Research Database Manager and Senior Analyst at @ICARDA interested in #DataScience, #AI, #RStats, #PHP and #Arabic Language. Views are my own.

Cairo, Egypt
Joined April 2009
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
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Khaled Al-Shamaa retweeted
In @Nature this week, our new research shows how machine learning can improve weather forecasts two to six weeks out, a timeframe that's historically been very difficult to predict. It's exciting to see the potential of this work to help us better prepare for extreme weather, manage natural resources, and make more informed decisions in agriculture. There's a broader lesson here... the future may not just be about ever-more-capable models, but about building intelligent verification systems around them: systems that learn where models are systematically wrong, reason about cause and effect, and continuously calibrate predictions against reality. Read more: microsoft.com/en-us/research…
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Khaled Al-Shamaa retweeted
RustGIS is now on the Microsoft Store! On Windows 10 and 11, you can now install RustGIS from the Microsoft Store in one click. No installer to download, no security warnings, and the Store keeps it up to date with each new release. What you get - The full desktop app: the ribbon, panes, map view, attribute table, geoprocessing tools and the AI Assistant. - Open data, built in: search STAC catalogs, Planetary Computer, Overture Maps, Source Cooperative, OpenStreetMap and other open-data portals. - Cloud-native formats read in place: GeoParquet, FlatGeobuf and cloud-optimised GeoTIFFs open by their web address. - The command line too: rustgis-cli is ready in your terminal as soon as the app is installed. - Free and open source, with no sign-up needed. Get it - Microsoft Store: apps.microsoft.com/detail/9p… - Or from a terminal: winget install OpenGeos.RustGIS - Not on Windows? Launch the web app: web.rustgis.app - Other downloads: downloads.rustgis.app - Documentation: rustgis.app - GitHub: github.com/opengeos/RustGIS #GIS #Rust #OpenSource #Geospatial #Windows #MicrosoftStore #OpenData
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Jais 3: First adaption of K2 Horizon Jais 3 is built on K2 Horizon, our six-fleet fully open model family. Stronger in Arabic at every size, without starting from scratch. Plus Jais Speech, the most accurate open Arabic ASR. Download weights now: huggingface.co/collections/I…
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Khaled Al-Shamaa retweeted
From Lebanon to the Arctic 🌱 On 13 October, ICARDA deposited 2,039 seed samples representing 177 species from its Lebanon genebank at the Svalbard Global Seed Vault, strengthening global efforts to safeguard crop diversity for future generations. 🔗 Read the full story: icarda.org/media/blog/protec… With thanks to NordGen, the Norwegian Ministry of Agriculture and Food, the Crop Trust, and the CGIAR Genebank Network. 📸 Crop Trust #WorldFoodDay
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Introducing Jais 3, Arabic-native agentic AI. Jais 3 375B matches the best open models, and with Jais Speech offers the most advanced Arabic AI stack available. → Hugging Face: huggingface.co/collections/I… → Technical blog (Jais 3): ifm.ai/blog/jais3 → Technical blog (Jais Speech): ifm.ai/blog/jais-asr → Learn more: ifm.ai/jais/ Jais 3 was created by the Institute of Foundation Models (IFM) at MBZUAI, in collaboration with Inception42 and Cerebras Systems. #Jais3 #IFM #MBZUAI
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Khaled Al-Shamaa retweeted
بدأت من فترة كورس كامل لبناء LLM من الصفر . محاولة مني لسد فجوة كبيرة في اتقان هذه التقنيات. الكورس 17 ساعة. أصدرنا 4 محاضرات حتى الآن, آخرها أساسيات الـ PyTorch اللازمة لشخص لم يستخدم المكتبة من قبل, و تجهيزه قبل لبناء الـ Transformers youtube.com/watch?v=pQ1V_Upd… ..
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Khaled Al-Shamaa retweeted
In our latest blog post, @alexdaubois shares how the PHP Security Team operates, how your security reports are triaged, and how you can do your part to help PHP be more secure. thephp.foundation/blog/2026/… #phpc #security
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There is a heated discussion about RustGIS on Reddit! reddit.com/r/gis/comments/1x… I stopped posting/commenting on Reddit a few weeks ago. Not good for my mental health. Here are my personal opinions about RustGIS: Nobody is forcing you to use RustGIS. If ArcGIS/QGIS works well for you, that's great! Keep using it. I believe in giving people choices. Competition and diversity drive innovation and ultimately benefit everyone. Why do we have so many car manufacturers, such as Toyota, Honda, BMW, and Tesla? They all serve the same basic purpose, but offer different features, experiences, and approaches. The same applies to smartphones. We have iPhones and Android phones from Google, Samsung, Motorola, and others. Should we all use the same phone? GIS software is no different. ArcGIS, QGIS, and RustGIS can coexist, each serving different needs and communities. I'm not trying to replace anyone's favorite GIS. I'm simply building another free and open-source option for people who might find it useful. More choices are a good thing, especially in open-source software. If you want to learn more about how RustGIS compares to other software, check out rustgis.app/comparison
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أفريقيا تستعد لاستعادة هدير الفورمولا 1 رواندا تحتضن عودة البطولة إلى القارة باتفاق لعشرة أعوام، بدءاً من 2030 على أقرب تقدير… #فورمولا1 #F1
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A sharper view of our changing planet is coming. 🛰️🌎 Meet LandIS, the Landsat Instrument Suite that will fly aboard Landsat 10, the next satellite in the Landsat series. With 26 spectral bands spanning visible light to thermal infrared, LandIS will collect more than twice as many bands as Landsat 8 and Landsat 9. These additional bands will help users better distinguish features on Earth’s surface and monitor water quality, agriculture, vegetation health, snow and ice, soil conditions, and other environmental parameters. LandIS will also capture finer spatial detail, with resolutions of 10 to 20 meters for visible, near-infrared, and shortwave-infrared observations. That means a clearer view of smaller features, including streams, streamside habitats, woodlots, and individual agricultural fields. Together, more spectral bands and finer spatial resolution will help users detect, distinguish, and track environmental change with greater detail and precision. Expected to begin operations in the early 2030s, LandIS will also continue Landsat’s coverage of sunlit land and near-shore waters, along with select nighttime observations. It will also uphold the program’s high standards for data accuracy, extending a record of Earth observations that spans more than 54 years. Learn more about Landsat 10 and its planned capabilities: ow.ly/X4gK50ZW4EE 📷: A visual comparison of spatial resolution showing the 30-meter pixels of Landsat 8 and 9 (left) alongside the finer, more detailed 10-meter pixels planned for Landsat 10 (right). Credit: NASA
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Create yours, supporting any characters or png! kejunmao.github.io/chars-dra…
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Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
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Khaled Al-Shamaa retweeted
Syria is where ICARDA’s journey began. It’s also where it continues. With support from Japan, we’re helping rebuild Syria’s seed system. 25 seed professionals from across the country have been trained. Now we’re mapping what’s still standing, what was lost, and what needs to come back first. What this means? 🌾 For farmers: improved varieties, quality seed, on time. 🏛️ For Syria’s institutions: the ability to produce, test, certify and distribute seed again. 🔬 For ICARDA: a scientific partnership with Syria that stretches back decades, and keeps going. Read the story 👇 icarda.org/media/news/seeds-…
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Khaled Al-Shamaa retweeted
Elon Musk
@elonmuskOct 10
Electricity production is the best metric for the true strength of any large-scale economy imo
Energy capacity = economic capacity, in one chart There are no low electricity, rich countries
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BREAKING NEWS The Norwegian Nobel Committee has decided to award the 2026 #NobelPeacePrize to Navanethem “Navi” Pillay for her efforts to promote peace and international law. #NobelPrize
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Replying to @KhodrRawi
اللهم آمين 🙏🏻
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Khaled Al-Shamaa retweeted
Replying to @googlechrome
@googlechrome 154 can now adjust the size an iframe to its content with one line of CSS: iframe { frame-sizing: content-height; } I wrote about it: alfy.blog/2026/10/09/iframe-… @ChromiumDev
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Khaled Al-Shamaa retweeted
You can now train your own Decision model with our free notebook! 💡 Qwen3.5-4B will generate decisions instead of text on just 8GB VRAM locally. Learn to data prep (state, questions, gold answers), train, serve. Notebook: colab.research.google.com/gi… Guide: unsloth.ai/docs/basics/train…
You can now train your own Decision model like Jev locally! We increased Qwen3.5 0.8B’s aggregate accuracy from 20.7% to 74.3% across 3 decision benchmarks - on just 4GB VRAM. Turn any LLM like Qwen3.8, Gemma 4 into decision models with our open-source Unsloth repo. We fine-tuned with a Clef head using Unsloth and LoRA (r=64) for one epoch, increasing downstream accuracy from 30–37% to 78%. GitHub: github.com/unslothai/unsloth Guide and Notebooks: unsloth.ai/docs/basics/train…
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