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Global • 2026-10-31, 01:47 GMT • ~1 min read

AI models may have disproved a decades-old computing hypothesis, scientists say

اے آئی ماڈلز نے کمپیوٹنگ کا دہائیوں پرانا مفروضہ غلط ثابت کر دیا ہو، سائنسدانوں کا کہنا

एआई मॉडल ने दशकों पुरानी कंप्यूटिंग परिकल्पना को गलत साबित कर दिया हो, वैज्ञानिकों का कहना

AI models may have disproved a decades-old computing hypothesis, scientists say

Key points

اہم نکات

मुख्य बातें

  • OpenAI and Anthropic each said on Monday that one of their AI models had disproved the exponential time hypothesis, an idea about the limits of computing proposed around 25 years ago by Russell Impagliazzo and Ramamohan Paturi of the University of California San Diego.
  • The hypothesis holds that some problems are so hard that computers can only solve them by trying nearly every possible answer, and hundreds of studies in computer science and biology rely on it.
  • The three researchers behind the idea, Impagliazzo, Paturi and MIT's Ryan Williams, a long-time sceptic, are now helping organise an independent review of the companies' claims.
  • اوپن اے آئی اور اینتھروپک نے پیر کو کہا کہ ان کے ایک اے آئی ماڈل نے ایکسپونینشل ٹائم ہائیپوتھیسس کو غلط ثابت کر دیا ہے، جو کمپیوٹنگ کی حدود کے بارے میں ایک خیال ہے جسے تقریباً 25 سال پہلے یونیورسٹی آف کیلیفورنیا سان ڈیاگو کے رسل امپاگلیازو اور راماموہن پٹوری نے پیش کیا تھا۔ اس مفروضے کے مطابق کچھ مسائل اتنے مشکل ہیں کہ کمپیوٹر انہیں صرف تقریباً ہر ممکنہ جواب آزما کر ہی حل کر سکتے ہیں، اور کمپیوٹر سائنس اور حیاتیات کی سیکڑوں تحقیقات اسی پر انحصار کرتی ہیں۔ اس خیال کے پیچھے تین محققین، امپاگلیازو، پٹوری اور ایم آئی ٹی کے ریان ولیمز، جو طویل عرصے سے اس پر شک کرتے رہے ہیں، اب کمپنیوں کے دعووں کا آزادانہ جائزہ لینے میں مدد کر رہے ہیں۔ ردعمل ملے جلے تھے: پٹوری نے اسے حیران کن کہا لیکن کہا کہ اس خیال پر بنی تحقیق ختم نہیں ہوگی، ولیمز نے خود کو درست ثابت محسوس کیا، اور امپاگلیازو نے کہا کہ وہ کسی انسان کی دریافت کو ترجیح دیتے جس سے وہ ہاتھ ملا سکتے۔ اگر یہ نتیجہ درست ثابت ہوا تو روزمرہ زندگی فوراً نہیں بدلے گی، لیکن آگے چل کر زیادہ موثر کمپیوٹنگ اور بہتر ڈیٹا تجزیے کے اوزار مل سکتے ہیں۔
  • ओपनएआई और एंथ्रोपिक ने सोमवार को कहा कि उनके एक एआई मॉडल ने एक्सपोनेंशियल टाइम हाइपोथिसिस को गलत साबित कर दिया है, जो कंप्यूटिंग की सीमाओं के बारे में एक विचार है जिसे लगभग 25 साल पहले कैलिफोर्निया विश्वविद्यालय सैन डिएगो के रसेल इम्पाग्लियाज़ो और रामामोहन पटूरी ने पेश किया था। इस परिकल्पना के अनुसार कुछ समस्याएँ इतनी कठिन हैं कि कंप्यूटर उन्हें लगभग हर संभव उत्तर आज़माकर ही हल कर सकते हैं, और कंप्यूटर विज्ञान और जीव विज्ञान के सैकड़ों अध्ययन इसी पर निर्भर हैं। इस विचार के पीछे तीन शोधकर्ता, इम्पाग्लियाज़ो, पटूरी और एमआईटी के रयान विलियम्स, जो लंबे समय से इस पर संदेह करते रहे हैं, अब कंपनियों के दावों की स्वतंत्र समीक्षा आयोजित करने में मदद कर रहे हैं। प्रतिक्रियाएँ मिली-जुली थीं: पटूरी ने इसे आश्चर्यजनक कहा लेकिन कहा कि इस विचार पर बना शोध खत्म नहीं होगा, विलियम्स को लगा कि वे सही साबित हुए, और इम्पाग्लियाज़ो ने कहा कि वे किसी मानव की खोज को प्राथमिकता देते जिससे वे हाथ मिला सकते। यदि यह परिणाम सही साबित हुआ तो दैनिक जीवन तुरंत नहीं बदलेगा, लेकिन आगे चलकर अधिक कुशल कंप्यूटिंग और बेहतर डेटा विश्लेषण उपकरण मिल सकते हैं।

OpenAI and Anthropic each said on Monday that one of their AI models had disproved the exponential time hypothesis, an idea about the limits of computing proposed around 25 years ago by Russell Impagliazzo and Ramamohan Paturi of the University of California San Diego. The hypothesis holds that some problems are so hard that computers can only solve them by trying nearly every possible answer, and hundreds of studies in computer science and biology rely on it. The three researchers behind the idea, Impagliazzo, Paturi and MIT's Ryan Williams, a long-time sceptic, are now helping organise an independent review of the companies' claims. Reactions were mixed: Paturi called it a surprise but said the research built around the idea would not disappear, Williams felt vindicated, and Impagliazzo said he would have preferred a human discovery he could shake hands with. If confirmed, the result would not change daily life at once, but could eventually lead to more efficient computing and better data-analysis tools.

اوپن اے آئی اور اینتھروپک نے پیر کو کہا کہ ان کے ایک اے آئی ماڈل نے ایکسپونینشل ٹائم ہائیپوتھیسس کو غلط ثابت کر دیا ہے، جو کمپیوٹنگ کی حدود کے بارے میں ایک خیال ہے جسے تقریباً 25 سال پہلے یونیورسٹی آف کیلیفورنیا سان ڈیاگو کے رسل امپاگلیازو اور راماموہن پٹوری نے پیش کیا تھا۔ اس مفروضے کے مطابق کچھ مسائل اتنے مشکل ہیں کہ کمپیوٹر انہیں صرف تقریباً ہر ممکنہ جواب آزما کر ہی حل کر سکتے ہیں، اور کمپیوٹر سائنس اور حیاتیات کی سیکڑوں تحقیقات اسی پر انحصار کرتی ہیں۔ اس خیال کے پیچھے تین محققین، امپاگلیازو، پٹوری اور ایم آئی ٹی کے ریان ولیمز، جو طویل عرصے سے اس پر شک کرتے رہے ہیں، اب کمپنیوں کے دعووں کا آزادانہ جائزہ لینے میں مدد کر رہے ہیں۔ ردعمل ملے جلے تھے: پٹوری نے اسے حیران کن کہا لیکن کہا کہ اس خیال پر بنی تحقیق ختم نہیں ہوگی، ولیمز نے خود کو درست ثابت محسوس کیا، اور امپاگلیازو نے کہا کہ وہ کسی انسان کی دریافت کو ترجیح دیتے جس سے وہ ہاتھ ملا سکتے۔ اگر یہ نتیجہ درست ثابت ہوا تو روزمرہ زندگی فوراً نہیں بدلے گی، لیکن آگے چل کر زیادہ موثر کمپیوٹنگ اور بہتر ڈیٹا تجزیے کے اوزار مل سکتے ہیں۔

ओपनएआई और एंथ्रोपिक ने सोमवार को कहा कि उनके एक एआई मॉडल ने एक्सपोनेंशियल टाइम हाइपोथिसिस को गलत साबित कर दिया है, जो कंप्यूटिंग की सीमाओं के बारे में एक विचार है जिसे लगभग 25 साल पहले कैलिफोर्निया विश्वविद्यालय सैन डिएगो के रसेल इम्पाग्लियाज़ो और रामामोहन पटूरी ने पेश किया था। इस परिकल्पना के अनुसार कुछ समस्याएँ इतनी कठिन हैं कि कंप्यूटर उन्हें लगभग हर संभव उत्तर आज़माकर ही हल कर सकते हैं, और कंप्यूटर विज्ञान और जीव विज्ञान के सैकड़ों अध्ययन इसी पर निर्भर हैं। इस विचार के पीछे तीन शोधकर्ता, इम्पाग्लियाज़ो, पटूरी और एमआईटी के रयान विलियम्स, जो लंबे समय से इस पर संदेह करते रहे हैं, अब कंपनियों के दावों की स्वतंत्र समीक्षा आयोजित करने में मदद कर रहे हैं। प्रतिक्रियाएँ मिली-जुली थीं: पटूरी ने इसे आश्चर्यजनक कहा लेकिन कहा कि इस विचार पर बना शोध खत्म नहीं होगा, विलियम्स को लगा कि वे सही साबित हुए, और इम्पाग्लियाज़ो ने कहा कि वे किसी मानव की खोज को प्राथमिकता देते जिससे वे हाथ मिला सकते। यदि यह परिणाम सही साबित हुआ तो दैनिक जीवन तुरंत नहीं बदलेगा, लेकिन आगे चलकर अधिक कुशल कंप्यूटिंग और बेहतर डेटा विश्लेषण उपकरण मिल सकते हैं।

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