinary, even tho they are most likely always beneficial.

With respect to the profile @permaculture, that is a friendica forum page for the fediVerse.
"Our setup" includes the forum page server https://tupambae.org/ as well as the friendica server https://tupambae.com/ harboring also the forum page profiles @permaculture for english and french and @permakultur for german. If you subsribe to a #forumPage and mention that profile in a inicial post (toot) that post will be reshared by that profile page and send to all it's subscribers!

The dot com server is for single profiles and harbors for example a friendica profile @[email protected]. That profile, besides being a standard account in the fediverse actually mirrors publicacions of this mastodon profile over here, in part examplifying the permaculture principal:
* Every element in a system as to be covered at least by two elements/aspects.

At the same time by using #friendica we have the benefits of all the extras that a fediVerse server software brings to the table for profiles and projects like:
* #imageGallery
* #calendar
* #personalNotes and #privateMessage
* #directory for to sort publications
* no character limite
* enhanced text editing tools like #bbCode and #markdown
* #postPreview

simultanios cross publications:
* by email
* to other platforms like #diaspora, #bluesky and #tumblr

In other words, a friendica server for the fediVerse is not only a perfect choice for "Fachbereichsprofile" of a #university like
@unikassel, something like https://social.uni-kassel.de, it's also extremely usefull for projects and larger articles.

Please keep us updated in particular about this very interesting project of yours, actually the best would be as answers in this very thread, so we can save your content in our setup and spread it into the #fediVerse.
👍

#terraPreta #permaCulture #permaCultura #permaKultur #fediTips

Some additional notes and observations
@HorcaDobleMango

#carbonActivado tanslates in german into #AktivKohle, that's the stuff you find in high quality filters, including filters for #fishTank's, #aquarium's and filres for drinking water as they have the capabilty to filter out all kind of chemicals from air and water. That's the same effect that carbon creates by storing chemical elements in it's space and structure in the soil for #plants and #microorganisms.

Creating carbon from wood by explosively cooling it down throwing it into water, transforming it into "active carbon" resolves the arduous task of creating carbon in an anaerobic setup, an interesting point because we could come up with some kind of #rocketStove with a continious feeding process, seperating glowing carbon from the rest, letting it somehow roll into a water recipient while using the heat created to warm up our houses in the winter. As of now not solved in this idea is what to do with the water steam that is produced, or even to think about some secondery use for that steam. These "ideas/considerations" are actually the result of:
* There is no waste, only primary materials
* Every element in a system has to fulfill at least two goals

What we couldn't find out into deep till now is a the issue that apparently carbon can be #hydrophobe or #hydrophilic and which process makes it hydrophillic. We guess that this is in part an important detail as the carbon harbors not only chemical elements but also is a kind of apartment building for microorganisms and their are probably different apartments for aerobic and anaerobic microorganisms.
Perhaps in the case of your soil some hydrophobic carbon could be even the better option.

Our question about the kind of soil, in part depending of the region you are from, is due to the observations that carbon to create terra preta is very usefull for old leached soils like those of the #Amazon basin, #SouthAmerica and #Africa in particular, as well as probably for example the sandy soils of #Brandenburg and #Mecklenburg-Vorpommern or regions of Spain, while the benefits in soils like Hessen, Western Germany in general and most likely the whole of central europe aren't that extraordinary, even tho they are most likely always beneficial.

With respect to the profile @permaculture, that is a friendica forum page for the fediVerse.
"Our setup" includes the forum page server https://tupambae.org/ as well as the friendica server https://tupambae.com/ harboring also the forum page profiles @permaculture for english and french and @permakultur for german. If you subsribe to a #forumPage and mention that profile in a inicial post (toot) that post will be reshared by that profile page and send to all it's subscribers!

The dot com server is for single profiles and harbors for example a friendica profile @[email protected]. That profile, besides being a standard account in the fediverse actually mirrors publicacions of this mastodon profile over here, in part examplifying the permaculture principal:
* Every element in a system as to be covered at least by two elements/aspects.

At the same time by using #friendica we have the benefits of all the extras that a fediVerse server software brings to the table for profiles and projects like:
* #imageGallery
* #calendar
* #personalNotes and #privateMessage
* #directory for to sort publications
* no character limite
* enhanced text editing tools like #bbCode and #markdown
* #postPreview

simultanios cross publications:
* by email
* to other platforms like #diaspora, #bluesky and #tumblr

In other words, a friendica server for the fediVerse is not only a perfect choice for "Fachbereichsprofile" of a #university like
@unikassel, something like https://social.uni-kassel.de, it's also extremely usefull for projects and larger articles.

Please keep us updated in particular about this very interesting project of yours, actually the best would be as answers in this very thread, so we can save your content in our setup and spread it into the #fediVerse.
👍

#terraPreta #permaCulture #permaCultura #permaKultur #fediTips

Some additional notes and observations
@HorcaDobleMango

#carbonActivado tanslates in german into #AktivKohle, that's the stuff you find in high quality filters, including filters for #fishTank's, #aquarium's and filres for drinking water as they have the capabilty to filter out all kind of chemicals from air and water. That's the same effect that carbon creates by storing chemical elements in it's space and structure in the soil for #plants and #microorganisms.

Creating carbon from wood by explosively cooling it down throwing it into water, transforming it into "active carbon" resolves the arduous task of creating carbon in an anaerobic setup, an interesting point because we could come up with some kind of #rocketStove with a continious feeding process, seperating glowing carbon from the rest, letting it somehow roll into a water recipient while using the heat created to warm up our houses in the winter. As of now not solved in this idea is what to do with the water steam that is produced, or even to think about some secondery use for that steam. These "ideas/considerations" are actually the result of:
* There is no waste, only primary materials
* Every element in a system has to fulfill at least two goals

What we couldn't find out into deep till now is a the issue that apparently carbon can be #hydrophobe or #hydrophilic and which process makes it hydrophillic. We guess that this is in part an important detail as the carbon harbors not only chemical elements but also is a kind of apartment building for microorganisms and their are probably different apartments for aerobic and anaerobic microorganisms.
Perhaps in the case of your soil some hydrophobic carbon could be even the better option.

Our question about the kind of soil, in part depending of the region you are from, is due to the observations that carbon to create terra preta is very usefull for old leached soils like those of the #Amazon basin, #SouthAmerica and #Africa in particular, as well as probably for example the sandy soils of #Brandenburg and #Mecklenburg-Vorpommern or regions of Spain, while the benefits in soils like Hessen, Western Germany in general and most likely the whole of central europe aren't that extraordinary, even tho they are most likely always beneficial.

With respect to the profile @permaculture, that is a friendica forum page for the fediVerse.
"Our setup" includes the forum page server https://tupambae.org/ as well as the friendica server https://tupambae.com/ harboring also the forum page profiles @permaculture for english and french and @permakultur for german. If you subsribe to a #forumPage and mention that profile in a inicial post (toot) that post will be reshared by that profile page and send to all it's subscribers!

The dot com server is for single profiles and harbors for example a friendica profile @[email protected]. That profile, besides being a standard account in the fediverse actually mirrors publicacions of this mastodon profile over here, in part examplifying the permaculture principal:
* Every element in a system as to be covered at least by two elements/aspects.

At the same time by using #friendica we have the benefits of all the extras that a fediVerse server software brings to the table for profiles and projects like:
* #imageGallery
* #calendar
* #personalNotes and #privateMessage
* #directory for to sort publications
* no character limite
* enhanced text editing tools like #bbCode and #markdown
* #postPreview

simultanios cross publications:
* by email
* to other platforms like #diaspora, #bluesky and #tumblr

In other words, a friendica server for the fediVerse is not only a perfect choice for "Fachbereichsprofile" of a #university like
@unikassel, something like https://social.uni-kassel.de, it's also extremely usefull for projects and larger articles.

Please keep us updated in particular about this very interesting project of yours, actually the best would be as answers in this very thread, so we can save your content in our setup and spread it into the #fediVerse.
👍

#terraPreta #permaCulture #permaCultura #permaKultur #fediTips

Some additional notes and observations
@HorcaDobleMango

#carbonActivado tanslates in german into #AktivKohle, that's the stuff you find in high quality filters, including filters for #fishTank's, #aquarium's and filres for drinking water as they have the capabilty to filter out all kind of chemicals from air and water. That's the same effect that carbon creates by storing chemical elements in it's space and structure in the soil for #plants and #microorganisms.

Creating carbon from wood by explosively cooling it down throwing it into water, transforming it into "active carbon" resolves the arduous task of creating carbon in an anaerobic setup, an interesting point because we could come up with some kind of #rocketStove with a continious feeding process, seperating glowing carbon from the rest, letting it somehow roll into a water recipient while using the heat created to warm up our houses in the winter. As of now not solved in this idea is what to do with the water steam that is produced, or even to think about some secondery use for that steam. These "ideas/considerations" are actually the result of:
* There is no waste, only primary materials
* Every element in a system has to fulfill at least two goals

What we couldn't find out into deep till now is a the issue that apparently carbon can be #hydrophobe or #hydrophilic and which process makes it hydrophillic. We guess that this is in part an important detail as the carbon harbors not only chemical elements but also is a kind of apartment building for microorganisms and their are probably different apartments for aerobic and anaerobic microorganisms.
Perhaps in the case of your soil some hydrophobic carbon could be even the better option.

Our question about the kind of soil, in part depending of the region you are from, is due to the observations that carbon to create terra preta is very usefull for old leached soils like those of the #Amazon basin, #SouthAmerica and #Africa in particular, as well as probably for example the sandy soils of #Brandenburg and #Mecklenburg-Vorpommern or regions of Spain, while the benefits in soils like Hessen, Western Germany in general and most likely the whole of central europe aren't that extraordinary, even tho they are most likely always beneficial.

With respect to the profile @permaculture, that is a friendica forum page for the fediVerse.
"Our setup" includes the forum page server https://tupambae.org/ as well as the friendica server https://tupambae.com/ harboring also the forum page profiles @permaculture for english and french and @permakultur for german. If you subsribe to a #forumPage and mention that profile in a inicial post (toot) that post will be reshared by that profile page and send to all it's subscribers!

The dot com server is for single profiles and harbors for example a friendica profile @[email protected]. That profile, besides being a standard account in the fediverse actually mirrors publicacions of this mastodon profile over here, in part examplifying the permaculture principal:
* Every element in a system as to be covered at least by two elements/aspects.

At the same time by using #friendica we have the benefits of all the extras that a fediVerse server software brings to the table for profiles and projects like:
* #imageGallery
* #calendar
* #personalNotes and #privateMessage
* #directory for to sort publications
* no character limite
* enhanced text editing tools like #bbCode and #markdown
* #postPreview

simultanios cross publications:
* by email
* to other platforms like #diaspora, #bluesky and #tumblr

In other words, a friendica server for the fediVerse is not only a perfect choice for "Fachbereichsprofile" of a #university like
@unikassel, something like https://social.uni-kassel.de, it's also extremely usefull for projects and larger articles.

Please keep us updated in particular about this very interesting project of yours, actually the best would be as answers in this very thread, so we can save your content in our setup and spread it into the #fediVerse.
👍

ONDA ANOMALA: MIGRANTI CLIMATICI, LE RISORSE PER MILITARIZZARE LE FRONTIERE OLTRE IL DOPPIO DI QUELLE PER MITIGARE IL CLIMA https://www.radiondadurto.org/2025/01/29/onda-anomala-migranti-climatici-le-risorse-per-militarizzare-le-frontiere-oltre-il-doppio-di-quelle-per-mitigare-il-clima/ #LaCassettadegliAttrezzi #cassettadegliattrezzi #ElenaGiacomelli #Internazionale #Immigrazione #Trasmissione #cambiamento #migrazioni #università #University #climatico #frontiere #sicurezza #Ambiente #ambiente

ONDA ANOMALA: MIGRANTI CLIMATICI, LE RISORSE PER MILITARIZZARE LE FRONTIERE OLTRE IL DOPPIO DI QUELLE PER MITIGARE IL CLIMA https://www.radiondadurto.org/2025/01/29/onda-anomala-migranti-climatici-le-risorse-per-militarizzare-le-frontiere-oltre-il-doppio-di-quelle-per-mitigare-il-clima/ #LaCassettadegliAttrezzi #cassettadegliattrezzi #ElenaGiacomelli #Internazionale #Immigrazione #Trasmissione #cambiamento #migrazioni #università #University #climatico #frontiere #sicurezza #Ambiente #ambiente

ONDA ANOMALA: MIGRANTI CLIMATICI, LE RISORSE PER MILITARIZZARE LE FRONTIERE OLTRE IL DOPPIO DI QUELLE PER MITIGARE IL CLIMA https://www.radiondadurto.org/2025/01/29/onda-anomala-migranti-climatici-le-risorse-per-militarizzare-le-frontiere-oltre-il-doppio-di-quelle-per-mitigare-il-clima/ #LaCassettadegliAttrezzi #cassettadegliattrezzi #ElenaGiacomelli #Internazionale #Immigrazione #Trasmissione #cambiamento #migrazioni #università #University #climatico #frontiere #sicurezza #Ambiente #ambiente

Arıkan's new solution was to create near-perfect channels from ordinary channels by a process he called “#channel #polarization.”

Noise would be transferred from one channel to a copy of the same channel to create a cleaner copy and a dirtier one.

After a recursive series of such steps, two sets of channels emerge, one set being extremely noisy, the other being almost noise-free.

The channels that are scrubbed of noise, in theory, can attain the Shannon limit.

He dubbed his solution #polar #codes.
It's as if the noise was banished to the North Pole, allowing for pristine communications at the South Pole.

After this discovery, Arıkan spent two more years refining the details.
He had read that before Shannon released his famous paper on information theory, his supervisor at Bell Labs would pop by and ask if the researcher had anything new.
“Shannon never mentioned information theory,” says Arıkan with a laugh.
“He kept his work undercover. He didn't disclose it.”

That was also Arıkan's MO. “I had the luxury of knowing that no other person in the world was working on this problem,” Arıkan says, “because it was not a fashionable subject.”

In 2008, three years after his eureka moment, Arıkan finally presented his work.

He had understood its importance all along. Over the years, whenever he traveled, he would leave his unpublished manuscript in two envelopes addressed to “top colleagues whom I trusted,” with the order to mail them “if I don't come back.”

In 2009 he published his definitive paper in the field's top journal, IEEE Transactions on Information Theory.

It didn't exactly make him a household name, but within the small community of information theorists, polar codes were a sensation.

Arıkan traveled to the US to give a series of lectures. (You can see them on YouTube; they are not for the mathematically fainthearted. The students look a bit bored.)

Arıkan was justifiably proud of his accomplishment, but he didn't think of polar codes as something with practical value.

It was a theoretical solution that, even if implemented, seemed unlikely to rival the error-correction codes already in place.

He didn't even bother to get a patent.

#channel #capacity #Shannon #limit #correcting #errors #Bilkent #University #eureka #accurately #redundancy #channel #coding #problem

Arıkan's new solution was to create near-perfect channels from ordinary channels by a process he called “#channel #polarization.”

Noise would be transferred from one channel to a copy of the same channel to create a cleaner copy and a dirtier one.

After a recursive series of such steps, two sets of channels emerge, one set being extremely noisy, the other being almost noise-free.

The channels that are scrubbed of noise, in theory, can attain the Shannon limit.

He dubbed his solution #polar #codes.
It's as if the noise was banished to the North Pole, allowing for pristine communications at the South Pole.

After this discovery, Arıkan spent two more years refining the details.
He had read that before Shannon released his famous paper on information theory, his supervisor at Bell Labs would pop by and ask if the researcher had anything new.
“Shannon never mentioned information theory,” says Arıkan with a laugh.
“He kept his work undercover. He didn't disclose it.”

That was also Arıkan's MO. “I had the luxury of knowing that no other person in the world was working on this problem,” Arıkan says, “because it was not a fashionable subject.”

In 2008, three years after his eureka moment, Arıkan finally presented his work.

He had understood its importance all along. Over the years, whenever he traveled, he would leave his unpublished manuscript in two envelopes addressed to “top colleagues whom I trusted,” with the order to mail them “if I don't come back.”

In 2009 he published his definitive paper in the field's top journal, IEEE Transactions on Information Theory.

It didn't exactly make him a household name, but within the small community of information theorists, polar codes were a sensation.

Arıkan traveled to the US to give a series of lectures. (You can see them on YouTube; they are not for the mathematically fainthearted. The students look a bit bored.)

Arıkan was justifiably proud of his accomplishment, but he didn't think of polar codes as something with practical value.

It was a theoretical solution that, even if implemented, seemed unlikely to rival the error-correction codes already in place.

He didn't even bother to get a patent.

#channel #capacity #Shannon #limit #correcting #errors #Bilkent #University #eureka #accurately #redundancy #channel #coding #problem

Arıkan's new solution was to create near-perfect channels from ordinary channels by a process he called “#channel #polarization.”

Noise would be transferred from one channel to a copy of the same channel to create a cleaner copy and a dirtier one.

After a recursive series of such steps, two sets of channels emerge, one set being extremely noisy, the other being almost noise-free.

The channels that are scrubbed of noise, in theory, can attain the Shannon limit.

He dubbed his solution #polar #codes.
It's as if the noise was banished to the North Pole, allowing for pristine communications at the South Pole.

After this discovery, Arıkan spent two more years refining the details.
He had read that before Shannon released his famous paper on information theory, his supervisor at Bell Labs would pop by and ask if the researcher had anything new.
“Shannon never mentioned information theory,” says Arıkan with a laugh.
“He kept his work undercover. He didn't disclose it.”

That was also Arıkan's MO. “I had the luxury of knowing that no other person in the world was working on this problem,” Arıkan says, “because it was not a fashionable subject.”

In 2008, three years after his eureka moment, Arıkan finally presented his work.

He had understood its importance all along. Over the years, whenever he traveled, he would leave his unpublished manuscript in two envelopes addressed to “top colleagues whom I trusted,” with the order to mail them “if I don't come back.”

In 2009 he published his definitive paper in the field's top journal, IEEE Transactions on Information Theory.

It didn't exactly make him a household name, but within the small community of information theorists, polar codes were a sensation.

Arıkan traveled to the US to give a series of lectures. (You can see them on YouTube; they are not for the mathematically fainthearted. The students look a bit bored.)

Arıkan was justifiably proud of his accomplishment, but he didn't think of polar codes as something with practical value.

It was a theoretical solution that, even if implemented, seemed unlikely to rival the error-correction codes already in place.

He didn't even bother to get a patent.

#channel #capacity #Shannon #limit #correcting #errors #Bilkent #University #eureka #accurately #redundancy #channel #coding #problem

Arıkan's new solution was to create near-perfect channels from ordinary channels by a process he called “#channel #polarization.”

Noise would be transferred from one channel to a copy of the same channel to create a cleaner copy and a dirtier one.

After a recursive series of such steps, two sets of channels emerge, one set being extremely noisy, the other being almost noise-free.

The channels that are scrubbed of noise, in theory, can attain the Shannon limit.

He dubbed his solution #polar #codes.
It's as if the noise was banished to the North Pole, allowing for pristine communications at the South Pole.

After this discovery, Arıkan spent two more years refining the details.
He had read that before Shannon released his famous paper on information theory, his supervisor at Bell Labs would pop by and ask if the researcher had anything new.
“Shannon never mentioned information theory,” says Arıkan with a laugh.
“He kept his work undercover. He didn't disclose it.”

That was also Arıkan's MO. “I had the luxury of knowing that no other person in the world was working on this problem,” Arıkan says, “because it was not a fashionable subject.”

In 2008, three years after his eureka moment, Arıkan finally presented his work.

He had understood its importance all along. Over the years, whenever he traveled, he would leave his unpublished manuscript in two envelopes addressed to “top colleagues whom I trusted,” with the order to mail them “if I don't come back.”

In 2009 he published his definitive paper in the field's top journal, IEEE Transactions on Information Theory.

It didn't exactly make him a household name, but within the small community of information theorists, polar codes were a sensation.

Arıkan traveled to the US to give a series of lectures. (You can see them on YouTube; they are not for the mathematically fainthearted. The students look a bit bored.)

Arıkan was justifiably proud of his accomplishment, but he didn't think of polar codes as something with practical value.

It was a theoretical solution that, even if implemented, seemed unlikely to rival the error-correction codes already in place.

He didn't even bother to get a patent.

#channel #capacity #Shannon #limit #correcting #errors #Bilkent #University #eureka #accurately #redundancy #channel #coding #problem

Arıkan's new solution was to create near-perfect channels from ordinary channels by a process he called “#channel #polarization.”

Noise would be transferred from one channel to a copy of the same channel to create a cleaner copy and a dirtier one.

After a recursive series of such steps, two sets of channels emerge, one set being extremely noisy, the other being almost noise-free.

The channels that are scrubbed of noise, in theory, can attain the Shannon limit.

He dubbed his solution #polar #codes.
It's as if the noise was banished to the North Pole, allowing for pristine communications at the South Pole.

After this discovery, Arıkan spent two more years refining the details.
He had read that before Shannon released his famous paper on information theory, his supervisor at Bell Labs would pop by and ask if the researcher had anything new.
“Shannon never mentioned information theory,” says Arıkan with a laugh.
“He kept his work undercover. He didn't disclose it.”

That was also Arıkan's MO. “I had the luxury of knowing that no other person in the world was working on this problem,” Arıkan says, “because it was not a fashionable subject.”

In 2008, three years after his eureka moment, Arıkan finally presented his work.

He had understood its importance all along. Over the years, whenever he traveled, he would leave his unpublished manuscript in two envelopes addressed to “top colleagues whom I trusted,” with the order to mail them “if I don't come back.”

In 2009 he published his definitive paper in the field's top journal, IEEE Transactions on Information Theory.

It didn't exactly make him a household name, but within the small community of information theorists, polar codes were a sensation.

Arıkan traveled to the US to give a series of lectures. (You can see them on YouTube; they are not for the mathematically fainthearted. The students look a bit bored.)

Arıkan was justifiably proud of his accomplishment, but he didn't think of polar codes as something with practical value.

It was a theoretical solution that, even if implemented, seemed unlikely to rival the error-correction codes already in place.

He didn't even bother to get a patent.

#channel #capacity #Shannon #limit #correcting #errors #Bilkent #University #eureka #accurately #redundancy #channel #coding #problem

Arıkan devoted the next year to learning about networks, but he never gave up on his passion for information science.

What gripped him most was solving a challenge that Shannon himself had spelled out in his 1948 paper:
how to transport accurate information at high speed while defeating the inevitable “noise”
—undesirable alterations of the message
—introduced in the process of moving all those bits.

The problem was known as #channel #capacity.

According to Shannon, every communications channel had a kind of speed limit for transmitting information reliably.

This as-yet-unattained theoretical boundary was referred to as the #Shannon #limit.

Gallager had wrestled with the Shannon limit early in his career, and he got close. His much celebrated theoretical approach was something he called low-density parity-check codes, or LDPC, which were, in simplest terms, a high-speed method of #correcting #errors on the fly.

While the mathematics of LDPC were innovative, Gallager understood at the time that it wasn't commercially viable.

“It was just too complicated for the cost of the logical operations that were needed,” Gallager says now.

Gallager and others at MIT figured that they had gotten as close to the Shannon limit as one could get, and he moved on.

At MIT in the 1980s, the excitement about information theory had waned.
But not for Arıkan.

He wanted to solve the problem that stood in the way of reaching the Shannon limit.

Even as he pursued his thesis on the networking problem that Gallager had pointed him to, he seized on a piece that included error correction.

“When you do error-correction coding, you are in Shannon theory,” he says.

Arıkan finished his doctoral thesis in 1986, and after a brief stint at the University of Illinois he returned to Turkey to join the country's first private, nonprofit research institution, #Bilkent #University, located on the outskirts of Ankara.

Arıkan helped establish its engineering school. He taught classes. He published papers.

But Bilkent also allowed him to pursue his potentially fruitless battle with the Shannon limit.

“The best people are in the US, but why aren't they working for 10 years, 20 years on the same problem?” he said.
“Because they wouldn't be able to get tenure; they wouldn't be able to get research funding.”

Rather than advancing his field in tiny increments, he went on a monumental quest. It would be his work for the next 20 years.

In December 2005 he had a kind of #eureka moment.
Spurred by a question posed in a three-page dispatch written in 1965 by a Russian information scientist, Arıkan reframed the problem for himself.

“The key to discoveries is to look at those places where there is still a paradox,” Arıkan says.

“It's like the tip of an iceberg. If there is a point of dissatisfaction, take a closer look at it. You are likely to find a treasure trove underneath.”

Arıkan's goal was to transmit messages accurately over a noisy channel at the fastest possible speed.

The key word is #accurately. If you don't care about accuracy, you can send messages unfettered.

But if you want the recipient to get the same data that you sent, you have to insert some #redundancy into the message.
That gives the recipient a way to cross-check the message to make sure it's what you sent.

Inevitably, that extra cross-checking slows things down.
This is known as the #channel #coding #problem.

The greater the amount of noise, the more added redundancy is needed to protect the message.

And the more redundancy you add, the slower the rate of transmission becomes.

The coding problem tries to defeat that trade-off and find ways to achieve reliable transmission of information at the fastest possible rate.

The optimum rate would be the Shannon limit: channel coding nirvana.

Arıkan devoted the next year to learning about networks, but he never gave up on his passion for information science.

What gripped him most was solving a challenge that Shannon himself had spelled out in his 1948 paper:
how to transport accurate information at high speed while defeating the inevitable “noise”
—undesirable alterations of the message
—introduced in the process of moving all those bits.

The problem was known as #channel #capacity.

According to Shannon, every communications channel had a kind of speed limit for transmitting information reliably.

This as-yet-unattained theoretical boundary was referred to as the #Shannon #limit.

Gallager had wrestled with the Shannon limit early in his career, and he got close. His much celebrated theoretical approach was something he called low-density parity-check codes, or LDPC, which were, in simplest terms, a high-speed method of #correcting #errors on the fly.

While the mathematics of LDPC were innovative, Gallager understood at the time that it wasn't commercially viable.

“It was just too complicated for the cost of the logical operations that were needed,” Gallager says now.

Gallager and others at MIT figured that they had gotten as close to the Shannon limit as one could get, and he moved on.

At MIT in the 1980s, the excitement about information theory had waned.
But not for Arıkan.

He wanted to solve the problem that stood in the way of reaching the Shannon limit.

Even as he pursued his thesis on the networking problem that Gallager had pointed him to, he seized on a piece that included error correction.

“When you do error-correction coding, you are in Shannon theory,” he says.

Arıkan finished his doctoral thesis in 1986, and after a brief stint at the University of Illinois he returned to Turkey to join the country's first private, nonprofit research institution, #Bilkent #University, located on the outskirts of Ankara.

Arıkan helped establish its engineering school. He taught classes. He published papers.

But Bilkent also allowed him to pursue his potentially fruitless battle with the Shannon limit.

“The best people are in the US, but why aren't they working for 10 years, 20 years on the same problem?” he said.
“Because they wouldn't be able to get tenure; they wouldn't be able to get research funding.”

Rather than advancing his field in tiny increments, he went on a monumental quest. It would be his work for the next 20 years.

In December 2005 he had a kind of #eureka moment.
Spurred by a question posed in a three-page dispatch written in 1965 by a Russian information scientist, Arıkan reframed the problem for himself.

“The key to discoveries is to look at those places where there is still a paradox,” Arıkan says.

“It's like the tip of an iceberg. If there is a point of dissatisfaction, take a closer look at it. You are likely to find a treasure trove underneath.”

Arıkan's goal was to transmit messages accurately over a noisy channel at the fastest possible speed.

The key word is #accurately. If you don't care about accuracy, you can send messages unfettered.

But if you want the recipient to get the same data that you sent, you have to insert some #redundancy into the message.
That gives the recipient a way to cross-check the message to make sure it's what you sent.

Inevitably, that extra cross-checking slows things down.
This is known as the #channel #coding #problem.

The greater the amount of noise, the more added redundancy is needed to protect the message.

And the more redundancy you add, the slower the rate of transmission becomes.

The coding problem tries to defeat that trade-off and find ways to achieve reliable transmission of information at the fastest possible rate.

The optimum rate would be the Shannon limit: channel coding nirvana.

Arıkan devoted the next year to learning about networks, but he never gave up on his passion for information science.

What gripped him most was solving a challenge that Shannon himself had spelled out in his 1948 paper:
how to transport accurate information at high speed while defeating the inevitable “noise”
—undesirable alterations of the message
—introduced in the process of moving all those bits.

The problem was known as #channel #capacity.

According to Shannon, every communications channel had a kind of speed limit for transmitting information reliably.

This as-yet-unattained theoretical boundary was referred to as the #Shannon #limit.

Gallager had wrestled with the Shannon limit early in his career, and he got close. His much celebrated theoretical approach was something he called low-density parity-check codes, or LDPC, which were, in simplest terms, a high-speed method of #correcting #errors on the fly.

While the mathematics of LDPC were innovative, Gallager understood at the time that it wasn't commercially viable.

“It was just too complicated for the cost of the logical operations that were needed,” Gallager says now.

Gallager and others at MIT figured that they had gotten as close to the Shannon limit as one could get, and he moved on.

At MIT in the 1980s, the excitement about information theory had waned.
But not for Arıkan.

He wanted to solve the problem that stood in the way of reaching the Shannon limit.

Even as he pursued his thesis on the networking problem that Gallager had pointed him to, he seized on a piece that included error correction.

“When you do error-correction coding, you are in Shannon theory,” he says.

Arıkan finished his doctoral thesis in 1986, and after a brief stint at the University of Illinois he returned to Turkey to join the country's first private, nonprofit research institution, #Bilkent #University, located on the outskirts of Ankara.

Arıkan helped establish its engineering school. He taught classes. He published papers.

But Bilkent also allowed him to pursue his potentially fruitless battle with the Shannon limit.

“The best people are in the US, but why aren't they working for 10 years, 20 years on the same problem?” he said.
“Because they wouldn't be able to get tenure; they wouldn't be able to get research funding.”

Rather than advancing his field in tiny increments, he went on a monumental quest. It would be his work for the next 20 years.

In December 2005 he had a kind of #eureka moment.
Spurred by a question posed in a three-page dispatch written in 1965 by a Russian information scientist, Arıkan reframed the problem for himself.

“The key to discoveries is to look at those places where there is still a paradox,” Arıkan says.

“It's like the tip of an iceberg. If there is a point of dissatisfaction, take a closer look at it. You are likely to find a treasure trove underneath.”

Arıkan's goal was to transmit messages accurately over a noisy channel at the fastest possible speed.

The key word is #accurately. If you don't care about accuracy, you can send messages unfettered.

But if you want the recipient to get the same data that you sent, you have to insert some #redundancy into the message.
That gives the recipient a way to cross-check the message to make sure it's what you sent.

Inevitably, that extra cross-checking slows things down.
This is known as the #channel #coding #problem.

The greater the amount of noise, the more added redundancy is needed to protect the message.

And the more redundancy you add, the slower the rate of transmission becomes.

The coding problem tries to defeat that trade-off and find ways to achieve reliable transmission of information at the fastest possible rate.

The optimum rate would be the Shannon limit: channel coding nirvana.

Arıkan devoted the next year to learning about networks, but he never gave up on his passion for information science.

What gripped him most was solving a challenge that Shannon himself had spelled out in his 1948 paper:
how to transport accurate information at high speed while defeating the inevitable “noise”
—undesirable alterations of the message
—introduced in the process of moving all those bits.

The problem was known as #channel #capacity.

According to Shannon, every communications channel had a kind of speed limit for transmitting information reliably.

This as-yet-unattained theoretical boundary was referred to as the #Shannon #limit.

Gallager had wrestled with the Shannon limit early in his career, and he got close. His much celebrated theoretical approach was something he called low-density parity-check codes, or LDPC, which were, in simplest terms, a high-speed method of #correcting #errors on the fly.

While the mathematics of LDPC were innovative, Gallager understood at the time that it wasn't commercially viable.

“It was just too complicated for the cost of the logical operations that were needed,” Gallager says now.

Gallager and others at MIT figured that they had gotten as close to the Shannon limit as one could get, and he moved on.

At MIT in the 1980s, the excitement about information theory had waned.
But not for Arıkan.

He wanted to solve the problem that stood in the way of reaching the Shannon limit.

Even as he pursued his thesis on the networking problem that Gallager had pointed him to, he seized on a piece that included error correction.

“When you do error-correction coding, you are in Shannon theory,” he says.

Arıkan finished his doctoral thesis in 1986, and after a brief stint at the University of Illinois he returned to Turkey to join the country's first private, nonprofit research institution, #Bilkent #University, located on the outskirts of Ankara.

Arıkan helped establish its engineering school. He taught classes. He published papers.

But Bilkent also allowed him to pursue his potentially fruitless battle with the Shannon limit.

“The best people are in the US, but why aren't they working for 10 years, 20 years on the same problem?” he said.
“Because they wouldn't be able to get tenure; they wouldn't be able to get research funding.”

Rather than advancing his field in tiny increments, he went on a monumental quest. It would be his work for the next 20 years.

In December 2005 he had a kind of #eureka moment.
Spurred by a question posed in a three-page dispatch written in 1965 by a Russian information scientist, Arıkan reframed the problem for himself.

“The key to discoveries is to look at those places where there is still a paradox,” Arıkan says.

“It's like the tip of an iceberg. If there is a point of dissatisfaction, take a closer look at it. You are likely to find a treasure trove underneath.”

Arıkan's goal was to transmit messages accurately over a noisy channel at the fastest possible speed.

The key word is #accurately. If you don't care about accuracy, you can send messages unfettered.

But if you want the recipient to get the same data that you sent, you have to insert some #redundancy into the message.
That gives the recipient a way to cross-check the message to make sure it's what you sent.

Inevitably, that extra cross-checking slows things down.
This is known as the #channel #coding #problem.

The greater the amount of noise, the more added redundancy is needed to protect the message.

And the more redundancy you add, the slower the rate of transmission becomes.

The coding problem tries to defeat that trade-off and find ways to achieve reliable transmission of information at the fastest possible rate.

The optimum rate would be the Shannon limit: channel coding nirvana.

Arıkan devoted the next year to learning about networks, but he never gave up on his passion for information science.

What gripped him most was solving a challenge that Shannon himself had spelled out in his 1948 paper:
how to transport accurate information at high speed while defeating the inevitable “noise”
—undesirable alterations of the message
—introduced in the process of moving all those bits.

The problem was known as #channel #capacity.

According to Shannon, every communications channel had a kind of speed limit for transmitting information reliably.

This as-yet-unattained theoretical boundary was referred to as the #Shannon #limit.

Gallager had wrestled with the Shannon limit early in his career, and he got close. His much celebrated theoretical approach was something he called low-density parity-check codes, or LDPC, which were, in simplest terms, a high-speed method of #correcting #errors on the fly.

While the mathematics of LDPC were innovative, Gallager understood at the time that it wasn't commercially viable.

“It was just too complicated for the cost of the logical operations that were needed,” Gallager says now.

Gallager and others at MIT figured that they had gotten as close to the Shannon limit as one could get, and he moved on.

At MIT in the 1980s, the excitement about information theory had waned.
But not for Arıkan.

He wanted to solve the problem that stood in the way of reaching the Shannon limit.

Even as he pursued his thesis on the networking problem that Gallager had pointed him to, he seized on a piece that included error correction.

“When you do error-correction coding, you are in Shannon theory,” he says.

Arıkan finished his doctoral thesis in 1986, and after a brief stint at the University of Illinois he returned to Turkey to join the country's first private, nonprofit research institution, #Bilkent #University, located on the outskirts of Ankara.

Arıkan helped establish its engineering school. He taught classes. He published papers.

But Bilkent also allowed him to pursue his potentially fruitless battle with the Shannon limit.

“The best people are in the US, but why aren't they working for 10 years, 20 years on the same problem?” he said.
“Because they wouldn't be able to get tenure; they wouldn't be able to get research funding.”

Rather than advancing his field in tiny increments, he went on a monumental quest. It would be his work for the next 20 years.

In December 2005 he had a kind of #eureka moment.
Spurred by a question posed in a three-page dispatch written in 1965 by a Russian information scientist, Arıkan reframed the problem for himself.

“The key to discoveries is to look at those places where there is still a paradox,” Arıkan says.

“It's like the tip of an iceberg. If there is a point of dissatisfaction, take a closer look at it. You are likely to find a treasure trove underneath.”

Arıkan's goal was to transmit messages accurately over a noisy channel at the fastest possible speed.

The key word is #accurately. If you don't care about accuracy, you can send messages unfettered.

But if you want the recipient to get the same data that you sent, you have to insert some #redundancy into the message.
That gives the recipient a way to cross-check the message to make sure it's what you sent.

Inevitably, that extra cross-checking slows things down.
This is known as the #channel #coding #problem.

The greater the amount of noise, the more added redundancy is needed to protect the message.

And the more redundancy you add, the slower the rate of transmission becomes.

The coding problem tries to defeat that trade-off and find ways to achieve reliable transmission of information at the fastest possible rate.

The optimum rate would be the Shannon limit: channel coding nirvana.