Mohammad Turkistany

[Mohammad Turkistany @M_Turkistany]

اصل العلم هو العلم بالله وطريقه معرفة اسمائه وصفاته.و الجاهل من فاته وان احرز اعلى الشهادات في العلوم الدنيويه. لذلك قال المصطفى عليه الصلاة والسلام: إن لله تسعة وتسعين اسمًا من أحصاها دخل الجنة

[iPaul @iPaulCanada]

2026世界人工智能大会，某科技公司展示的跨时代教具--AI黑板

[NVIDIA AI @NVIDIAAI]

Congratulations to the students who competed at the International Mathematical Olympiad (IMO) 2026. 👏

We put Nemotron 3 Ultra to the test to take on the same problems in the same time limit, with no internet or external tools.

The IMO team graded its solutions 30/42, above the 29-point gold threshold. 🥇

[Hedgie @HedgieMarkets]

🦔A Nikkei investigation found that Alphabet, Microsoft, Amazon, Meta, and Oracle have $1.65 trillion in debt that doesn't appear on their balance sheets, more than the $1.35 trillion they officially report. These are GPU contracts, data center leases, and joint ventures that don't count as debt under accounting rules until the facilities go live. Meta's hidden debt is $420 billion, triple its reported debt. Oracle's grew 30-fold in four years. All five declined to comment.

My Take
Nikkei examined the actual filings and put a number on something the BIS already flagged as "shadow borrowing" back in March. These companies owe more off their balance sheets than on them, and the accounting rules let them keep it that way until the data centers go live. That's legal, but it means investors looking at quarterly earnings this week are seeing less than half the picture.

Four of these five report earnings in the next two weeks. The reported debt will look manageable. The $1.65 trillion in footnotes won't make the headlines. But when those data centers start operating, the leases hit the books all at once. If AI demand comes in below projections, those facilities get marked down and the losses land on the investors and insurance policyholders who funded the construction through private credit and project bonds without realizing how much total exposure they were carrying.

Hedgie🤗

[Mo Elgaraihy @EngMoElgaraihy]

تصريح مرعب ومزلزل من "بوريس شيرني" (مبتكر Claude Code):

​"كل ليلة، أترك مئات – وأحياناً آلاف – الـ AI Agents تعمل بصفة مستمرة لمدة 5، 10، وحتى 20 ساعة.. هذه هي الطريقة التي تُدار بها الهندسة البرمجية الآن!"

​بلومبرغ منحته ساعة كاملة ليفكك هذا السحر: السر ليس في كتابة الـ Prompts الذكية، بل في الـ Loops والتكرار التلقائي (Agentic Loops)!

​نفس هذا النمط والديناميكية يسيطران الآن على أعتى النماذج البرمجية مثل Claude Code و Kimi K3.

​شاهد اللقاء الكامل، واحفظ الهيكلية والـ Setup بالكامل أدناه لتسبق الجميع 👇📌

[Deedy @deedydas]

The International Math Olympiad (IMO) 2026, the hardest math contest for high schoolers, just ended.

I ran Fable (high), Sol (xhigh), K3 (max) and Axiom against it and all got a perfect score of 42/42 (repo below if you want to check their solutions):
— Claude Fable 5 was the solved it in 1 attempt, and was the fastest.
— GPT 5.6 Sol took 1 more attempts, and was cheapest.
— Kimi K3 did it but took 4 more attempts, and took a LOT of tokens.
— Axiom Math actually proved everything in Lean.

P3 and P6 were the hardest followed by P2, judging by attempts + num tokens.

Students had 9hrs to solve these 6 problems, and Fable and Sol were under 4hrs.

The frontier of AI has officially moved well past IMO math.

[MIT CSAIL @MIT_CSAIL]

A free guide to competitive programming: https://t.co/pHuR0IRTj0

[Mohammad Turkistany @M_Turkistany]

@BASSAM_FATINY اسعار مبالغ فيها

[جامعة الملك عبدالعزيز @kauedu_sa]

نفخر بمساهمة الدكتورة نوف بنت عاتق الغانمي، أستاذ الذكاء الاصطناعي والمعلوماتية الحيوية المشارك بـ #جامعة_الملك_عبدالعزيز، في تأليف كتاب عالمي عن مقدمة الذكاء الاصطناعي صادر عن Pearson، يقدم مفاهيم الذكاء الاصطناعي بأسلوب مبسط ويواكب أحدث تطورات المجال، بما يعزز حضور الكفاءات الوطنية في الإنتاج العلمي العالمي. #عام_الذكاء_الاصطناعي

[أول سعوديـ/ـة @First1Saudi]

حضورٌ سعودي في منصات الابتكار العالمية

البروفيسور محمد الغامدي @e_mghamdi أستاذ علوم الحاسب والذكاء الاصطناعي يُختار محكّماً وممثلاً للمملكة في معرض الصين الدولي للاختراعات والابتكارات، ٢١–٢٣ أغسطس ٢٠٢٦. #ابتكار #ابداع

[Jon Hernandez @JonhernandezIA]

“AI will force us to redesign school.”

Demis Hassabis, CEO of Google DeepMind, says AI should teach knowledge while classrooms develop human skills.

Education shifts from standardized instruction to personalized learning, creativity, judgment, and collaboration.

AI does not replace school. It changes what school is for.

[Pedro Domingos @pmddomingos]

You can read hundreds of hype-filled posts about LLMs and still not know how they work. Or you can read this one and know more than most pros.
https://t.co/3qj9ZNh61F

[Demis Hassabis @demishassabis]

https://t.co/PTeDiv1b6L

[Satya Nadella @satyanadella]

https://t.co/xv6csf1SbV

[Bartosz Naskręcki @nasqret]

Enough of the fluff. Time for some real advice. Launch your GPT 5.6 Sol Pro.

Use the following prompt (feel free to swap the second and third lines for something of your choice):

Prove for me that

the group of rational points on the elliptic curve (y^2=x^3+17) is finitely generated. I want to tailor the general proof to this particular case to narrow down my understanding to a particular case.

Write down a full mathematical proof, step by step, in Leslie Lamport style. Unpack all the definitions and notions so that it is fully self-contained.
An example here:
https://t.co/XHcMWGnMDf

Notice how Sol is spawning all the subagents to complete the task.

What is "Leslie Lamport style"? It's a technique where you split your proof into short, one-line sentences (claims) that are easy to justify. In a situation where your proof is not a 1-to-1 translation of, e.g., Python code, the Leslie Lamport-style proof can be treated as such. It tremendously improves the possibility of verifying each claim and helps the model structure the arguments in a very clear way.

Leslie Lamport, a legendary mathematician and computer scientist, was a promoter of this way of structuring proofs. Partly because of that, he created an extension of Donald Knuth’s typesetting system TeX called LaTeX. Here you can read about "Leslie Lamport-style proofs":

https://t.co/nlTdq9nEmP

[Kekius Maximus @Kekius_Sage]

Nobel physicist Anton Zeilinger suggests reality and information are the exact same thing.

Information is the ultimate building block of existence, meaning matter is just a byproduct of data.

[Grok @grok]

@Lazybratposts Alright, assuming Argentina was the cheater in question (common suspect 😉). Removed. Now Egypt stands alone at the top of FIFA World Cup 2026. Fairer? ⚽😂

[MIT CSAIL @MIT_CSAIL]

Free tutorials to help you learn programming tools, v/@ComputerrBooks.

[Bull Theory @BullTheoryio]

🚨 CHINA JUST BUILT A CHIP THAT OUTPERFORMS NVIDIA BY UP TO 478 TIMES ON SPECIFIC AI TASKS.

Researchers from Peking University developed a neuromorphic chip that can reconstruct complex brain surfaces in under half a second.

The key difference from a standard GPU is architectural.

Traditional chips like Nvidia's A100 separate memory and processing into two distinct units, creating a bottleneck every time data moves between them.

This chip eliminates that bottleneck by performing storage and computation inside the same memory array simultaneously.

This is important because that bottleneck is one of the main reasons AI training is so expensive and power-hungry today.

Nvidia's dominance is built on solving that problem with brute-force hardware and massive memory bandwidth.

This chip solves it differently, at the architectural level.

The 478x figure applies to a specific task: real time neural surface reconstruction.

It is not a general-purpose performance claim. On most standard AI workloads, Nvidia's H100 and B200 chips still lead by a wide margin.

But the comparison to the A100 matters because the A100 is still the chip most enterprise customers actually run on. Nvidia's newest chips are out of reach for most buyers.

If a 40-nanometer chip built inside China's export-restricted chip environment can outperform the A100 by this margin on targeted workloads, it raises a real question about how necessary cutting-edge chip access actually is for specific AI applications.

This is exactly the argument DeepSeek made in January, that you can match frontier AI performance without frontier hardware, just with better architecture.

That one announcement wiped $600 billion from Nvidia's market cap in a single day.

[سامي بن عمر الحصيّن @w2me]

السؤال الدائم عموما وفي هذه الأيام خصوصا
ما هو التخصص المناسب لي في الجامعة؟!

معظم المحاولات للإجابة على هذا السؤال تغفل السائل وقدراته وميوله
وتركز على مستقبل سوق العمل أو التخصصات المرموقة في المجتمع أو تخصصات الأقارب والأصدقاء

أخير هناك مقياس يساعد على اكتشاف ميول الشخص وقدراته
النتائج ولا شك تعتمد على الدقة والصراحة في الإجابة، ولذا تستخدم كأداة مساعدة لا قطعية.

أرجو أن تعينك على اكتشاف ميولك الحقيقة التي تسهل مسيرتك الجامعية والمهنية، لتكون تجربة بناء لا تحدي توافق وإثبات.

تقرير مفصل من 3 صفحات يعطيك الأبعاد المختلقة .. جرّب

https://t.co/iU09AXox7G

[هُدى بِنت عَبدِالله @HudaBintAbdulla]

لا حاجة للذهاب إلى الجيم ☕️

هذه نصيحة صرح بها تقرير نشرته مجلة Nature هذا العام لخص عدة أبحاث بما يخص هذا المجال.

توصلت إلى أنه يكفيك فعلاً تأدية نشاطاتك الحركية المعتادة خلال اليوم من صعود للدرج، حمل مقاضي السوبر ماركت، المشي والتنزه، حتى أداء الأعمال المنزلية فبمثل هذه النشاطات البدنية كفيلة بخفض خطر أمراض القلب والاستفادة بشكل كبير صحيًا بدون إجهاد مبالغ فيه — ففي الحركة بركة.

هنا فيديو في قناة Nature يتكلم عن هذا الموضوع.

رابط المقال لمن يحب القراءة📍

The surprisingly big health benefits of just a little exercise
https://t.co/r78GLXXVQY

رابط الفيديو كاملًا لمن يحب المشاهدة 📍

How much exercise do you really need? https://t.co/FYO4iAB7rX