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→ nekoares: 「AI沒有錯!(笑)」 111.248.102.98 02/06 16:32 本版不缺 稻草人論證 99.99% 都如此 不見得AI有錯!!! -> 「AI沒有錯!(笑)」 某問:支持妓女有權做生意嗎? 我回:支持! -> 你一定去嫖過妓 推 SShirakawa: 建構式數學加上文字邏輯...好像台灣現 114.136.129.162 02/06 16:34 → SShirakawa: 在在教小朋友的那套啊 114.136.129.162 02/06 16:34 //// 推 stratuss: DeepSeek完全沒問題 220.137.205.44 02/06 17:31 → feelthat: DeepSeek一開始就以中文編碼中文問剛好 114.32.93.159 02/06 18:23 這裡有簡易版的gpt, bert chatbot model 稍微懂一點也就了解AI問題出在那了 https://tinkerd.net/blog/machine-learning/bert-embeddings/ // 會有這些問題的人 因為沒去理解chat ai model原理才會發生的 那說原因了 還有人不以為然 chatbot AI基本運作知識不足外 惡意嘲諷 現在我以另一種語文去問deepseek 答案與chatgpt 一樣 https://www.mediafire.com/view/kb5ifrk0xsvuy12/exdai00.png/file https://www.mediafire.com/view/wytqrtwxei1zf7f/exdai01.png/file 所以可以知道deepseek的運作方式 與 chatgpt 應該有相似之處 ※ 引述《feelthat (雲端傳送)》之銘言: : AI先用語言編碼再進神經網路最後歸納演算 : 請用英文問且 關鍵字 要正確 : calculate math 9.11-9.9 is? : ChatGPT 說: : The result of : 9.11 : 9.9 : 9.11.9 is: : 9.11 : 9.9 : = : 0.79 : 9.11.9=-.79 : //另一段 : I mean 9.11 - 9.9 = -0.79 but now 9.11 - 9.9 = 0.21 : maybe it's not decimal maybe some situation can you list? : ChatGPT 說: : Ah, I get it now! You're asking for scenarios where the result of : 9.11 : 9.9 : 9.11.9 could change from : 0.79 : .79 to : 0.21 : 0.21, which might not involve decimal arithmetic. Here's a list of : possibilities where such a situation could occur: : 1. Modulo Arithmetic : In modular arithmetic, results "wrap around" after reaching a certain value. : For example: : If we are working in modulo : 1 : 1, : 9.11 : 9.11 becomes : 0.11 : 0.11 and : 9.9 : 9.9 becomes : 0.9 : 0.9. : Subtraction : 0.11 : 0.9 : 0.11.9 in modulo : 1 : 1 gives : 0.21 : 0.21 (wrapping back around). : 2. Custom Number Systems or Scales : The subtraction is performed in a non-decimal number system, such as: : Base-12 (duodecimal): Numbers in different bases can yield results that don't : align with decimal subtraction. : Arbitrary scale adjustment: For example, : 9.11 : 9.11 and : 9.9 : 9.9 are values scaled by a factor or offset, changing the subtraction outcome. : 3. Signed vs. Unsigned Interpretation : If the numbers are stored as signed vs. unsigned integers in computer systems: : 9.11 : 9.9 : 9.11.9 could behave differently depending on how the system interprets : values. : Overflow or underflow in unsigned subtraction could result in a different : outcome. : 4. Error Correction or Adjustment Factor : The calculation might include a hidden correction factor or adjustment: : Some systems might add a constant adjustment to ensure positive results. : For example, a constant : + : 1 : +1 correction: : ( : 9.11 : 9.9 : ) : + : 1 : = : 0.21 : (9.11.9)+1=0.21 : 5. Quantum or Probabilistic Systems : In quantum computing or probabilistic algorithms: : Subtraction results might not be deterministic, allowing : 9.11 : 9.9 : 9.11.9 to : 0.21 : 0.21 in : 6. Time-Based Context : In specific contexts like timestamps: : 9.11 : 9.11 and ( 9.9 : 9.9 : 9.9 might represent : 7. Measurement Errors or Bias : In physical systems, results could change due to: : Mea : Bi : // : 9.11 - 9.9 = -0.79 but now 9.11 - 9.9 = 0.21 : maybe it's not decimal maybe some situation can you list? : ChatGPT 說: : Great catch! If : 9.11 : 9.9 : = : 0.21 : 9.11.9=0.21, then the numbers might not be in decimal form. Let's explore : potential scenarios where this could make sense: : 1. Base Systems (Non-Decimal) : Base 10 (Decimal): : 9.11 : 9.9 : = : 0.79 : 9.11.9=.79, as calculated initially. : Base 12 (Duodecimal): : 9.11 : 9.11 and : 9.9 : 9.9 are interpreted in base 12. : 9.11 : 12 : = : 9 : + : 1 : 12 : + : 1 : 144 : 9.11 : 12 : =9+ : 12 : 1 : + : 144 : 1 : 9.9 : 12 : = : 9 : + : 9 : 12 : 9.9 : 12 : =9+ : 12 : 9 : Subtraction could yield : 0.21 : 0.21 when converted to base 10. : 2. Time Format (Hours and Minutes) : Hours and Minutes: : 9.11 : 9.11 could mean 9 hours and 11 minutes. : 9.9 : 9.9 could mean 9 hours and 90 minutes (or 10 hours and 30 minutes). : Subtracting : 9 : 11 : 10 : 30 : 9:110:30 might give you : 0 : 21 : 0:21 (21 minutes). : 3. Measurement Systems : If : 9.11 : 9.11 and : 9.9 : 9.9 are part of a measurement system with specific units or rounding : conventions, the difference might result in : 0.21 : 0.21. : 4. Financial Rounding or Precision : In accounting or financial settings, numbers might be rounded or truncated : based on significant figures, giving a result of : 0.21 : 0.21. : // : 是我們想得太簡單 不見得AI有錯!!! : ※ 引述《bengowa (鞭狗蛙 舒服)》之銘言: : : 乳題啦 : : 我剛剛看到有人PO文說 : : 如果你去問chatgpt一個簡單的減法問題 : : 9.11-9.9=? : : 他會跟你說0.21 : : 我本來想說 幹怎麼可能 : : 結果測試後真的是這樣 : : https://imgur.com/6cQOyFC.jpg
: : 而且解釋後重複問他 他還是答錯 : : 笑死== -- ※ 發信站: 批踢踢實業坊(ptt.cc), 來自: 114.32.93.159 (臺灣) ※ 文章網址: https://www.ptt.cc/bbs/Gossiping/M.1738839150.A.C42.html
cs09312: 所以結論是chatgpt抄DS嗎 39.9.67.159 02/06 18:55
※ 編輯: feelthat (114.32.93.159 臺灣), 02/06/2025 19:06:11