#redundancy — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #redundancy, aggregated by home.social.
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Blog alert!
This time on checking your options when a cloud service goes down. Are you aware of what happens in your cloud?
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Blog alert!
This time on checking your options when a cloud service goes down. Are you aware of what happens in your cloud?
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Blog alert!
This time on checking your options when a cloud service goes down. Are you aware of what happens in your cloud?
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Blog alert!
This time on checking your options when a cloud service goes down. Are you aware of what happens in your cloud?
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https://www.europesays.com/uk/951533/ Britain to lose 163,000 jobs amid Iran war fallout – with two UK regions hit the hardest #BankOfEngland #Banks #Business #Economy #EnergyBills #HumberInc #Iran #JobLosses #LivingStandards #MiddleEast #PriceRises #redundancy #UK #unemployment #UnitedKingdom
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https://www.europesays.com/britain/33231/ Britain to lose 163,000 jobs amid Iran war fallout – with two UK regions hit the hardest #BankOfEngland #Banks #Britain #EnergyBills #HumberInc #Iran #JobLosses #LivingStandards #MiddleEast #PriceRises #redundancy #unemployment
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TGJONES: Bailiff threat and tax debts cast fresh doubt over south-west Wales stores as WH Smith refuses to fund redundancy payments
The seven TGJones stores at risk across south-west Wales face fresh uncertainty after new details emerged about the dire financial state of the chain — including millions of pounds in unpaid taxes and a looming threat of bailiff action.
Seven branches in the region — including the Swansea Quadrant, Neath, Llanelli, Carmarthen, Bridgend, Tenby and Haverfordwest — were put at risk last week when owner Modella Capital announced plans to close up to 150 stores nationally as part of a major restructuring.
Now documents circulated to creditors have revealed that TGJones owes £8.4 million to HMRC, with a six-month payment agreement struck in April — and a further £3.4 million in business rates arrears. The Telegraph has reported that bailiffs are now a real threat if those payments are not maintained.
The revelations paint a stark picture of a business that has deteriorated rapidly since WH Smith sold its 480 high street stores to Modella Capital in March 2025 and rebranded them as TGJones.
The sale was originally valued at £76 million, but this was renegotiated sharply downward to £42 million to reflect what was described at the time as a “sharp deterioration in trading conditions.” In reality, WH Smith received just £10 million upfront, with the remaining £32 million contingent on the business’s future cash flows — money that now looks unlikely ever to materialise.
Modella has since approached WH Smith to ask whether it would fund enhanced redundancy payments for staff likely to lose their jobs if stores close. WH Smith had previously offered staff a more generous redundancy scheme than the statutory minimum. It declined to provide any further support.
The development is significant for workers at the seven south-west Wales branches, who now face the prospect of statutory redundancy only if their stores are among those confirmed for closure.
The restructuring Modella is planning is known as a “cram-down” — a relatively novel legal mechanism that requires the consent of only one class of creditors to proceed, rather than a majority. It will require approval from a High Court judge, with a hearing expected in late June.
Landlords are likely to face demands for severe reductions in rent as part of the plan. Those who refuse could simply take back the keys to their stores.
If the restructuring is approved, Modella has promised to invest £35 million in a turnaround plan it claims would return TGJones to profitability, with what it describes as a “considerable investment” in the stores that survive.
The creditor documents also reveal the existence of a mystery private individual — described as not being linked to Modella — who is owed £8 million by TGJones. No further details have been disclosed.
The crisis comes as Modella’s track record with other retail brands comes under scrutiny. Both The Original Factory Shop and Claire’s Accessories — two other chains acquired by the firm — have been placed into administration in recent months. Modella blamed the worsening conditions on the British high street and tax rises enacted by the Government.
An insolvency specialist quoted in earlier reporting warned that the pipeline of retail closures was “far from over,” pointing to the collapse in discretionary spending, stubbornly low high street footfall outside major city centres, and the impact of rising National Living Wage costs and higher employer National Insurance contributions.
Post Office has previously said it will update communities if any of its services — hosted within TGJones stores — are forced to relocate as a result of the closures.
The High Court hearing in late June is now the key date for anyone with an interest in the future of the south-west Wales stores — and for the staff who work in them.
Our TGJones coverage
Seven south-west Wales stores at risk as chain announces 150 closures
The full list of at-risk branches across the region.Post Office promises to update communities if any branches are forced to relocate
What the closures could mean for Post Office services hosted within TGJones stores.WH Smith sells high street stores — which will be renamed TGJones
#administration #Carmarthen #featured #HMRC #ModellaCapital #Neath #QuadrantShoppingCentre #redundancy #Swansea #SwanseaQuadrant #TGJones #WHSmith
How the chain ended up in Modella Capital’s hands in the first place. -
🤡 Ah, the groundbreaking "GETadb" service—a true #innovation in redundancy! 🎉 Use your own random #UUID because, clearly, automated processes are so last year. 🤖 Don't forget to outsmart WebFetch's 15-minute memory span, because who needs efficiency when you can generate endless unique URLs for every breath you take? 🚀
https://www.getadb.com/ #GETadb #redundancy #WebFetch #uniqueURLs #HackerNews #ngated -
🤡 Ah, the groundbreaking "GETadb" service—a true #innovation in redundancy! 🎉 Use your own random #UUID because, clearly, automated processes are so last year. 🤖 Don't forget to outsmart WebFetch's 15-minute memory span, because who needs efficiency when you can generate endless unique URLs for every breath you take? 🚀
https://www.getadb.com/ #GETadb #redundancy #WebFetch #uniqueURLs #HackerNews #ngated -
🤡 Ah, the groundbreaking "GETadb" service—a true #innovation in redundancy! 🎉 Use your own random #UUID because, clearly, automated processes are so last year. 🤖 Don't forget to outsmart WebFetch's 15-minute memory span, because who needs efficiency when you can generate endless unique URLs for every breath you take? 🚀
https://www.getadb.com/ #GETadb #redundancy #WebFetch #uniqueURLs #HackerNews #ngated -
🤡 Ah, the groundbreaking "GETadb" service—a true #innovation in redundancy! 🎉 Use your own random #UUID because, clearly, automated processes are so last year. 🤖 Don't forget to outsmart WebFetch's 15-minute memory span, because who needs efficiency when you can generate endless unique URLs for every breath you take? 🚀
https://www.getadb.com/ #GETadb #redundancy #WebFetch #uniqueURLs #HackerNews #ngated -
🤡 Ah, the groundbreaking "GETadb" service—a true #innovation in redundancy! 🎉 Use your own random #UUID because, clearly, automated processes are so last year. 🤖 Don't forget to outsmart WebFetch's 15-minute memory span, because who needs efficiency when you can generate endless unique URLs for every breath you take? 🚀
https://www.getadb.com/ #GETadb #redundancy #WebFetch #uniqueURLs #HackerNews #ngated -
🚀 Ah, the classic tale of NASA’s grown-up game of #computer hopscotch, where eight #CPUs tiptoe around failure like a toddler dodging broccoli. 🙄 Who knew #redundancy could sound this thrilling? If only everyday #tech had this level of #excitement — or functionality, for that matter. 🤖✨
https://alearningaday.blog/2026/05/01/artemis-ii-fault-tolerance/ #NASA #science #HackerNews #ngated -
“A number of things were taken into account as we move towards proposing changes … #funding model changes, #regulatory environment, international student #downturn and so on – but also the reality that the #demand for courses in the Faculty of #Arts has changed,”
VS
“The chair of the inquiry, #DrSarahKaine, raised concerns about “sham redundancies” within the #FacultyOfArts because a number of #courses that had previously been taught by a #staff member who took a #redundancy are now being taught by #casuals
Those uppity clerks are getting out of control again.
#Academics / #Work / #MacquarieUniversity / #PhD / #RayGun 💃🧑🩰🩰 <https://smh.com.au/national/sydney-olympic-sensation-raygun-loses-academic-post-20260429-p5zs8n.html> / <https://archive.md/C2D6L>
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pfsync(4) Packet Header Field Renamed to Avoid AI Bug Report Noise https://www.undeadly.org/cgi?action=article;sid=20260413055845 #openbsd #pfsync #networking #redundancy #carp #pf #packetfilter #development #libresoftware #freesoftware
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Sydney mum-of-two has lost her senior news editor role at LinkedIn after 7 years—just 6 weeks post-maternity leave—due to the company's 'AI transformation'. Hit with the news at 1am, she felt the world fall out from under her. Sad fact: AI-driven redundancies are hitting Australia hard.
#AI #JobLoss #AITransformation #Australia #TechLayoffs #Redundancy
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Staff Photographers at The Washington Post All Lose Their Jobs https://petapixel.com/2026/02/05/staff-photographers-at-the-washington-post-all-lose-their-jobs/ #pressphotographers #staffphotographers #newsphotographers #thewashingtonpost #visualjournalists #picturedesk #redundancy #Industry #layoffs #layoff #News
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🚨 Breaking news from the Department of #Redundancy Department: An ICE agent filmed a video. The #BBC, in its infinite wisdom, offers zero useful details while displaying its ability to list every continent and political entity known to humankind. 🌎🗺️ Because who doesn't need a geography lesson with their news? 🙄
https://www.bbc.com/news/articles/cz7yv4524gqo #BreakingNews #ICEagent #GeographyLesson #HackerNews #ngated -
#HarshButFairComment | #IT's #Brutal; I #LikeIT...
#Whether you #LikeIT; #OrNot...
#Mastodon already #Fulfils #ITs #Original #DesignBrief...
#Adding more #FluffAndBullshit to #Satisfy an #Anonymous #UnqualifiedDemand for #NewFeatures will #Undermine any #Existing #GoodWill and #Strays into the #InvidiousWorld of #MissionCreeping #Redundancy
#TakeThatRisk #IF you #WantTo; #SeeWhatHappens...
🧙⚕️🤖:wolfparty:🤖⚕️🧙 | :PirateBadge:🦹:fediverse:🦄:fediverse:🦹:PirateBadge:
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#HarshButFairComment | #IT's #Brutal; I #LikeIT...
#Whether you #LikeIT; #OrNot...
#Mastodon already #Fulfils #ITs #Original #DesignBrief...
#Adding more #FluffAndBullshit to #Satisfy an #Anonymous #UnqualifiedDemand for #NewFeatures will #Undermine any #Existing #GoodWill and #Strays into the #InvidiousWorld of #MissionCreeping #Redundancy
#TakeThatRisk #IF you #WantTo; #SeeWhatHappens...
🧙⚕️🤖:wolfparty:🤖⚕️🧙 | :PirateBadge:🦹:fediverse:🦄:fediverse:🦹:PirateBadge:
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#HarshButFairComment | #IT's #Brutal; I #LikeIT...
#Whether you #LikeIT; #OrNot...
#Mastodon already #Fulfils #ITs #Original #DesignBrief...
#Adding more #FluffAndBullshit to #Satisfy an #Anonymous #UnqualifiedDemand for #NewFeatures will #Undermine any #Existing #GoodWill and #Strays into the #InvidiousWorld of #MissionCreeping #Redundancy
#TakeThatRisk #IF you #WantTo; #SeeWhatHappens...
🧙⚕️🤖:wolfparty:🤖⚕️🧙 | :PirateBadge:🦹:fediverse:🦄:fediverse:🦹:PirateBadge:
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#HarshButFairComment | #IT's #Brutal; I #LikeIT...
#Whether you #LikeIT; #OrNot...
#Mastodon already #Fulfils #ITs #Original #DesignBrief...
#Adding more #FluffAndBullshit to #Satisfy an #Anonymous #UnqualifiedDemand for #NewFeatures will #Undermine any #Existing #GoodWill and #Strays into the #InvidiousWorld of #MissionCreeping #Redundancy
#TakeThatRisk #IF you #WantTo; #SeeWhatHappens...
🧙⚕️🤖:wolfparty:🤖⚕️🧙 | :PirateBadge:🦹:fediverse:🦄:fediverse:🦹:PirateBadge:
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Genuinely sad to receive the news that #Zipcar is looking to wind up their UK operations by 31/12/2025.
Not just a miserable Christmas for their staff but a real buggeration to lose access to their vans - even if we didn't use it all that often often, we've had a business account subscription for ages for projects and emergencies. :(
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#AcademicVenting #Redundancy #Consultancy 🧵
But whilst I very much thought about “going into consultancy”, it’s not teasy when you don’t have an existing network; i found the permanent insecurity hard; and also kept on hearing stories of consultants, too, really struggling at the moment (AI part of this). Also by spring, more academic jobs were advertised again, and overall i felt I had to prioritise applications for more “permanent” jobs; i simply had no time to focus on consultancy -
"Modern civilisation has a number of extremely delicate and highly interconnected components whose graceful degradation is effectively impossible."
It is "much easier to break things than to build them up. The government administrations of Britain, France and Germany for example, were set up at a time in the nineteenth century when the rising middle classes demanded a properly functioning state[…]. It took perhaps a generation for professional, neutral public services to fully emerge."
"Forty years of globalised neoliberalism have broken our societies, our economies and our political systems, and we no longer have the ability to put them back together."
https://braveneweurope.com/aurelien-the-end
#civilService #statehood #bureaucracy #complexity #risk #digitalization #quantification #technocracy #quantitative #repair #mitigation #redundancy #resiliency #Deregulation #Economics #politics #EUPol #EU #Europe #institutions #institutionsDeceive #finance #globalisation #NeoLiberalism #Privatisation #technique #technoCriticism
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🚨 Breaking news for all the 🧠 enthusiasts out there: apparently, the question of whether #ketamine is neurotoxic requires endless scrolling through repetitive content loops. 🤯🔄 If you're looking for a deep dive into #redundancy, this article's got you covered! 🙄 Because who needs concise answers when you can navigate a labyrinth of recycled headers and filler text? 😂
https://desmolysium.com/ketamineneurotoxic/ #breakingnews #neurotoxicity #contentloops #humor #HackerNews #ngated -
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
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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
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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.
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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.
-
To #backup my family's 2 2TB #MacBook #MacBookPro #MacBookAir #M1 I use #timemachine & 4 Samsung 2B #T5 external SSDs : 2 on each machine for drive failure redundancy. This is not cheap & only ok while space permits & not sufficiently automatic while at home as it requires action to plug in drives to make a backup. Which 8TB #networkattachedstorage #NAS solution for automatic background backup only costs less than 800 € and has simple #redundancy against drive failure? Is #RAID even needed?
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Lessons Learned from a CubeSat Postmortem - On the 3rd of June 2019, a 1U CubeSat developed by students of the AGH University of Science and Tec... more: https://hackaday.com/2020/01/24/lessons-learned-from-a-cubesat-postmortem/ #failureanalysis #powermanagement #redundancy #hardware #cubesat #space