Mohammad Fadl

PhD, Faculty of Education (EDT), E-Learning Developer, leads a talented team of Developers, Designers and Researchers

[Mohammad Fadl @iMohammadFadl]

مَن صَمَتَ ... نَجَا.

[Shining Science @ShiningScience]

Even the planet's most resilient desert survivors have started succumbing to extreme heat. Experts say it’s like nothing we’ve ever seen.

For centuries, camels have been celebrated as the ultimate 'ships of the desert,' renowned for their ability to thrive in arid environments too harsh for almost any other livestock. However, an escalating climate crisis in North Africa and the Horn of Africa is pushing these evolutionary marvels past their biological limits.

In regions like Ethiopia's scorching Afar desert, where summer temperatures frequently exceed 50°C (122°F), herders are witnessing unprecedented levels of suffering among their herds. Ali Umer, a veteran local camel herder, recently reported losing eight calves in a single month to the unrelenting heat.

He described a horrifying reality where the animals suffer from blistered feet and watery eyes, and the sand itself becomes so intensely hot that it burns their skin and singes their hair as they rest.

This crisis is not an isolated tragedy; it represents a systemic threat to the ecological and economic stability of communities that rely on camels for transport, milk, and meat. North and East Africa are home to approximately 80% of the world's dromedary camel population, and as traditional grazing areas dry up, pastoralist families are facing catastrophic losses.

Scientists and animal welfare experts warn that prolonged temperatures above the camels' comfort threshold compromise their immune systems, leaving them highly vulnerable to dehydration, disease, and death. With even the hardiest desert species struggling to survive, researchers are urging immediate interventions, such as strategic water distribution and emergency veterinary care, to prevent a total collapse of the region's agricultural backbone.

source: BBC News. (2026). Even camels can't cope: Africa's ships of the desert hit by rising temperatures.

[سعيد الكلباني @smalkalbani]

قصة 👇
رفض Google/ Apple ورجع للصين 🇨🇳

شاب صيني مواليد 1992
تخرج من جامعة تسينغهوا بتفوق، راح أمريكا يكمل دكتوراه في كارنيجي ميلون.. خلصها في 4 سنين

اشتغل في Google Brain و Meta AI، وساهم في أبحاث أساسية غيرت المجال مثل Transformer-XL و XLNet

لما خلص 2019
جاته ��روض ما تُرفض:
Apple تريده
Stanford و MIT يفتحوا له أبواب ما بعد الدكتوراه براتب ومكانة عالية..
رفض الكل ورجع الصين.

قال: (أبغى أبني AGI هنا) شاف إن الفرصة الحقيقية لصنع منظمة كبيرة قادرة توصل للذكاء الاصطناعي العام موجودة في بلده أكثر.

اليوم يانغ تشيلين (33 سنة) مؤسس ومدير تنفيذي لـ Moonshot AI، واحدة من أقوى شركات الـ AI الصينية.

الشركة جمعت مليارات الدولارات، ونموذجها الأخير (K3) اللي صدر بالأمس يُعتبر من أقوى النماذج المفتوحة عالمياً في السياق الطويل والتفكير المعقد، ويُنافس أقوى النماذج العالمية بموارد أقل بكثير حتى أنه أفضل من Fable 5 في بعض الجوانب

أحياناً النجاحات تبدأ برفض (الطريق السهل) واختيار الطموح الكبير في المكان المناسب

[Eye on Palestine @EyeonPalestine]

An Israeli soldier throws a stun grenade into a vehicle carrying several Palestinian young men after stopping it in the Qalandiya refugee camp.

[Qwen @Alibaba_Qwen]

📣📣 Meet Qwen-AgentWorld — a native language world model that simulates 7 agent environments (MCP, Search, Terminal, SWE, Web, OS, Android) within a single model. Environment modeling is the training objective from day one, not a post-hoc adaptation.

🤔 LLMs are trained to be better agents — better at acting in environments. But nobody has trained them to model the environments themselves.

🗺️ Our roadmap: investigate how language world modeling can push the boundaries of general agent capabilities, along two routes:

1️⃣ Build a foundation model for environment simulation — outperforming Claude Opus 4.8 and GPT-5.4 on AgentWorldBench

2️⃣ Investigate how world modeling enhances agent training:
🔬 Controllable Sim RL (agentic RL with LWM as environments) surpasses training in real environments
🧠 Learning to predict environments (LWM warm-up) makes agents stronger — remarkably, even without any agent-specific training, this predictive knowledge transfers to agentic tasks with zero fine-tuning

📑 Paper: https://t.co/Jx2l5RKq71
📖 Blog: https://t.co/7tVcKyhsx2
💻 GitHub: https://t.co/B5Lvb1UZCn
🤗 HuggingFace: https://t.co/Kw3QBL1TM5
🧩 ModelScope: https://t.co/YBnGYgMWWI

[Justin Poehnelt @JPoehnelt]

Two months ago I was fired by Google for creating the Google Workspace CLI. It went viral, hit #1 on Hacker News, gained thousands of GitHub stars and many thousands of actual users in just a couple days.

It was an incredible, confusing journey, from directors and leaders asking what they could learn from the tool to getting grilled by legal about why the Google logo and brand colors are on the Google Workspace GitHub code repositories.

I think the cause was that Workspace and certain leaders (and projects) were afraid of being disrupted. But the fear wasn't specific to my CLI, it was a broader fear in what agents meant for Workspace. Either way, the irony of my termination was the announcement at Google Cloud Next two days before I was fired that an official Workspace CLI was coming.

I want this out there because it is easier for me to explain my story and it is an experience I want to fully own. It's also part of my healing.

Nearly 7 years at Google was an incredible opportunity for me and I was fortunate to have wonderful teammates and a manager that fully supported me through these last few months. Thank you.

[Belal Fadl @belalfadl]

الأب هو ذلك الكائن الحي الذي لا يحب أحداً في الدنيا مثل أمه، ومع ذلك يتوقع طيلة الوقت أن يحبه أبناؤه أكثر من أمهم.
#سفاسف_الأمور

[Faheem Ullah @Faheem_uh]

PhD Students – How to identify related papers for your research paper?

1. Go to https://t.co/q2nnjqxKY8
2. Paste your DOI or title of your research paper
3. @ResearchCollab_ will display the network of papers
4. Explore the network in following ways

→ Filter the network of papers based on research field
→ Filter the network based on thematic clusters
→ Filter the network based on keywords
→ and much more

As you find related papers, keep saving them.

This use case has multiple advantages.

➟ You won’t miss a related paper to cite in your paper
➟ You can identify related papers for your lit review
➟ You can explore new research directions and trends
➟ You can visualize the entire collection of papers

As a researcher, work smarter not just harder.

For this, try ResearchCollab:

https://t.co/q2nnjqxKY8

[Y Combinator @ycombinator]

RASPIRE (@raspire_) is building app security at AI speed.

As AI accelerates mobile attacks, their platform protects Android and iOS apps from fraud, reverse engineering, and API abuse with zero code changes. They're already securing apps used by 20M+ people across banking, fintech, and healthcare.

Congrats on the launch, @EzV01d & @hsanmost!

https://t.co/0J7Sw3GOHe

[هند الخليفة @hend_alkhalifa]

#البحث_العلمي

صممت أداة https://t.co/HHloQRX0Jm الذكية من جامعة ستانفورد خصيصًا للباحثين في العلوم الاجتماعية والسياسية والاقتصاد وعلم النفس.

ارفع بياناتك، وحدد اتجاه بحثك، ودع #الذكاء_الاصطناعي يكتب لك ورقةً بحثية متكاملة وقابلة للتكرار في وقت قياسي.
https://t.co/cuse6hXC9X

[سامي بن عمر الحصيّن @w2me]

يقول مات لاركين أحد خبراء تقنيات التعليم في جامعة ميريلاند:

"قضيتُ بعض الوقت في قراءة هذه الورقة البحثية حول الذكاء الاصطناعي في التعليم العالي، ولفت انتباهي أن كثيراً من الجامعات لم تعد منشغلة بالسؤال التقليدي: هل ينتمي الذكاء الاصطناعي إلى التعليم أم لا؟ لقد تجاوزت هذه المرحلة، وأصبحت تفكر بجدية في كيفية دمجه بصورة مسؤولة وأخلاقية وعميقة داخل منظومة التعليم والتعلّم.

ما أعجبني في التقرير أنه لا ي��عامل مع الذكاء الاصطناعي بوصفه بديلاً سحرياً للتعليم، بل بوصفه طبقة داعمة تعزّز العملية التعليمية وتثريها.
فهو أداة قادرة على تخصيص التعلّم، وتقليل الأعباء المتكررة، وتحسين التغذية الراجعة، وخلق بيئات تعليمية أكثر تفاعلاً وحيوية، مع بقاء الإنسان وحكمه وخبرته في قلب العملية التعليمية.

ومن أبرز الأفكار التي استوقفتني:

▫���أن الجامعات بدأت تتجاوز مرحلة التجريب إلى بناء أطر حوكمة واضحة تعالج قضايا أخلاقيات الذكاء الاصطناعي، والخصوصية، والشفافية، والمساءلة.

▫️أن تطوير قدرات أعضاء هيئة التدريس أصبح لا يقل أهمية عن التقنية نفسها، إذ ما يزال كثير من المعلمين يحاولون اكتشاف أفضل السبل لدمج الذكاء الاصطناعي في ممارساتهم التعليمية بصورة فعّالة وذات معنى.

▫️أن عدداً متزايداً من الجامعات يعيد تصميم أساليب التقييم، متجهاً نحو المناقشات الشفهية، والمشاريع التطبيقية، والمحاكاة، وأنشطة التفكير النقدي، بدلاً من الاعتماد الحصري على المقالات التقليدية والاختبارات المعتادة.

▫���أن الذكاء الاصطناعي يُستخدم بشكل متنامٍ لتخصيص مسارات التعلم، وتقديم تغذية راجعة تكيّفية، ودعم الطلاب متعددي اللغات، والكشف المبكر عن المتعثرين أكاديمياً.

▫️أن هناك وعياً متزايداً بأن الطلاب لا يحتاجون فقط إلى الوصول إلى أدوات الذكاء الاصطناعي، بل إلى بناء ثقافة نقدية واعية تمكّنهم من فهم هذه الأدوات والتعامل معها بوعي ومسؤولية.

▫️المؤسسات التي تحقق تقدماً حقيقياً ليست تلك التي تنظر إلى الذكاء الاصطناعي بوصفه اختصاراً للطريق، بل تلك التي تراه فرصة لإعادة التفكير في تصميم التعلم من جذوره.

وهذا – في تقديري – هو التحول الأهم. لأن النقاش المستقبلي في التعليم العالي لن يتمحور حول مجرد تبني الذكاء الاصطناعي، بل حول كيفية إعادة تصميم تجارب التعلم، وأساليب التقييم، ونماذج دعم أعضاء هيئة التدريس، وطرق تفاعل الطلاب، في عالم أصبح الذكاء الاصطناعي جزءاً أصيلاً من بنيته اليومية.

كما أن استعراض تجارب جامعات من دول مختلفة عزّز لديّ قناعة مهمة: لا يوجد نموذج واحد تتجه إليه الجامعات في تعاملها مع الذكاء الاصطناعي. الجميع ما يزال في حالة تجريب وتعلّم وتكيّف مستمر، والجميع يحاول أن يفهم هذا التحول وهو يحدث أمامه في الوقت الفعلي."

[د. عبدالرحمن ذياب @dr2alshehri]

من الخبرات القوية جدًا في المجال الأكاديمي والبحثي — سواء كنت محاضر، معيد، أو دكتور — إنك تحصل على صفة Reviewer أو محكّم للأوراق العلمية في المجلات البحثية العالمية.

هذه الخطوة تعزز سيرتك الأكاديمية بشكل كبير، وتفيدك في الترقيات، وبناء العلاقات العلمية، وفهم طريقة تقييم ونشر الأبحاث الاحترافية.

إذا مهتم تبدأ بهذا المجال، فهذا الدليل يشرح لك كيف تقدم وتعمل كمراجع علمي مع مجلات عالمية محكّمة 👇🏼

https://t.co/3KLhwAeQOE

[سعيد الكلباني @smalkalbani]

88% من الشركات تستخدم الذكاء الاصطناعي.
لكن فقط 6% تحقق منه أثراً مالي حقيقي

المشكلة ما في الـ AI.
المشكلة في طريقة العمل نفسها.

تقرير McKinsey كشف الفارق:

55% من الشركات الناجحة أعادت تصميم طريقة العمل بالكامل حول AI.
بينما البقية اكتفت بإضافة AI فوق أنظمة قديمة.

وهنا الفرق:

🔻إذا وضعت AI داخل عملية سيئة ستحصل على نفس النتيجة… أسرع فقط.
🔺أما إذا أعدت بناء العملية من الأساس تتغير النتائج جذرياً.

الخلاصة
من يغيّر طريقة العمل ينضم إلى الـ 6%.
ومن يكتفي بإضافة أدوات جديدة… يبقى ضمن الـ 94%.

[هند الخليفة @hend_alkhalifa]

ترجمة لإطار الاستخدام المسؤول #الذكاء_الاصطناعي في #البحث_العلمي

[Chris @ChrisGPT]

I literally just watched GPT-5.5 via codex beat an Amazon customer associate in real time. 💀

I asked it to get me a refund, and I watched it navigate the settings, cancel the subscription, then it went step further into the help page.

I thought it was going to request a phone call (which would prompt me to take over)

Instead, it opened:

“Chat with an associate now.”

That’s when I sat up on my couch because I knew it was going to get real

The agent said:

“Your subscription is active.”

And GPT-5.5 immediately explained that it only shows as active because cancellation leaves access through the billing period, but that I wanted it stopped now and refunded.

And my jaw just hung open, it was the first time I watched sand handle a customer service agent for me in real time

Once the agent confirmed the refund, it just ended the chat no mercy no thank you LMAO

First time I’ve watched a human customer service agent get outmaneuvered by AI in real time.

And it made me 15$! almost paid for itself in 5 minutes

[Faheem Ullah @Faheem_uh]

PhD Students - How to create a scientific figure in seconds?

Follow these 3 simple steps.

1. Go to https://t.co/oefgTLjy0Z
2. From the left menu, select figure generation
3. Enter the requirements of your diagram.

- @NoahAITech will create a perfect figure for you.
- For creating figure, NOAH first searched the literature
- Then properly generated the figure.
- So, it’s grounded in research, not just drawing.
- You can download it as PNG.

The figures NOAH AI creates are not ordinary figures.

- It offers unique features
- Re-create figures based on upload image/data
- Matches the journal/visual style
- Keep consistency across diagrams
- Searches PubMed and related sources for figures
- Aligns visuals with users’ needs

Try it today for FREE:
https://t.co/oefgTLjy0Z

Every user gets a free quota to generate figures.

[Ihtesham Ali @ihteshamali]

An MIT professor taught the same math course for 62 years, and the day he retired, students from every country on earth showed up online to watch him give his final lecture.

I opened the playlist at 2am and ended up watching three of them back to back.

His name is Gilbert Strang. The course is MIT 18.06 Linear Algebra.

Every machine learning engineer, every data scientist, every quant, every self-taught programmer who actually understands how AI works learned the math from this one man. Most of them never set foot on MIT's campus. They just opened a free playlist on YouTube and let him teach.

Here's the story almost nobody tells you.

Strang joined the MIT math faculty in 1962. He retired in 2023. That is 61 years of standing at the same chalkboard teaching the same subject to 18-year-olds.

The interesting part is what he did when MIT launched OpenCourseWare in 2002. Most professors were skeptical. They worried that putting their lectures online would make their classrooms irrelevant. Strang did not hesitate. He said his life's mission was to open mathematics to students everywhere. He filmed every lecture and gave it away.

The decision quietly changed how the world learns math.

For decades linear algebra was taught the wrong way. Professors started with abstract vector spaces and proofs about field axioms. Students drowned in the abstraction. Most never recovered. They walked out believing they were bad at math when they had simply been taught in an order that nobody's brain is built to absorb.

Strang inverted the entire curriculum.

He started with matrix multiplication. Something you can write down on paper. Something you can compute by hand. Something you can see. Then he showed his students that everything else in linear algebra eigenvectors, singular value decomposition, orthogonality, the four fundamental subspaces was just a different lens for understanding what the matrix was actually doing under the hood.

His rule was strict. If a student could not explain a concept using a concrete 3 by 3 example, that student did not actually understand the concept yet. The abstraction was supposed to come last, not first. The intuition was the foundation. The proofs were just confirmation that the intuition was correct.

The second thing Strang changed was the classroom itself. He said please and thank you to his students. Every single lecture. He paused mid-derivation to ask "am I OK?" to check if anyone was lost. He never used the word "obviously" or "trivially" because he knew exactly what those words do to a student who is one step behind. He treated 19-year-olds learning math for the first time the way he treated his own colleagues. With patience. With respect. With the assumption that they belonged in the room.

For 62 years.

The result is something that has never happened in the history of education. A single math professor became the default teacher of his subject for the entire planet.

Universities in India, China, Brazil, Nigeria, every country with a computer science department, started telling their own students to just watch Strang's lectures. The University of Illinois revised its linear algebra course to do almost no in-person lecturing. The reason was honest. The professor said they could not compete with the videos.

His final lecture was in May 2023.

The auditorium was packed with students who had never met him before. He walked to the chalkboard, taught for an hour, and at the end the entire room stood and applauded. He looked confused for a moment, like he genuinely did not understand why they were cheering. Then he smiled and waved them off and walked out.

His written comment under the YouTube video of that final lecture was four sentences long. He said teaching had been a wonderful life. He said he was grateful to everyone who saw the importance of linear algebra. He said the movement of teaching it well would continue because it was right.

That was it. No book promotion. No farewell speech. No legacy management.

The man whose teaching is the foundation of modern AI just thanked the audience and went home.

20 million views. Zero ego. The entire engine of the AI revolution sits on top of math that millions of people learned for free from one quiet professor in Cambridge.

The course is still on MIT OpenCourseWare. Every lecture, every problem set, every exam, every solution. Free.

The most important math course of the 21st century is sitting one click away from you. Most people will never open it.

[Shahrukh Raza @ssraza21]

Bismillah. Introducing @ScribeTools 2.0 : THE platform to transform your documents (Arabic/Urdu/English/etc) into actual usable knowledge!

It unlocks centuries of knowledge and allows you to interact with them in any way possible: search it, copy/paste it, throw it into an LLM, or whatever else!

Link is below

[Rogério Tomaz Jr. @rogeriotomazjr]

Quantas gerações de incestos, estupros e outras práticas bizarras foram necessárias pra gerar esse bando de degenerados que atacam diariamente as famílias palestinas na Cisjordânia? Que coisa doentia é uma sociedade capaz de criar esse tipo de gente!

[سعيد الكلباني @smalkalbani]

Google لديها نموذج يستطيع كتابة ورقة بحثية كاملة

نشرت Google ورقة بحثية جديدة تدور فكرتها الرئيسية حولنظام ذكاء اصطناعي جديد يستطيع كتابة ورقة بحثية كاملة بشكل أفضل من الأنظمة السابقة.

▪️ما الذي درسته؟
كيف يمكن للذكاء الاصطناعي تحويل أفكار وتجارب أولية غير مرتبة إلى بحث علمي جاهز للنشر.
وهل يمكن أن يكتب البحث بجودة قريبة من الإنسان.

▪️كيف أجريت؟
•استخدم الباحثون بيانات من 200 ورقة علمية حقيقية.
•أعطوا الأنظمة “ملاحظات خام” (فكرة + نتائج تجارب).
•قارنوا بين عدة أنظمة لمعرفة أيها يكتب أفضل، باستخدام تقييم بشري وآلي.

▪️ماذا وجدت؟

•النظام الجديد تفوق على الأنظمة الأخرى بنسبة فوز وصلت إلى 50%–68% في جودة مراجعة الأدبيات، و14%–38% في جودة الورقة بشكل عام.

•حقق معدلات قبول افتراضية عالية في التقييم (حوالي 84% و81% في مؤتمرين).

•أنتج عدد مراجع أقرب للإنسان (حوالي 45–48 مرجعًا مقارنةً بـ ~59 في الأ��راق الحقيقية).

▪️الخلاصة
مستقبلاً، يمكن للباحثين ��ستخدام الذكاء الاصطناعي لمساعدتهم في كتابة الأبحاث بسرعة، بدل البدء من الصفر. لكن ما زال الإنسان ضروريًا للمراجعة والتأكد من صحة المعلومات.

[Motasem A Dalloul @AbujomaaGaza]

As part of psychological torture, Israeli captors told Palestinian hostage from Gaza Shadi abu Seido that his family and children had been bombed and killed..

He was shocked when he was released and found them alive..