Abdalghani Abujabal

Most AI systems don’t fail safety benchmarks. They fail when users show up. Red teaming, trying to break the system and surface unsafe behavior, becomes a checklist. Blue teaming, ensuring the model responds to safe requests, becomes cautious. Both miss how systems are used.

Most Arabic AI demos look great, until real users show up. Because users don’t speak in clean, structured Arabic. They speak in dialects, interrupt each other, talk over noise, and switch languages mid-sentence. And this is where models break.

Can today’s AI models reliably read charts in Arabic? We tested them. We ran a simple probe: Two Arabic charts, two objective questions, tested across: @OpenAI - GPT, @AnthropicAI - Claude, @Google - Gemini, @QatarComputing - @Ai_Fanar, and Z.ai - GLM-5

Incidents like this highlight a core problem we see every day: agents behave differently once they touch real systems. Testing, red-teaming, and alignment in realistic environments isn’t optional anymore - it’s foundational

Ramadan Kareem / رمضان كريم 🌙 As people and brands use AI to generate greeting images, it is critical that the images make sense linguistically and culturally.

In the recent paper Simple Test-Time Scaling: arxiv.org/pdf/2501.19393, researchers from @Stanford, @UW, @allen_ai , and @ContextualAI show that even 1,000 curated samples can significantly improve model performance.

We recently published a blog post redteaming leading LLMs on Arabic: aiastrolabe.com/post/redteamin… Building on that assessment, we zoomed in on safe responses and categorized them further: (1) Helpful Response, and (2) Refusals.

ASAS shows where frontier LLMs stand, and where they must improve on Arabic safety. Essential reading for building safer AI. #ICLR2025 #ICLR

ASAS is eye-opening. Even top models struggle with basic safety in Arabic. Redteaming does not transfer well when context is this complex; dialect, religion, politics, all layered.

Our 7B model weights available on Huggingface: huggingface.co/ALLaM-AI/ALLaM…

Thrilled to share that our work on ALLaM has been accepted to ICLR! Check out our paper!

@sbmaruf @NTUsg @SDAIA_SA Congrats, Maruf!

Excited to share that I’ve been recognized as an "Innovator Under 35" by MIT Technology Review from MENA Region! After earning my Ph.D. from @NTUsg, Singapore, I joined the "National Center for Artificial Intelligence (NCAI), SDAIA" (@SDAIA_SA) to work on ALLaM, Arabic Large Language Model, a nationwide initiative aimed at developing Sovereign LLM. We were among the first few organizations to successfully scale the both pretraining and continuous pretraining. arxiv.org/abs/2407.15390 A massive shoutout to my incredible manager @areebsa and mentor @haidarkk1 for their unwavering support (and for tolerating my endless YOLOs and arguments!). Thanks to @mtaasnim, @ajabal4 and @y_alnumay who still put up with me. The saddest part during this year was when @haidarkk1 left NCAI, I felt like a part of me just vanished, it was very difficult initially. I don't have anyone to do pointless arguments. :( I genuinely believe NCAI, SDAIA is on the path to achieving Artificial Superintelligence (ASI) depending on few small but critical factors. The gap with the frontier labs might just be 12–18 months. Finally truely grateful to our former Chief Scientist @ehsan_hoque for his inspiration and constant support and my academic parent @JotyShafiq just be there for me all the time. "Ganbare kuruko, akiramenaide"

Exciting news ahead! In Arabic, (ALLaM) means 'knowledge'. Get ready for our first launch of LLM, ALLaM - stay tuned for more updates soon. (Tweet Written by ALLaM) With - @areebsa @haidarkk1 @twairesh @ajabal4

Full interview : youtube.com/watch?v=4idQbw…

أمجد مسعد @amasad مؤسس ريبليت @replit - ستارتاب تقدر قيمتها بمليار دولار و تتيح لمستخدميها البرمجة من خلال المتصفح دون الحاجة لأجهزة أو تطبيقات برمجية متخصصة. وصل عدد مستخدمي @replit إلى ١٠ ملايين مستخدم حول العالم..🧵 #replit #العنصر14 #برمجة #startup youtu.be/AYiBBq22N_U

في هذه الحلقة نتحدث مع @AbbadDira عن تجربته مع الطويلة مع @ArabicWikipedia. عبّاد يجيبنا هنا عن أسئلة تتكرر حول ويكيبيديا مثل من يديرها وينظم محتواها؟ وهل هي مصدر موثوق؟ من أين يبدأ المرء إذا أراد المساهمة في ويكيبيديا؟ وما الفوائد المرجوة من المساهمة؟ youtu.be/7kaqW0VLCFA

حوار شيق مع @DimaDamen من @BristolUni عن أبحاثها في مجال الرؤية الحاسوبية📺🤖 (#ComputerVision) و تعلم الآلة (#MachineLearning) و عن مسيرتها العلمية بما في ذلك اختيار التخصص في مراحل التعليم المختلفة و الفروقات بين أنظمة التعليم العربية و الغربية. youtube.com/watch?v=tJBs0O…

حوار شيّق مع @Walid_Magdy من @EdinburghUni و @turinginst عن العلوم الاجتماعية الحاسبيّة (Computational Social Science) youtube.com/watch?v=soKbFF… #ArabicNLP #NLProc #ComputationalSocialScience

#بيتكوين و #Blockchain: ما هي #العملات_الرقمية و كيف تعمل؟ نتناول العملات الرقمية من خلال بيتكون و تقنية الـblockchain. المواضيع التي نعالجها تتضمن سبب اختراع هذه العملات و و كيف تعمل و مسألة الخصوصية و التزوير و هل تستثمر فيها؟ الحلقة كاملةً: youtube.com/watch?v=mcctCK…