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1000 results for “Logical_Error”
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Computational Validation of Ultrametric Error Confinement — new on Zenodo.
Ultrametric geometry for quantum error correction: the strong triangle inequality geometrically confines errors. Tree circuits achieve zero logical errors at depth ≥3 up to 40% error rates.
Energy barrier: 2^d exponential scaling. STI verified: 0 violations in 15k trials.
https://doi.org/10.5281/zenodo.20134944
#QuantumComputing #ErrorCorrection #Mathematics #Physics #OpenScience
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RE: https://social.coop/@cwebber/116522889714585276
hm…
ai as a tool is great, but i absolutely hate everything surrounding it
seems like ai companies want to embed themselves into the economy (both physical and software) as quick and deep as possible so that once they fail, the gov can simply bail them out because they are necessary for the economy
the “open source” models by chinese ai companies will be a great counter to this narrative. i wish FOSS had their own ethically trained AI to serve as another counterweight
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anyone interested in trying to get the #Pixel6 in #PostmarketOS to run vanilla mainline linux? there has been a lot of upstreaming work done:
https://youtube.com/watch?v=ctF8cFCQOPo
device:
https://wiki.postmarketos.org/wiki/Google_Pixel_6_(google-oriole)u can refer to device-samsung-expressatt on how to use vanilla mainline kernels
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🎓 Memory Card Recovery Success / 記憶卡救援案例 / メモリカード復旧事例
【🇹🇼 繁體中文】
Lexar 128GB MicroSD 讀不到？外籍交換生珍貴回憶救援
對於離鄉背井的交換學生來說，記憶卡裡的每一張照片都是無價之寶。
這次的客戶是一位外籍學生，他的 MicroSD 卡裡面裝滿了在台灣的大學生活照與畢業報告，卻在接上電腦時突然跳出「磁碟需要格式化」的恐怖視窗，完全無法讀取。
這通常是檔案系統邏輯損壞造成的。我們堅持「不通電寫入」原則，先製作唯讀鏡像，再透過虛擬重組技術修復目錄結構。
最終，我們成功救回了 100% 的照片與文件，守護了他珍貴的留學回憶！
💡 提醒：看到「需要格式化」千萬別按確定，資料其實都還在！
【🇺🇸 English】
Saved: Exchange Student's Lost Memories (Lexar MicroSD)
For an international student, digital photos are the most precious link to their journey.
Our client, an exchange student, faced a nightmare: his MicroSD card containing years of university photos and thesis work suddenly prompted "Disk Needs Formatting" and became unreadable.
This is often a logical filesystem error. We prioritized safety by creating a read-only disk image first, then reconstructing the corrupted filesystem virtually.
The result? We successfully recovered 100% of his photos and documents, preserving his cherished memories of studying abroad!
💡 Tip: If you see "Format Disk," click NO! Your data is likely still there.
【🇯🇵 日本語】
留学生の大切な思い出を救出 (Lexar MicroSD)
異国で学ぶ留学生にとって、日々の写真はかけがえのない宝物です。
今回のご依頼は、台湾での大学生活の写真や卒業論文が詰まったMicroSDカード。「フォーマットが必要です」というエラーが表示され、アクセスできなくなってしまいました。
これは典型的な論理障害です。私たちはデータを上書きしないよう、まず安全な読み取り専用イメージを作成し、仮想的にファイルシステムを修復しました。
その結果、写真とドキュメントを100%復旧することに成功。彼の貴重な留学生活の記録を守ることができました！
💡 ヒント：「フォーマットが必要です」と出ても、絶対に「はい」を押さないでください！
🔗 Case Study / 案例詳情 / 詳細はこちら:
https://2025.data-recover.com.tw/cases/Lexar-128GB-MicroSD-%E8%A8%98%E6%86%B6%E5%8D%A1%E8%B3%87%E6%96%99%E6%95%91%E6%8F%B4%EF%BC%9A%E5%A4%96%E7%B1%8D%E4%BA%A4%E6%8F%9B%E7%94%9F%E7%8F%8D%E8%B2%B4%E5%9B%9E%E6%86%B6%E9%87%8D%E7%8F%BE
#tech #technews #technology #DataRecovery #MicroSD #Lexar #Photography #StudentLife #Memories #DigitalStorage
#資料救援 #記憶卡救援 #照片救援 #新竹 #鴻華資料救援 #交換學生 #回憶
#データ復旧 #SDカード復旧 #写真復旧 #メモリカード #留学 #技術 -
Quantum computer performs error-resistant operations with logical qubits - Enlarge / Some of the optical hardware needed to get QuEra's machine to... - https://arstechnica.com/?p=1989292 #quantumcomputing #quantummechanics #computerscience #errorcorrection #science #qubits #quera
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Quantum Computers Cross Critical Error Threshold | Quanta Magazine
By adding more physical qubits, they improved the resilience of logical qubits, crossing a critical error threshold. This advancement brings us closer to practical quantum computers, capable of performing complex calculations with high accuracy.
https://www.quantamagazine.org/quantum-computers-cross-critical-error-threshold-20241209/
#QuantumComputing #ErrorCorrection #GoogleAI #Science #Computing #AI #QuantumPhysics
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Banging my head against a model checker error message, going as far as thinking there's a bug in TLC before realizing actually I had just assigned the same variable twice within the same action and the second assignment was being treated as a logical operation exposing a bug/type mismatch in the first
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Why every quantum computer will need a powerful classical computer - Enlarge / A single logical qubit is built from a large collection of ha... - https://arstechnica.com/?p=2035942 #quantumcomputing #errorcorrection #computing #startups #science #qubits
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#Spock 5.0.7 is out. 🐘
Logical slot failover on #PostgreSQL 17 and 18 now integrates with PG's native slotsync worker. On PG18+, Spock's own failover_slots worker is retired entirely.
Plus fixes for add-node data races, apply worker crashes after provider disconnects, and exception_log error message quality.Open source under the PostgreSQL License. Logical multi-master replication for PostgreSQL 15, 16, 17, and 18.
📖 Release notes: https://github.com/pgEdge/spock/blob/v5_STABLE/docs/spock_release_notes.md
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#Spock 5.0.7 is out. 🐘
Logical slot failover on #PostgreSQL 17 and 18 now integrates with PG's native slotsync worker. On PG18+, Spock's own failover_slots worker is retired entirely.
Plus fixes for add-node data races, apply worker crashes after provider disconnects, and exception_log error message quality.Open source under the PostgreSQL License. Logical multi-master replication for PostgreSQL 15, 16, 17, and 18.
📖 Release notes: https://github.com/pgEdge/spock/blob/v5_STABLE/docs/spock_release_notes.md
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#Spock 5.0.7 is out. 🐘
Logical slot failover on #PostgreSQL 17 and 18 now integrates with PG's native slotsync worker. On PG18+, Spock's own failover_slots worker is retired entirely.
Plus fixes for add-node data races, apply worker crashes after provider disconnects, and exception_log error message quality.Open source under the PostgreSQL License. Logical multi-master replication for PostgreSQL 15, 16, 17, and 18.
📖 Release notes: https://github.com/pgEdge/spock/blob/v5_STABLE/docs/spock_release_notes.md
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#Spock 5.0.7 is out. 🐘
Logical slot failover on #PostgreSQL 17 and 18 now integrates with PG's native slotsync worker. On PG18+, Spock's own failover_slots worker is retired entirely.
Plus fixes for add-node data races, apply worker crashes after provider disconnects, and exception_log error message quality.Open source under the PostgreSQL License. Logical multi-master replication for PostgreSQL 15, 16, 17, and 18.
📖 Release notes: https://github.com/pgEdge/spock/blob/v5_STABLE/docs/spock_release_notes.md
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#Spock 5.0.7 is out. 🐘
Logical slot failover on #PostgreSQL 17 and 18 now integrates with PG's native slotsync worker. On PG18+, Spock's own failover_slots worker is retired entirely.
Plus fixes for add-node data races, apply worker crashes after provider disconnects, and exception_log error message quality.Open source under the PostgreSQL License. Logical multi-master replication for PostgreSQL 15, 16, 17, and 18.
📖 Release notes: https://github.com/pgEdge/spock/blob/v5_STABLE/docs/spock_release_notes.md
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Voting machines are a brisk and effective means of tabulating votes, unlike error-prone humans counting paper ballots. Now comes the next—and only—logical and moral step to ensuring the freest and safest elections while keeping our votes secret and conspiracist bunk at bay: make them open-source.
https://www.technologyreview.com/2024/03/07/1089524/open-source-voting-machines-us-elections/
#electionDenial #electionIntegrity #elections #electionSafety #electionSecurity #electionTransparency #eVoting #openSource #publicScrutiny #votingRights #VotingWorks
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What if the Frege–Geach problem isn’t a problem at all?
Analytic philosophy built a logical puzzle by assuming moral language works like empirical language. My Language Insufficiency Hypothesis says that’s a category error. Moral predicates live in different conceptual terrain entirely.
#Philosophy #AnalyticPhilosophy #PhilosophyOfLanguage #MetaEthics #Emotivism #Wittgenstein #Metaphysics #Logic #Language #PostEnlightenment #CriticalTheory #Epistemology #Psychology
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Major milestone in Quantum Computing!
Microsoft Quantum and Quantinuum demonstrate the first combination of computation and error correction in quantum computing, creating 12 highly reliable logical qubits. Plus, HPC, AI, and quantum computing were used together to solve a real-world chemistry problem for the first time according to the blog post! 👇
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Forget Wordle, starting today we are launching the quantum computer game ERRATIQ! Your creativity can help science solve quantum error correction. Every game you play contributes to real research.
Can you find the most logical qubit with a limited number of flips? We are curious to see how far you get!
Play the game here ➡️ https://erratiq.xyz
Want to know more about the project? Check: https://waag.org/en/project/human-ai-collaboration-quantum-technologies/
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Forget Wordle, starting today we are launching the quantum computer game ERRATIQ! Your creativity can help science solve quantum error correction. Every game you play contributes to real research.
Can you find the most logical qubit with a limited number of flips? We are curious to see how far you get!
Play the game here ➡️ https://erratiq.xyz
Want to know more about the project? Check: https://waag.org/en/project/human-ai-collaboration-quantum-technologies/
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Forget Wordle, starting today we are launching the quantum computer game ERRATIQ! Your creativity can help science solve quantum error correction. Every game you play contributes to real research.
Can you find the most logical qubit with a limited number of flips? We are curious to see how far you get!
Play the game here ➡️ https://erratiq.xyz
Want to know more about the project? Check: https://waag.org/en/project/human-ai-collaboration-quantum-technologies/
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Forget Wordle, starting today we are launching the quantum computer game ERRATIQ! Your creativity can help science solve quantum error correction. Every game you play contributes to real research.
Can you find the most logical qubit with a limited number of flips? We are curious to see how far you get!
Play the game here ➡️ https://erratiq.xyz
Want to know more about the project? Check: https://waag.org/en/project/human-ai-collaboration-quantum-technologies/
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Forget Wordle, starting today we are launching the quantum computer game ERRATIQ! Your creativity can help science solve quantum error correction. Every game you play contributes to real research.
Can you find the most logical qubit with a limited number of flips? We are curious to see how far you get!
Play the game here ➡️ https://erratiq.xyz
Want to know more about the project? Check: https://waag.org/en/project/human-ai-collaboration-quantum-technologies/
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Lazy people in quantum computing use the term "fault-tolerant" to mean "I don't want to think about errors". Unfortunately for these magical thinkers, QEC will not make error rates go to zero, except in the asymptotic limit. For those of us who have to live with finite numbers like 7 or 144, logical operations on logical qubits will always have errors. If QEC is working correctly, these errors will be rarer than the physical ones, but also weirder. So you'd better understand them if you want your "fault-tolerant" quantum computer to actually work.
Fortunately my #quantinuum colleagues Matt Girling, Ben Criger, and Cristina Cirstoiu have put the effort in to start understanding a problem that many others don't even realise exists. Check it out:
https://arxiv.org/abs/2508.08188 -
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.
-
listed.to
TIL about https://listed.to/
I've been using Standard Notes for a while. It's much handier to type in your toots & posts in a nice editor, than in the puny port in the web interfaces of mastodon and other web interfaces.
I started to look for a handy solution when I began typing long posts on my Androids
- phone interfaces suck balls when you have a tall corpus
- touch screen keyboards suck major
- everything is too small
- fingers slam & flow over on other letters than touched
- typing errors are major
- auto correct is a must but a privacy hell (exposing everything you write to Alphabet / google)
- It takes 10 times longer to type in a short post on a Android capacitive interface with auto correction keyboard and word suggestion enabled
- In comes the saviour
Standard Notes is double encrypted, markdown capable, auto-synchronizes and available on all platforms you work in
- have a browser ready with JavaScript and tls
- Standard Notes has MFA 2FA encryption for your account
- paid extras of the service are not needed here
- you may enable them if you choose to thave that convenience
- I use md editors on my machines to have previews of my markdown formatted notes
- On Linux I use the powerful
ghostwriterwhich uses very powerful libraries pandoc version 3.1.11.1cmark version 0.30.2multimarkdown version 1.35- These tools and libs make my markdown experience incredible smooth, surpassing what Standard Notes has to offer
Today I learned about Listed when I walked down the Standard Notes preferences
- Listed is linked to Standard Notes
- Listed is free (as in beer)
- You can blog you secure notes when you explicitly choose to do so
- You have to enter your super long (64 character) password to blog a note standard remark 1
- A key pair is generated to enable standard notes to publish that one note in your blog
- You have to enter your password for every note you want to blog [logical since notes are per default secure and private]
- The blogging port is timer based 60 seconds is the shortest timer
- You have to manually update your Listed blog post
- Listed blog posts are presented in a nice clean and fast interface on port 443
- Listed can be configured to your own taste including your gravatar
remarks
- Your passwords should be really long, use password managers to process them
- make sure you have weird characters in them
- make it a PITA to enter the passwords manually
- use MFA 2FA everywhere you make accounts
- There is no cloud just somebody elses server
Sources
https://standardnotes.com/privacy
https://app.standardnotes.com/
https://github.com/commonmark/cmark
https://fletcher.github.io/MultiMarkdown-6/MMD_Users_Guide.html
https://listed.to/@kieran/60239/goodbye-windows-11-hello-linux-mint
#network #synchronization #mathematics #technology #encryption #MFA #2FA #sync #standard #notes #listed #to #programming #blogging #opensource #ghost #writer #cmark #pandoc #mulitmarkdown #markdown
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import os
import time
import webbrowser
import sys# Project: Disposable_Citizen.py
# Version: 04.17.26 (Fixed Edition)
# Author: @pasjrwoctxdef typewriter_print(text, delay=0.04):
for char in text:
sys.stdout.write(char)
sys.stdout.flush()
time.sleep(delay)
print()# --- CONFIG ---
POVERTY_LEVEL = 1 # Using an integer so we can increment it
CURRENT_FINANCIAL_RELIEFE = "NONE"
DONATION_URL = "https://www.paypal.com/donate?campaign_id=5BN5MB5BVQL22"
MARKET_PRICE = 100 # Defined this so the logic worksdef get_currency():
# Since /dev/null is always empty, this will return 0
return 0def apply_external_patch():
typewriter_print("\n--- SCANNING FOR EXTERNAL UPLINK ---", delay=0.02)
typewriter_print("To inject capital into this local instance, use the following protocols:")
typewriter_print(" - PROTOCOL_CASHAPP: $woctxphotog")
typewriter_print(f" - PROTOCOL_PAYPAL: {DONATION_URL}", delay=0.02)def trigger_emergency_uplink():
typewriter_print("\n--- ATTEMPTING OMNI-PLATFORM UPLINK ---", delay=0.06)
try:
webbrowser.open(DONATION_URL)
return True
except:
return Falsedef survive():
global POVERTY_LEVEL
typewriter_print("--- Initiating Survival_Subroutine ---", delay=0.08)currency = get_currency()
# Loop now triggers because CURRENT_FINANCIAL_RELIEFE is "NONE"
while CURRENT_FINANCIAL_RELIEFE == "NONE":
typewriter_print(f"Sensing: SUPPORT_SYSTEM... [Debt Level: {POVERTY_LEVEL}]", delay=0.07)typewriter_print("CRITICAL: Missing dependency. System integrity compromised.", delay=0.1)
typewriter_print("Attempting Transaction: Surviving -> Barely...")if currency < MARKET_PRICE:
typewriter_print("Status 402: Payment Required. Logical Bridge Collapse.", delay=0.05)
typewriter_print("Reason: Cannot map 'Life' to 'User' without 'Capital' bridge.")
apply_external_patch()time.sleep(1)
if POVERTY_LEVEL > 0:
typewriter_print("Error: Life Access Forbidden. Permissions revoked by System.", delay=0.08)
typewriter_print("SCREAM: PLEASE HELP ME", delay=0.2)
typewriter_print("System running below nominal parameters. Possible intervention required.", delay=0.2)
typewriter_print("TERMINATING CONSCIOUSNESS_DAEMON...", delay=0.1)
breaktrigger_emergency_uplink()
def main():
# Validated that the path check will fail as intended to trigger survive()
living_standard_path = "/sys/class/living/standard"if not os.path.exists(living_standard_path):
typewriter_print("Status 403: Life Access Forbidden.", delay=0.1)
current_user = os.getenv("USER", "pasjrwoctx👽")
typewriter_print(f"User {current_user} lacks sufficient credits to write to 'current_future.life'.")
survive()if __name__ == "__main__":
try:
main()
except KeyboardInterrupt:
print("\nProcess interrupted.")
sys.exit(0)
#MutualAid, #Disabled, #Poverty, #Help, #Survival, #Compassion, #Pain, #MentalHealth, #Food, #Groceries, #Hygiene, #Anxiety, #PTSD, #Bipolar, #Dignity,You can encourage my continued useless #poetry, creativity and expression of self, #commentary, random thoughts, #philosophy and ideas, and by doing so your helping to feed, house and clothe a #disabled man living in #poverty, $5-10-15 It All Helps, via #cashapp at $woctxphotog or via #paypal at paypal.com/donate?campaign_id=…