Khaled Al-Shamaa

Wrapping up the year grateful for an inspiring work environment and an incredible global team. Learning every day from colleagues across Chile, Mexico, Spain, Morocco, Italy, Senegal, India, and beyond. Different cultures, one shared purpose. Onward to an even stronger year ahead

New course: Spec-Driven Development with Coding Agents, built in partnership with @jetbrains, and taught by @paulweveritt. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track! deeplearning.ai/short-courses/…

🧬 Deploying genomic AI just got easier The NVIDIA Evo 2 NIM microservice is now live on Amazon SageMaker AI. If you're building in bioinformatics, you can instantly spin up this foundation model to map DNA sequences to protein functions - all with zero infrastructure overhead on AWS's fully managed environment. 🧵 ⬇️

I just published Don’t Perish! A Step-by-Step Guide to Writing a Scientific Paper (2026 edition) Great science deserves to be read—not buried under unclear writing. This is the updated 2026 edition of your favorite guide to writing scientific papers. medium.com/p/dont-perish-…

We use NDVI to read plant health 🌱 Now imagine reading human health the same way. Light-based glucose monitoring using near infrared spectral fingerprint = no more finger pricks 🤯 Let’s get this into smartwatches fast⌚

L'annessione della Cisgiordania, con i soldati complici dei coloni. Gaza annientata. L'avanzata in Libano. Il confine violato in Siria. La guerra all'Iran. Pulizia etnica e massacri. Così la destra sionista dà forma al Grande Israele Il numero de L’Espresso, in edicola e su app

دليل شامل للمستقلين وأصحاب المشاريع حول كيفية العمل بفعالية على منصة مستقل. من إعداد الملف الشخصي وحتى اختيار العروض وتنفيذ المشاريع. blog.mostaql.com/how-to-use-mos… #مستقل

Beirut’s hospitals are posting photos of children — hoping someone will recognise them and identify their parents. I told @PiersUncensored: this is what Israel’s wars looks like — 100 air raids on 🇱🇧 within minutes, immediately after Netanyahu heard of a U.S. ceasefire announcement. Lebanon, the jewel of the Arab world, endures. When is enough, enough? America must stop fighting Israel’s genocidal wars. 🔗 Full interview: youtu.be/OH1JAoOkRpM?si…

A clean energy future begins w/ a better knowledge of our resources. WMO supports countries develop highres 🍃☀️💧 power atlases to help decision-makers better understand renewable energy potential & make informed choices on energy planning & investment. 📗library.wmo.int/idurl/4/69779

Opus want to go to sleep :D (it is also mess wrote, sure what is going on)

Artemis II astronauts have traveled 252,756 miles from Earth, flown around the Moon, and observed the lunar surface like never before. Now, they’re coming home. 🌎 Watch the crew splash down on Friday, April 10, around 8:07pm ET (0007 UTC April 11). nasa.gov/ways-to-watch/

نعم تحصل، هذه مقابلة قديمة للمديفر مع رجل الأعمال الكويتي محمد الشارخ الله يرحمه، واللي يُعد أول من أدخل اللغة العربية في عالم الحوسبة. هذا كلامه كيف شركة مايكروسفت سنة 90 سرقت موظفينه عشان تعريب الويندوز. لاحظ رغم كل هذا في حديثه كمية النبل والتفهم من قبله للموظفين.

*Finally* read through @samwhoo's blog on LLM quantization. It's incredible. For many (even in tech) the understanding of how LLMs work stops at the surface level. Sam is helping us all go deeper, digging into the interesting facets of how AI models truly work. Read it!

Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.

Recently I wrote these articles, and you all really loved the simplifications. - Math behind Attention - Q, K, and V - Math behind √dₖ Scaling Factor in Attention - Math Behind Backpropagation What topic should I simplify next? X is a knowledge sharing platform.

We are releasing Falcon Perception, an open-vocabulary referring expression segmentation model. Along with it, a 0.3B OCR model that is on par with 3-10x larger competitors. Current systems solve this with complex pipelines (separate encoders, late fusion, matching algorithms). We developed a novel simpler "bitter" approach: one early-fusion Transformer (image + text from first layer) with a shared parameter space, and let scale + training signal do the work. Please check our work ! 📄 Paper: arxiv.org/pdf/2603.27365 💻 Code: github.com/tiiuae/falcon-… 🎮 Playground: vision.falcon.aidrc.tii.ae 🤗 Blogpost: huggingface.co/blog/tiiuae/fa…

Introducing Project Glasswing: an urgent initiative to help secure the world’s most critical software. It’s powered by our newest frontier model, Claude Mythos Preview, which can find software vulnerabilities better than all but the most skilled humans. anthropic.com/glasswing

@ahmd3ssam @YouTube #dd2olc" target="_blank" rel="nofollow noopener">github.com/icarda/VBA_Too…

[ممكن مصر كمان] من المسؤول عن مشكلة الموقع | سياق youtu.be/EwKo7FKcaLA?si… via @YouTube