Nabil
1.6K posts

Nabil
@_ImNH
Building the future @Cloudorithms 🔮 RHCSA, OpenShift | Mobile & Backend Dev +5 years. @KAUST_Academy BI & AI ‘25 | Download https://t.co/kvTr0aSyfN now

كل الشكر والامتنان لـ @aag_lawyers على وقفتهم ودعمهم القانوني لـفريق Skooly ⚖️💙 فخورين بشركاء نجاح يملكون رؤية ملهمة في دعم الطلاب، وتمهيد الطريق للمشاريع الناشئة لتنافس بأعلى معايير الكفاءة والحماية في مسابقة إنجاز السعودية🇸🇦 #إنجاز_السعودية #ابتكار #تقنية

As a result of a US government directive, we are suspending access to Claude Fable 5 for all users. You can continue to use all other Claude models. Here’s what this means for you: Across Claude products, new sessions will run on your selected default model or Opus 4.8, and existing Fable 5 sessions will end with an error. On the Claude Platform, requests to Fable 5 will also return an error. Please update your integrations to other Claude models. We know this is a disruption to your workflows; we appreciate your patience and support.

As a result of a US government directive, we are suspending access to Claude Fable 5 for all users. You can continue to use all other Claude models. Here’s what this means for you: Across Claude products, new sessions will run on your selected default model or Opus 4.8, and existing Fable 5 sessions will end with an error. On the Claude Platform, requests to Fable 5 will also return an error. Please update your integrations to other Claude models. We know this is a disruption to your workflows; we appreciate your patience and support.

🚨 [New Paper] The Adam optimizer is a zombie algorithm... It senses and adapts the learning rate, sure. But the update rule itself? Fixed, frozen. Decided before even the training starts. It works in some regions of the loss landscape and fails in others. What if the optimizer itself was an agent, free to learn its own trajectory through the landscape and adjust its own update rule at every step? and maybe transfer its learned policy to train models on unseen datasets! Introducing: PILOT (Policy-Informed Learned OpTimizer) 📄Preprint: arxiv.org/abs/2605.24570 🧵TLDR 👇




Today, we share a breakthrough on the planar unit distance problem, a famous open question first posed by Paul Erdős in 1946. For nearly 80 years, mathematicians believed the best possible solutions looked roughly like square grids. An OpenAI model has now disproved that belief, discovering an entirely new family of constructions that performs better. This marks the first time AI has autonomously solved a prominent open problem central to a field of mathematics.





























