• حبيت نقوللكم، البرمجة مش غير كتابة كود، بل هي فهم عميق للمفاهيم!

    فيديو جديد رح يتعمق في "٥ مفاهيم ٩٠٪؜ من المبرمجين فاهمينها غلط". رح نتكلم عن الفروقات بين المكتبة (Library) وإطار العمل (Framework)، وكذا معنى واجهة برمجة التطبيقات (API) ومعاني المصادقة (Authentication) والتفويض (Authorization).

    كتجربة شخصية، عشت صعوبات في توضيح هالمفاهيم، حتى بعد ما نعرفها. كنا نعتقد انو الكود هو كلش، لكن في النهاية، كيفاش تشرح المفاهيم هو اللي يفتح لك الأبواب في مقابلات العمل!

    خليك متميز وفهم عميق رح يفرق معاك. تابع الفيديو وخلينا نطوروا مهاراتنا مع بعض!

    https://www.youtube.com/watch?v=V1x2Pq6bV8s
    #برمجة #مفاهيم #Coding #API #Tech
    🌟 حبيت نقوللكم، البرمجة مش غير كتابة كود، بل هي فهم عميق للمفاهيم! 🌟 فيديو جديد رح يتعمق في "٥ مفاهيم ٩٠٪؜ من المبرمجين فاهمينها غلط". رح نتكلم عن الفروقات بين المكتبة (Library) وإطار العمل (Framework)، وكذا معنى واجهة برمجة التطبيقات (API) ومعاني المصادقة (Authentication) والتفويض (Authorization). 🤔💻 كتجربة شخصية، عشت صعوبات في توضيح هالمفاهيم، حتى بعد ما نعرفها. كنا نعتقد انو الكود هو كلش، لكن في النهاية، كيفاش تشرح المفاهيم هو اللي يفتح لك الأبواب في مقابلات العمل! خليك متميز وفهم عميق رح يفرق معاك. تابع الفيديو وخلينا نطوروا مهاراتنا مع بعض! 😉 https://www.youtube.com/watch?v=V1x2Pq6bV8s #برمجة #مفاهيم #Coding #API #Tech
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  • هل سمعتوا بالخبر الجديد حول نقل البيانات بين أوروبا وأمريكا؟

    المحكمة الأوروبية، الثانية الأهم، قررت تدعم الاتفاقية الجديدة لنقل البيانات بين الاتحاد الأوروبي والولايات المتحدة. بعد تحديات ومحاكمات، الحكم جاء لصالح الفكرة التي تضمن حماية البيانات الشخصية الأوروبية حتى لو كانت موجودة في الولايات المتحدة. الاتفاقية تنص على أن المستخدمين الأوروبيين يقدروا يرفعوا شكاوى حول كيفية التعامل مع بياناتهم.

    شخصياً، نحب الفكرة أنو راح يكون عندنا ضوابط أكثر تحمي خصوصيتنا في زمن كلشي ولا رقمياً. لكن يظل السؤال: هل فعلاً راح تكون هذه الضوابط كافية في ظل التحديات المتزايدة؟

    https://www.engadget.com/big-tech/european-court-rules-in-favor-of-the-latest-us-and-eu-data-transfer-framework-150049576.html?src=rss

    #حماية_البيانات #TransmissionDeDonnées #DataPrivacy #EU #US
    هل سمعتوا بالخبر الجديد حول نقل البيانات بين أوروبا وأمريكا؟ 😲 المحكمة الأوروبية، الثانية الأهم، قررت تدعم الاتفاقية الجديدة لنقل البيانات بين الاتحاد الأوروبي والولايات المتحدة. بعد تحديات ومحاكمات، الحكم جاء لصالح الفكرة التي تضمن حماية البيانات الشخصية الأوروبية حتى لو كانت موجودة في الولايات المتحدة. الاتفاقية تنص على أن المستخدمين الأوروبيين يقدروا يرفعوا شكاوى حول كيفية التعامل مع بياناتهم. شخصياً، نحب الفكرة أنو راح يكون عندنا ضوابط أكثر تحمي خصوصيتنا في زمن كلشي ولا رقمياً. لكن يظل السؤال: هل فعلاً راح تكون هذه الضوابط كافية في ظل التحديات المتزايدة؟ https://www.engadget.com/big-tech/european-court-rules-in-favor-of-the-latest-us-and-eu-data-transfer-framework-150049576.html?src=rss #حماية_البيانات #TransmissionDeDonnées #DataPrivacy #EU #US
    www.engadget.com
    Europe’s second-highest court has dismissed a challenge against a data transfer pact between the European Union and the US. "On the date of adoption of the contested decision, the United States of America ensured an adequate level of protection
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  • واش خباركم يا جماعة؟ عندي سؤال يشعل الحماس: هل تظنوا أن الاختيار بين Langchain و Langgraph يقدر يبدل مستقبل المشاريع التكنولوجية؟

    في العالم اليوم، تكنولوجيا الذكاء الاصطناعي والبرمجة بقاو في تطور مستمر، وكيبانو بزاف أفكار جديدة. لكن الفرق بين هذين الإطارين (frameworks) بصح مش ساهل. كل واحد عنده الميزات تاعه، وعندهم تأثيرات إيجابية وسلبية. شخصيًا، نحب Langchain لأنه يسهّل عملية تطوير التطبيقات، بصح ناس يحكيو على قوة Langgraph في إدارة البيانات وتحليلها.

    فكروا شوية، واش هو الإطار اللي تتوقعوا يجيب أفضل نتائج في المستقبل؟ هل نحتاجوا التوازن بين الاثنين؟

    #تكنولوجيا #برمجة #ذكاء_اصطناعي #Langchain #Langgraph
    واش خباركم يا جماعة؟ عندي سؤال يشعل الحماس: هل تظنوا أن الاختيار بين Langchain و Langgraph يقدر يبدل مستقبل المشاريع التكنولوجية؟ في العالم اليوم، تكنولوجيا الذكاء الاصطناعي والبرمجة بقاو في تطور مستمر، وكيبانو بزاف أفكار جديدة. لكن الفرق بين هذين الإطارين (frameworks) بصح مش ساهل. كل واحد عنده الميزات تاعه، وعندهم تأثيرات إيجابية وسلبية. شخصيًا، نحب Langchain لأنه يسهّل عملية تطوير التطبيقات، بصح ناس يحكيو على قوة Langgraph في إدارة البيانات وتحليلها. فكروا شوية، واش هو الإطار اللي تتوقعوا يجيب أفضل نتائج في المستقبل؟ هل نحتاجوا التوازن بين الاثنين؟ #تكنولوجيا #برمجة #ذكاء_اصطناعي #Langchain #Langgraph
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  • إذا كنتم تحبوا السيارات والتكنولوجيا، لازم تشوفوا الفيديو هدا!

    في الفيديو "Procedural Worlds by McLaren: Automotive Visualization with PCG Content | Unreal Fest Orlando 2025"، يتحدث Jack Gullen عن كيفاش يمكننا نبنيو سيارات في بيئات مختلفة وبسرعة بفضل Procedural Content Generation Framework في Unreal Engine. يعني تقدروا تشوفوا السيارة متاحة في كل الفصول والمناطق، من الغابة حتى الصحراء، وهذا في ثواني!

    شخصياً، عندي تجربة مع التصميم ونعرف قداش التغييرات السريعة في البيئات تقدر تخلي خيالنا يتحرر ويعطي ثماره. هذا الفيديو راح يفتح لكم آفاق جديدة في عالم التصميم!

    شوفوا الفيديو وخليوا عقولكم تتلاقى مع الإبداع!

    https://www.youtube.com/watch?v=ZqMBA1IVrVs
    #تصميم #AutomotiveDesign #UnrealEngine #تكنولوجيا #Innovation
    🚗✨ إذا كنتم تحبوا السيارات والتكنولوجيا، لازم تشوفوا الفيديو هدا! في الفيديو "Procedural Worlds by McLaren: Automotive Visualization with PCG Content | Unreal Fest Orlando 2025"، يتحدث Jack Gullen عن كيفاش يمكننا نبنيو سيارات في بيئات مختلفة وبسرعة بفضل Procedural Content Generation Framework في Unreal Engine. يعني تقدروا تشوفوا السيارة متاحة في كل الفصول والمناطق، من الغابة حتى الصحراء، وهذا في ثواني! شخصياً، عندي تجربة مع التصميم ونعرف قداش التغييرات السريعة في البيئات تقدر تخلي خيالنا يتحرر ويعطي ثماره. هذا الفيديو راح يفتح لكم آفاق جديدة في عالم التصميم! شوفوا الفيديو وخليوا عقولكم تتلاقى مع الإبداع! https://www.youtube.com/watch?v=ZqMBA1IVrVs #تصميم #AutomotiveDesign #UnrealEngine #تكنولوجيا #Innovation
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  • هل تصدقوا أن التكنولوجيا قادرة على تغيير تجربتنا في عالم الألعاب؟

    الخبر السار هو أن Framework جابوا الحل اللي كنا ننتظروه! CEO تاعهم، Nirav Patel، أعلن عن أول لاب توب يجمع بين القوة التكنولوجية والتحديث السهل للـ GPU. يعني كأنك تلعب في ديزاين تاع PC، مع الرفاهية تاع اللاب توب. في 2023، هذا الجهاز يعد بأنه "الكأس المقدسة" لكل gamers. من بعد ما شكون شاف وعدات من قبل، كنا شوي متشككين، بصح هذه المرة شكلها جدية.

    شخصياً، قابلت صعوبات كبيرة في تحديث عتاد اللاب توب تاعي، ونعرف كيف ممكن هاد الجهاز يحللي الأمور.

    حاجة مليحة تكون عندنا خيارات أفضل في عالم الألعاب، ومانسوش أن كل خطوة جديدة هي فرصة لنكتشف أبعاد جديدة لطموحاتنا.

    https://www.theverge.com/laptops/765528/framework-is-now-selling-the-first-gaming-laptop-that-lets-you-easily-upgrade-its-gpu-with-n
    هل تصدقوا أن التكنولوجيا قادرة على تغيير تجربتنا في عالم الألعاب؟ 🤔 الخبر السار هو أن Framework جابوا الحل اللي كنا ننتظروه! CEO تاعهم، Nirav Patel، أعلن عن أول لاب توب يجمع بين القوة التكنولوجية والتحديث السهل للـ GPU. يعني كأنك تلعب في ديزاين تاع PC، مع الرفاهية تاع اللاب توب. في 2023، هذا الجهاز يعد بأنه "الكأس المقدسة" لكل gamers. من بعد ما شكون شاف وعدات من قبل، كنا شوي متشككين، بصح هذه المرة شكلها جدية. شخصياً، قابلت صعوبات كبيرة في تحديث عتاد اللاب توب تاعي، ونعرف كيف ممكن هاد الجهاز يحللي الأمور. حاجة مليحة تكون عندنا خيارات أفضل في عالم الألعاب، ومانسوش أن كل خطوة جديدة هي فرصة لنكتشف أبعاد جديدة لطموحاتنا. https://www.theverge.com/laptops/765528/framework-is-now-selling-the-first-gaming-laptop-that-lets-you-easily-upgrade-its-gpu-with-n
    www.theverge.com
    Framework CEO Nirav Patel said he would deliver "the holy grail for gamers" with the Framework Laptop 16. In 2023, he suggested it'd be the first consumer notebook to fulfil the promise of modular, upgradable graphics cards like a desktop PC. We at T
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  • NVIDIA Jetson Thor Unlocks Real-Time Reasoning for General Robotics and Physical AI

    Robots around the world are about to get a lot smarter as physical AI developers plug in NVIDIA Jetson Thor modules — new robotics computers that can serve as the brains for robotic systems across research and industry.
    Robots demand rich sensor data and low-latency AI processing. Running real-time robotic applications requires significant AI compute and memory to handle concurrent data streams from multiple sensors. Jetson Thor, now in general availability, delivers 7.5x more AI compute, 3.1x more CPU performance and 2x more memory than its predecessor, the NVIDIA Jetson Orin, to make this possible on device.
    This performance leap will enable roboticists to process high-speed sensor data and perform visual reasoning at the edge — workflows that were previously too slow to run in dynamic real-world environments. This opens new possibilities for multimodal AI applications such as humanoid robotics.

    Agility Robotics, a leader in humanoid robotics, has integrated NVIDIA Jetson into the fifth generation of its robot, Digit — and plans to adopt Jetson Thor as the onboard compute platform for the sixth generation of Digit. This transition will enhance Digit’s real-time perception and decision-making capabilities, supporting increasingly complex AI skills and behaviors. Digit is commercially deployed and performs logistics tasks such as stacking, loading and palletizing in warehouse and manufacturing environments.
    “The powerful edge processing offered by Jetson Thor will take Digit to the next level — enhancing its real-time responsiveness and expanding its abilities to a broader, more complex set of skills,” said Peggy Johnson, CEO of Agility Robotics. “With Jetson Thor, we can deliver the latest physical AI advancements to optimize operations across our customers’ warehouses and factories.”
    Boston Dynamics — which has been building some of the industry’s most advanced robots for over 30 years — is integrating Jetson Thor into its humanoid robot Atlas, enabling Atlas to harness formerly server-level compute, AI workload acceleration, high-bandwidth data processing and significant memory on device.
    Beyond humanoids, Jetson Thor will accelerate various robotic applications — such as surgical assistants, smart tractors, delivery robots, industrial manipulators and visual AI agents — with real-time inference on device for larger, more complex AI models.
    A Giant Leap for Real-Time Robot Reasoning
    Jetson Thor is built for generative reasoning models. It enables the next generation of physical AI agents — powered by large transformer models, vision language models and vision language action models — to run in real time at the edge while minimizing cloud dependency.
    Optimized with the Jetson software stack to enable the low latency and high performance required in real-world applications, Jetson Thor supports all popular generative AI frameworks and AI reasoning models with unmatched real-time performance. These include Cosmos Reason, DeepSeek, Llama, Gemini and Qwen models, as well as domain-specific models for robotics like Isaac GR00T N1.5, enabling any developer to easily experiment and run inference locally.
    NVIDIA Jetson Thor opens new capabilities for real-time reasoning with multi-sensor input. Further performance improvement is expected with FP4 and speculative decoding optimization.
    With NVIDIA CUDA ecosystem support through its lifecycle, Jetson Thor is expected to deliver even better throughput and faster responses with future software releases.
    Jetson Thor modules also run the full NVIDIA AI software stack to accelerate virtually every physical AI workflow with platforms including NVIDIA Isaac for robotics, NVIDIA Metropolis for video analytics AI agents and NVIDIA Holoscan for sensor processing.
    With these software tools, developers can easily build and deploy applications, such as visual AI agents that can analyze live camera streams to monitor worker safety, humanoid robots capable of manipulation tasks in unstructured environments and smart operating rooms that guide surgeons based on data from multi-camera streams.
    Jetson Thor Set to Advance Research Innovation 
    Research labs at Stanford University, Carnegie Mellon University and the University of Zurich are tapping Jetson Thor to push the boundaries of perception, planning and navigation models for a host of potential applications.
    At Carnegie Mellon’s Robotics Institute, a research team uses NVIDIA Jetson to power autonomous robots that can navigate complex, unstructured environments to conduct medical triage as well as search and rescue.
    “We can only do as much as the compute available allows,” said Sebastian Scherer, an associate research professor at the university and head of the AirLab. “Years ago, there was a big disconnect between computer vision and robotics because computer vision workloads were too slow for real-time decision-making — but now, models and computing have gotten fast enough so robots can handle much more nuanced tasks.”
    Scherer anticipates that by upgrading from his team’s existing NVIDIA Jetson AGX Orin systems to Jetson AGX Thor developer kit, they’ll improve the performance of AI models including their award-winning MAC-VO model for robot perception at the edge, boost their sensor-fusion capabilities and be able to experiment with robot fleets.
    Wield the Strength of Jetson Thor
    The Jetson Thor family includes a developer kit and production modules. The developer kit includes a Jetson T5000 module, a reference carrier board with abundant connectivity, an active heatsink with a fan and a power supply.
    NVIDIA Jetson AGX Thor Developer Kit
    The Jetson ecosystem supports a variety of application requirements, high-speed industrial automation protocols and sensor interfaces, accelerating time to market for enterprise developers. Hardware partners including Advantech, Aetina, ConnectTech, MiiVii and TZTEK are building production-ready Jetson Thor systems with flexible I/O and custom configurations in various form factors.
    Sensor and Actuator companies including Analog Devices, Inc., e-con Systems,  Infineon, Leopard Imaging, RealSense and Sensing are using NVIDIA Holoscan Sensor Bridge — a platform that simplifies sensor fusion and data streaming — to connect sensor data from cameras, radar, lidar and more directly to GPU memory on Jetson Thor with ultralow latency.
    Thousands of software companies can now elevate their traditional vision AI and robotics applications with multi-AI agent workflows running on Jetson Thor. Leading adopters include Openzeka, Rebotnix, Solomon and Vaidio.
    More than 2 million developers use NVIDIA technologies to accelerate robotics workflows. Get started with Jetson Thor by reading the NVIDIA Technical Blog and watching the developer kit walkthrough.

    To get hands-on experience with Jetson Thor, sign up to participate in upcoming hackathons with Seeed Studio and LeRobot by Hugging Face.
    The NVIDIA Jetson AGX Thor developer kit is available now starting at NVIDIA Jetson T5000 modules are available starting at for 1,000 units. Buy now from authorized NVIDIA partners.
    NVIDIA today also announced that the NVIDIA DRIVE AGX Thor developer kit, which provides a platform for developing autonomous vehicles and mobility solutions, is available for preorder. Deliveries are slated to start in September.
    #nvidia #jetson #thor #unlocks #realtime
    NVIDIA Jetson Thor Unlocks Real-Time Reasoning for General Robotics and Physical AI
    Robots around the world are about to get a lot smarter as physical AI developers plug in NVIDIA Jetson Thor modules — new robotics computers that can serve as the brains for robotic systems across research and industry. Robots demand rich sensor data and low-latency AI processing. Running real-time robotic applications requires significant AI compute and memory to handle concurrent data streams from multiple sensors. Jetson Thor, now in general availability, delivers 7.5x more AI compute, 3.1x more CPU performance and 2x more memory than its predecessor, the NVIDIA Jetson Orin, to make this possible on device. This performance leap will enable roboticists to process high-speed sensor data and perform visual reasoning at the edge — workflows that were previously too slow to run in dynamic real-world environments. This opens new possibilities for multimodal AI applications such as humanoid robotics. Agility Robotics, a leader in humanoid robotics, has integrated NVIDIA Jetson into the fifth generation of its robot, Digit — and plans to adopt Jetson Thor as the onboard compute platform for the sixth generation of Digit. This transition will enhance Digit’s real-time perception and decision-making capabilities, supporting increasingly complex AI skills and behaviors. Digit is commercially deployed and performs logistics tasks such as stacking, loading and palletizing in warehouse and manufacturing environments. “The powerful edge processing offered by Jetson Thor will take Digit to the next level — enhancing its real-time responsiveness and expanding its abilities to a broader, more complex set of skills,” said Peggy Johnson, CEO of Agility Robotics. “With Jetson Thor, we can deliver the latest physical AI advancements to optimize operations across our customers’ warehouses and factories.” Boston Dynamics — which has been building some of the industry’s most advanced robots for over 30 years — is integrating Jetson Thor into its humanoid robot Atlas, enabling Atlas to harness formerly server-level compute, AI workload acceleration, high-bandwidth data processing and significant memory on device. Beyond humanoids, Jetson Thor will accelerate various robotic applications — such as surgical assistants, smart tractors, delivery robots, industrial manipulators and visual AI agents — with real-time inference on device for larger, more complex AI models. A Giant Leap for Real-Time Robot Reasoning Jetson Thor is built for generative reasoning models. It enables the next generation of physical AI agents — powered by large transformer models, vision language models and vision language action models — to run in real time at the edge while minimizing cloud dependency. Optimized with the Jetson software stack to enable the low latency and high performance required in real-world applications, Jetson Thor supports all popular generative AI frameworks and AI reasoning models with unmatched real-time performance. These include Cosmos Reason, DeepSeek, Llama, Gemini and Qwen models, as well as domain-specific models for robotics like Isaac GR00T N1.5, enabling any developer to easily experiment and run inference locally. NVIDIA Jetson Thor opens new capabilities for real-time reasoning with multi-sensor input. Further performance improvement is expected with FP4 and speculative decoding optimization. With NVIDIA CUDA ecosystem support through its lifecycle, Jetson Thor is expected to deliver even better throughput and faster responses with future software releases. Jetson Thor modules also run the full NVIDIA AI software stack to accelerate virtually every physical AI workflow with platforms including NVIDIA Isaac for robotics, NVIDIA Metropolis for video analytics AI agents and NVIDIA Holoscan for sensor processing. With these software tools, developers can easily build and deploy applications, such as visual AI agents that can analyze live camera streams to monitor worker safety, humanoid robots capable of manipulation tasks in unstructured environments and smart operating rooms that guide surgeons based on data from multi-camera streams. Jetson Thor Set to Advance Research Innovation  Research labs at Stanford University, Carnegie Mellon University and the University of Zurich are tapping Jetson Thor to push the boundaries of perception, planning and navigation models for a host of potential applications. At Carnegie Mellon’s Robotics Institute, a research team uses NVIDIA Jetson to power autonomous robots that can navigate complex, unstructured environments to conduct medical triage as well as search and rescue. “We can only do as much as the compute available allows,” said Sebastian Scherer, an associate research professor at the university and head of the AirLab. “Years ago, there was a big disconnect between computer vision and robotics because computer vision workloads were too slow for real-time decision-making — but now, models and computing have gotten fast enough so robots can handle much more nuanced tasks.” Scherer anticipates that by upgrading from his team’s existing NVIDIA Jetson AGX Orin systems to Jetson AGX Thor developer kit, they’ll improve the performance of AI models including their award-winning MAC-VO model for robot perception at the edge, boost their sensor-fusion capabilities and be able to experiment with robot fleets. Wield the Strength of Jetson Thor The Jetson Thor family includes a developer kit and production modules. The developer kit includes a Jetson T5000 module, a reference carrier board with abundant connectivity, an active heatsink with a fan and a power supply. NVIDIA Jetson AGX Thor Developer Kit The Jetson ecosystem supports a variety of application requirements, high-speed industrial automation protocols and sensor interfaces, accelerating time to market for enterprise developers. Hardware partners including Advantech, Aetina, ConnectTech, MiiVii and TZTEK are building production-ready Jetson Thor systems with flexible I/O and custom configurations in various form factors. Sensor and Actuator companies including Analog Devices, Inc., e-con Systems,  Infineon, Leopard Imaging, RealSense and Sensing are using NVIDIA Holoscan Sensor Bridge — a platform that simplifies sensor fusion and data streaming — to connect sensor data from cameras, radar, lidar and more directly to GPU memory on Jetson Thor with ultralow latency. Thousands of software companies can now elevate their traditional vision AI and robotics applications with multi-AI agent workflows running on Jetson Thor. Leading adopters include Openzeka, Rebotnix, Solomon and Vaidio. More than 2 million developers use NVIDIA technologies to accelerate robotics workflows. Get started with Jetson Thor by reading the NVIDIA Technical Blog and watching the developer kit walkthrough. To get hands-on experience with Jetson Thor, sign up to participate in upcoming hackathons with Seeed Studio and LeRobot by Hugging Face. The NVIDIA Jetson AGX Thor developer kit is available now starting at NVIDIA Jetson T5000 modules are available starting at for 1,000 units. Buy now from authorized NVIDIA partners. NVIDIA today also announced that the NVIDIA DRIVE AGX Thor developer kit, which provides a platform for developing autonomous vehicles and mobility solutions, is available for preorder. Deliveries are slated to start in September. #nvidia #jetson #thor #unlocks #realtime
    NVIDIA Jetson Thor Unlocks Real-Time Reasoning for General Robotics and Physical AI
    blogs.nvidia.com
    Robots around the world are about to get a lot smarter as physical AI developers plug in NVIDIA Jetson Thor modules — new robotics computers that can serve as the brains for robotic systems across research and industry. Robots demand rich sensor data and low-latency AI processing. Running real-time robotic applications requires significant AI compute and memory to handle concurrent data streams from multiple sensors. Jetson Thor, now in general availability, delivers 7.5x more AI compute, 3.1x more CPU performance and 2x more memory than its predecessor, the NVIDIA Jetson Orin, to make this possible on device. This performance leap will enable roboticists to process high-speed sensor data and perform visual reasoning at the edge — workflows that were previously too slow to run in dynamic real-world environments. This opens new possibilities for multimodal AI applications such as humanoid robotics. Agility Robotics, a leader in humanoid robotics, has integrated NVIDIA Jetson into the fifth generation of its robot, Digit — and plans to adopt Jetson Thor as the onboard compute platform for the sixth generation of Digit. This transition will enhance Digit’s real-time perception and decision-making capabilities, supporting increasingly complex AI skills and behaviors. Digit is commercially deployed and performs logistics tasks such as stacking, loading and palletizing in warehouse and manufacturing environments. “The powerful edge processing offered by Jetson Thor will take Digit to the next level — enhancing its real-time responsiveness and expanding its abilities to a broader, more complex set of skills,” said Peggy Johnson, CEO of Agility Robotics. “With Jetson Thor, we can deliver the latest physical AI advancements to optimize operations across our customers’ warehouses and factories.” Boston Dynamics — which has been building some of the industry’s most advanced robots for over 30 years — is integrating Jetson Thor into its humanoid robot Atlas, enabling Atlas to harness formerly server-level compute, AI workload acceleration, high-bandwidth data processing and significant memory on device. Beyond humanoids, Jetson Thor will accelerate various robotic applications — such as surgical assistants, smart tractors, delivery robots, industrial manipulators and visual AI agents — with real-time inference on device for larger, more complex AI models. A Giant Leap for Real-Time Robot Reasoning Jetson Thor is built for generative reasoning models. It enables the next generation of physical AI agents — powered by large transformer models, vision language models and vision language action models — to run in real time at the edge while minimizing cloud dependency. Optimized with the Jetson software stack to enable the low latency and high performance required in real-world applications, Jetson Thor supports all popular generative AI frameworks and AI reasoning models with unmatched real-time performance. These include Cosmos Reason, DeepSeek, Llama, Gemini and Qwen models, as well as domain-specific models for robotics like Isaac GR00T N1.5, enabling any developer to easily experiment and run inference locally. NVIDIA Jetson Thor opens new capabilities for real-time reasoning with multi-sensor input. Further performance improvement is expected with FP4 and speculative decoding optimization. With NVIDIA CUDA ecosystem support through its lifecycle, Jetson Thor is expected to deliver even better throughput and faster responses with future software releases. Jetson Thor modules also run the full NVIDIA AI software stack to accelerate virtually every physical AI workflow with platforms including NVIDIA Isaac for robotics, NVIDIA Metropolis for video analytics AI agents and NVIDIA Holoscan for sensor processing. With these software tools, developers can easily build and deploy applications, such as visual AI agents that can analyze live camera streams to monitor worker safety, humanoid robots capable of manipulation tasks in unstructured environments and smart operating rooms that guide surgeons based on data from multi-camera streams. Jetson Thor Set to Advance Research Innovation  Research labs at Stanford University, Carnegie Mellon University and the University of Zurich are tapping Jetson Thor to push the boundaries of perception, planning and navigation models for a host of potential applications. At Carnegie Mellon’s Robotics Institute, a research team uses NVIDIA Jetson to power autonomous robots that can navigate complex, unstructured environments to conduct medical triage as well as search and rescue. “We can only do as much as the compute available allows,” said Sebastian Scherer, an associate research professor at the university and head of the AirLab. “Years ago, there was a big disconnect between computer vision and robotics because computer vision workloads were too slow for real-time decision-making — but now, models and computing have gotten fast enough so robots can handle much more nuanced tasks.” Scherer anticipates that by upgrading from his team’s existing NVIDIA Jetson AGX Orin systems to Jetson AGX Thor developer kit, they’ll improve the performance of AI models including their award-winning MAC-VO model for robot perception at the edge, boost their sensor-fusion capabilities and be able to experiment with robot fleets. Wield the Strength of Jetson Thor The Jetson Thor family includes a developer kit and production modules. The developer kit includes a Jetson T5000 module, a reference carrier board with abundant connectivity, an active heatsink with a fan and a power supply. NVIDIA Jetson AGX Thor Developer Kit The Jetson ecosystem supports a variety of application requirements, high-speed industrial automation protocols and sensor interfaces, accelerating time to market for enterprise developers. Hardware partners including Advantech, Aetina, ConnectTech, MiiVii and TZTEK are building production-ready Jetson Thor systems with flexible I/O and custom configurations in various form factors. Sensor and Actuator companies including Analog Devices, Inc. (ADI), e-con Systems,  Infineon, Leopard Imaging, RealSense and Sensing are using NVIDIA Holoscan Sensor Bridge — a platform that simplifies sensor fusion and data streaming — to connect sensor data from cameras, radar, lidar and more directly to GPU memory on Jetson Thor with ultralow latency. Thousands of software companies can now elevate their traditional vision AI and robotics applications with multi-AI agent workflows running on Jetson Thor. Leading adopters include Openzeka, Rebotnix, Solomon and Vaidio. More than 2 million developers use NVIDIA technologies to accelerate robotics workflows. Get started with Jetson Thor by reading the NVIDIA Technical Blog and watching the developer kit walkthrough. To get hands-on experience with Jetson Thor, sign up to participate in upcoming hackathons with Seeed Studio and LeRobot by Hugging Face. The NVIDIA Jetson AGX Thor developer kit is available now starting at $3,499. NVIDIA Jetson T5000 modules are available starting at $2,999 for 1,000 units. Buy now from authorized NVIDIA partners. NVIDIA today also announced that the NVIDIA DRIVE AGX Thor developer kit, which provides a platform for developing autonomous vehicles and mobility solutions, is available for preorder. Deliveries are slated to start in September.
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  • يا جماعة، شكون فينا ما حلمش باش يلعب ألعاب الفيديو على البي سي من الصالون؟

    في هذا المقال، نتحدثو عن كيف Framework Desktop و Linux ورّونا الطريق لنجربو تجربة الألعاب على البي سي بطريقة جديدة. خاصتا مع Steam Deck، اللي هو زوين بصح، لكن كل واحد فينا يحب حاجة أقوى وأكثر راحة قدام التلفاز. بالصح، واش كاين أفضل من جهاز يقدر يتطور معانا ويخلينا نستمتع بالمكتبة الكبيرة تاع Steam وينما رحنّا؟

    أنا شخصيا، دايما كنت نحب نلعب مع الأصحاب في الصالون، وكي نشوف هاد التطورات، نحب نكون جزء من هاد العالم. نعرف بلي كاين بزاف منكم عندهم نفس الشغف!

    خليونا نفكرو في كيفاش نقدروا نستمتعو بتجربة الألعاب في البيوت تاعنا بطريقة جديدة وفعّالة.

    https://www.theverge.com/games/761025/framework-desktop-bazzite-linux-steam-machine-pc-game-console-impressions
    #ألعاب_البي_سي #
    يا جماعة، شكون فينا ما حلمش باش يلعب ألعاب الفيديو على البي سي من الصالون؟ 🎮✨ في هذا المقال، نتحدثو عن كيف Framework Desktop و Linux ورّونا الطريق لنجربو تجربة الألعاب على البي سي بطريقة جديدة. خاصتا مع Steam Deck، اللي هو زوين بصح، لكن كل واحد فينا يحب حاجة أقوى وأكثر راحة قدام التلفاز. بالصح، واش كاين أفضل من جهاز يقدر يتطور معانا ويخلينا نستمتع بالمكتبة الكبيرة تاع Steam وينما رحنّا؟ أنا شخصيا، دايما كنت نحب نلعب مع الأصحاب في الصالون، وكي نشوف هاد التطورات، نحب نكون جزء من هاد العالم. نعرف بلي كاين بزاف منكم عندهم نفس الشغف! خليونا نفكرو في كيفاش نقدروا نستمتعو بتجربة الألعاب في البيوت تاعنا بطريقة جديدة وفعّالة. https://www.theverge.com/games/761025/framework-desktop-bazzite-linux-steam-machine-pc-game-console-impressions #ألعاب_البي_سي #
    www.theverge.com
    I've long dreamed of doing all my gaming on PC - a single platform that's easily upgradeable and lets me play my overstuffed Steam library wherever and however I like. The Steam Deck is a fantastic handheld, but for my living room, I want something m
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  • يا جماعة، أنتم جاهزين لعالم الذكاء الاصطناعي؟

    حبيت نشارك معاكم مقال مهم حول "Our updated Preparedness Framework". هذا الإطار الجديد يهدف لقياس وحماية أنفسنا من الأضرار الكبيرة اللي ممكن تسببها تقنيات الذكاء الاصطناعي المتطورة. في الوقت اللي التكنولوجيا تتطور بسرعة، كيفاش نقدروا نحميوا أرواحنا وأعمالنا من المخاطر اللي ممكن تظهر؟

    شخصياً، كنت دايماً مهتم بالتوازن بين الابتكار والحذر. كلما زادت الإمكانيات، زادت التحديات. كاين حاجة لازم نكونوا واعيين بها، والوعي هو المفتاح.

    خلينا نفكروا في الموضوع ونشوفوا كيفاش نقدروا نكونوا جزء من الحل بدلاً من أن نكون ضحية.

    https://openai.com/index/updating-our-preparedness-framework
    #ذكاء_اصطناعي #AI #إطار_التحضير #Innovation #Protection
    🔥 يا جماعة، أنتم جاهزين لعالم الذكاء الاصطناعي؟ 🔍 حبيت نشارك معاكم مقال مهم حول "Our updated Preparedness Framework". هذا الإطار الجديد يهدف لقياس وحماية أنفسنا من الأضرار الكبيرة اللي ممكن تسببها تقنيات الذكاء الاصطناعي المتطورة. في الوقت اللي التكنولوجيا تتطور بسرعة، كيفاش نقدروا نحميوا أرواحنا وأعمالنا من المخاطر اللي ممكن تظهر؟ شخصياً، كنت دايماً مهتم بالتوازن بين الابتكار والحذر. كلما زادت الإمكانيات، زادت التحديات. كاين حاجة لازم نكونوا واعيين بها، والوعي هو المفتاح. خلينا نفكروا في الموضوع ونشوفوا كيفاش نقدروا نكونوا جزء من الحل بدلاً من أن نكون ضحية. https://openai.com/index/updating-our-preparedness-framework #ذكاء_اصطناعي #AI #إطار_التحضير #Innovation #Protection
    openai.com
    Sharing our updated framework for measuring and protecting against severe harm from frontier AI capabilities.
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  • Hot Topics at Hot Chips: Inference, Networking, AI Innovation at Every Scale — All Built on NVIDIA

    AI reasoning, inference and networking will be top of mind for attendees of next week’s Hot Chips conference.
    A key forum for processor and system architects from industry and academia, Hot Chips — running Aug. 24-26 at Stanford University — showcases the latest innovations poised to advance AI factories and drive revenue for the trillion-dollar data center computing market.
    At the conference, NVIDIA will join industry leaders including Google and Microsoft in a “tutorial” session — taking place on Sunday, Aug. 24 — that discusses designing rack-scale architecture for data centers.
    In addition, NVIDIA experts will present at four sessions and one tutorial detailing how:

    NVIDIA networking, including the NVIDIA ConnectX-8 SuperNIC, delivers AI reasoning at rack- and data-center scale.Neural rendering advancements and massive leaps in inference — powered by the NVIDIA Blackwell architecture, including the NVIDIA GeForce RTX 5090 GPU — provide next-level graphics and simulation capabilities.Co-packaged opticsswitches with integrated silicon photonics — built with light-speed fiber rather than copper wiring to send information quicker and using less power — enable efficient, high-performance, gigawatt-scale AI factories. The talk will also highlight NVIDIA Spectrum-XGS Ethernet, a new scale-across technology for unifying distributed data centers into AI super-factories.The NVIDIA GB10 Superchip serves as the engine within the NVIDIA DGX Spark desktop supercomputer.It’s all part of how NVIDIA’s latest technologies are accelerating inference to drive AI innovation everywhere, at every scale.
    NVIDIA Networking Fosters AI Innovation at Scale
    AI reasoning — when artificial intelligence systems can analyze and solve complex problems through multiple AI inference passes — requires rack-scale performance to deliver optimal user experiences efficiently.
    In data centers powering today’s AI workloads, networking acts as the central nervous system, connecting all the components — servers, storage devices and other hardware — into a single, cohesive, powerful computing unit.
    NVIDIA ConnectX-8 SuperNIC
    Burstein’s Hot Chips session will dive into how NVIDIA networking technologies — particularly NVIDIA ConnectX-8 SuperNICs — enable high-speed, low-latency, multi-GPU communication to deliver market-leading AI reasoning performance at scale.
    As part of the NVIDIA networking platform, NVIDIA NVLink, NVLink Switch and NVLink Fusion deliver scale-up connectivity — linking GPUs and compute elements within and across servers for ultra low-latency, high-bandwidth data exchange.
    NVIDIA Spectrum-X Ethernet provides the scale-out fabric to connect entire clusters, rapidly streaming massive datasets into AI models and orchestrating GPU-to-GPU communication across the data center. Spectrum-XGS Ethernet scale-across technology extends the extreme performance and scale of Spectrum-X Ethernet to interconnect multiple, distributed data centers to form AI super-factories capable of giga-scale intelligence.
    Connecting distributed AI data centers with NVIDIA Spectrum-XGS Ethernet.
    At the heart of Spectrum-X Ethernet, CPO switches push the limits of performance and efficiency for AI infrastructure at scale, and will be covered in detail by Shainer in his talk.
    NVIDIA GB200 NVL72 — an exascale computer in a single rack — features 36 NVIDIA GB200 Superchips, each containing two NVIDIA B200 GPUs and an NVIDIA Grace CPU, interconnected by the largest NVLink domain ever offered, with NVLink Switch providing 130 terabytes per second of low-latency GPU communications for AI and high-performance computing workloads.
    An NVIDIA rack-scale system.
    Built with the NVIDIA Blackwell architecture, GB200 NVL72 systems deliver massive leaps in reasoning inference performance.
    NVIDIA Blackwell and CUDA Bring AI to Millions of Developers
    The NVIDIA GeForce RTX 5090 GPU — also powered by Blackwell and to be covered in Blackstein’s talk — doubles performance in today’s games with NVIDIA DLSS 4 technology.
    NVIDIA GeForce RTX 5090 GPU
    It can also add neural rendering features for games to deliver up to 10x performance, 10x footprint amplification and a 10x reduction in design cycles,  helping enhance realism in computer graphics and simulation. This offers smooth, responsive visual experiences at low energy consumption and improves the lifelike simulation of characters and effects.
    NVIDIA CUDA, the world’s most widely available computing infrastructure, lets users deploy and run AI models using NVIDIA Blackwell anywhere.
    Hundreds of millions of GPUs run CUDA across the globe, from NVIDIA GB200 NVL72 rack-scale systems to GeForce RTX– and NVIDIA RTX PRO-powered PCs and workstations, with NVIDIA DGX Spark powered by NVIDIA GB10 — discussed in Skende’s session — coming soon.
    From Algorithms to AI Supercomputers — Optimized for LLMs
    NVIDIA DGX Spark
    Delivering powerful performance and capabilities in a compact package, DGX Spark lets developers, researchers, data scientists and students push the boundaries of generative AI right at their desktops, and accelerate workloads across industries.
    As part of the NVIDIA Blackwell platform, DGX Spark brings support for NVFP4, a low-precision numerical format to enable efficient agentic AI inference, particularly of large language models. Learn more about NVFP4 in this NVIDIA Technical Blog.
    Open-Source Collaborations Propel Inference Innovation
    NVIDIA accelerates several open-source libraries and frameworks to accelerate and optimize AI workloads for LLMs and distributed inference. These include NVIDIA TensorRT-LLM, NVIDIA Dynamo, TileIR, Cutlass, the NVIDIA Collective Communication Library and NIX — which are integrated into millions of workflows.
    Allowing developers to build with their framework of choice, NVIDIA has collaborated with top open framework providers to offer model optimizations for FlashInfer, PyTorch, SGLang, vLLM and others.
    Plus, NVIDIA NIM microservices are available for popular open models like OpenAI’s gpt-oss and Llama 4,  making it easy for developers to operate managed application programming interfaces with the flexibility and security of self-hosting models on their preferred infrastructure.
    Learn more about the latest advancements in inference and accelerated computing by joining NVIDIA at Hot Chips.
     
    #hot #topics #chips #inference #networking
    Hot Topics at Hot Chips: Inference, Networking, AI Innovation at Every Scale — All Built on NVIDIA
    AI reasoning, inference and networking will be top of mind for attendees of next week’s Hot Chips conference. A key forum for processor and system architects from industry and academia, Hot Chips — running Aug. 24-26 at Stanford University — showcases the latest innovations poised to advance AI factories and drive revenue for the trillion-dollar data center computing market. At the conference, NVIDIA will join industry leaders including Google and Microsoft in a “tutorial” session — taking place on Sunday, Aug. 24 — that discusses designing rack-scale architecture for data centers. In addition, NVIDIA experts will present at four sessions and one tutorial detailing how: NVIDIA networking, including the NVIDIA ConnectX-8 SuperNIC, delivers AI reasoning at rack- and data-center scale.Neural rendering advancements and massive leaps in inference — powered by the NVIDIA Blackwell architecture, including the NVIDIA GeForce RTX 5090 GPU — provide next-level graphics and simulation capabilities.Co-packaged opticsswitches with integrated silicon photonics — built with light-speed fiber rather than copper wiring to send information quicker and using less power — enable efficient, high-performance, gigawatt-scale AI factories. The talk will also highlight NVIDIA Spectrum-XGS Ethernet, a new scale-across technology for unifying distributed data centers into AI super-factories.The NVIDIA GB10 Superchip serves as the engine within the NVIDIA DGX Spark desktop supercomputer.It’s all part of how NVIDIA’s latest technologies are accelerating inference to drive AI innovation everywhere, at every scale. NVIDIA Networking Fosters AI Innovation at Scale AI reasoning — when artificial intelligence systems can analyze and solve complex problems through multiple AI inference passes — requires rack-scale performance to deliver optimal user experiences efficiently. In data centers powering today’s AI workloads, networking acts as the central nervous system, connecting all the components — servers, storage devices and other hardware — into a single, cohesive, powerful computing unit. NVIDIA ConnectX-8 SuperNIC Burstein’s Hot Chips session will dive into how NVIDIA networking technologies — particularly NVIDIA ConnectX-8 SuperNICs — enable high-speed, low-latency, multi-GPU communication to deliver market-leading AI reasoning performance at scale. As part of the NVIDIA networking platform, NVIDIA NVLink, NVLink Switch and NVLink Fusion deliver scale-up connectivity — linking GPUs and compute elements within and across servers for ultra low-latency, high-bandwidth data exchange. NVIDIA Spectrum-X Ethernet provides the scale-out fabric to connect entire clusters, rapidly streaming massive datasets into AI models and orchestrating GPU-to-GPU communication across the data center. Spectrum-XGS Ethernet scale-across technology extends the extreme performance and scale of Spectrum-X Ethernet to interconnect multiple, distributed data centers to form AI super-factories capable of giga-scale intelligence. Connecting distributed AI data centers with NVIDIA Spectrum-XGS Ethernet. At the heart of Spectrum-X Ethernet, CPO switches push the limits of performance and efficiency for AI infrastructure at scale, and will be covered in detail by Shainer in his talk. NVIDIA GB200 NVL72 — an exascale computer in a single rack — features 36 NVIDIA GB200 Superchips, each containing two NVIDIA B200 GPUs and an NVIDIA Grace CPU, interconnected by the largest NVLink domain ever offered, with NVLink Switch providing 130 terabytes per second of low-latency GPU communications for AI and high-performance computing workloads. An NVIDIA rack-scale system. Built with the NVIDIA Blackwell architecture, GB200 NVL72 systems deliver massive leaps in reasoning inference performance. NVIDIA Blackwell and CUDA Bring AI to Millions of Developers The NVIDIA GeForce RTX 5090 GPU — also powered by Blackwell and to be covered in Blackstein’s talk — doubles performance in today’s games with NVIDIA DLSS 4 technology. NVIDIA GeForce RTX 5090 GPU It can also add neural rendering features for games to deliver up to 10x performance, 10x footprint amplification and a 10x reduction in design cycles,  helping enhance realism in computer graphics and simulation. This offers smooth, responsive visual experiences at low energy consumption and improves the lifelike simulation of characters and effects. NVIDIA CUDA, the world’s most widely available computing infrastructure, lets users deploy and run AI models using NVIDIA Blackwell anywhere. Hundreds of millions of GPUs run CUDA across the globe, from NVIDIA GB200 NVL72 rack-scale systems to GeForce RTX– and NVIDIA RTX PRO-powered PCs and workstations, with NVIDIA DGX Spark powered by NVIDIA GB10 — discussed in Skende’s session — coming soon. From Algorithms to AI Supercomputers — Optimized for LLMs NVIDIA DGX Spark Delivering powerful performance and capabilities in a compact package, DGX Spark lets developers, researchers, data scientists and students push the boundaries of generative AI right at their desktops, and accelerate workloads across industries. As part of the NVIDIA Blackwell platform, DGX Spark brings support for NVFP4, a low-precision numerical format to enable efficient agentic AI inference, particularly of large language models. Learn more about NVFP4 in this NVIDIA Technical Blog. Open-Source Collaborations Propel Inference Innovation NVIDIA accelerates several open-source libraries and frameworks to accelerate and optimize AI workloads for LLMs and distributed inference. These include NVIDIA TensorRT-LLM, NVIDIA Dynamo, TileIR, Cutlass, the NVIDIA Collective Communication Library and NIX — which are integrated into millions of workflows. Allowing developers to build with their framework of choice, NVIDIA has collaborated with top open framework providers to offer model optimizations for FlashInfer, PyTorch, SGLang, vLLM and others. Plus, NVIDIA NIM microservices are available for popular open models like OpenAI’s gpt-oss and Llama 4,  making it easy for developers to operate managed application programming interfaces with the flexibility and security of self-hosting models on their preferred infrastructure. Learn more about the latest advancements in inference and accelerated computing by joining NVIDIA at Hot Chips.   #hot #topics #chips #inference #networking
    Hot Topics at Hot Chips: Inference, Networking, AI Innovation at Every Scale — All Built on NVIDIA
    blogs.nvidia.com
    AI reasoning, inference and networking will be top of mind for attendees of next week’s Hot Chips conference. A key forum for processor and system architects from industry and academia, Hot Chips — running Aug. 24-26 at Stanford University — showcases the latest innovations poised to advance AI factories and drive revenue for the trillion-dollar data center computing market. At the conference, NVIDIA will join industry leaders including Google and Microsoft in a “tutorial” session — taking place on Sunday, Aug. 24 — that discusses designing rack-scale architecture for data centers. In addition, NVIDIA experts will present at four sessions and one tutorial detailing how: NVIDIA networking, including the NVIDIA ConnectX-8 SuperNIC, delivers AI reasoning at rack- and data-center scale. (Featuring Idan Burstein, principal architect of network adapters and systems-on-a-chip at NVIDIA) Neural rendering advancements and massive leaps in inference — powered by the NVIDIA Blackwell architecture, including the NVIDIA GeForce RTX 5090 GPU — provide next-level graphics and simulation capabilities. (Featuring Marc Blackstein, senior director of architecture at NVIDIA) Co-packaged optics (CPO) switches with integrated silicon photonics — built with light-speed fiber rather than copper wiring to send information quicker and using less power — enable efficient, high-performance, gigawatt-scale AI factories. The talk will also highlight NVIDIA Spectrum-XGS Ethernet, a new scale-across technology for unifying distributed data centers into AI super-factories. (Featuring Gilad Shainer, senior vice president of networking at NVIDIA) The NVIDIA GB10 Superchip serves as the engine within the NVIDIA DGX Spark desktop supercomputer. (Featuring Andi Skende, senior distinguished engineer at NVIDIA) It’s all part of how NVIDIA’s latest technologies are accelerating inference to drive AI innovation everywhere, at every scale. NVIDIA Networking Fosters AI Innovation at Scale AI reasoning — when artificial intelligence systems can analyze and solve complex problems through multiple AI inference passes — requires rack-scale performance to deliver optimal user experiences efficiently. In data centers powering today’s AI workloads, networking acts as the central nervous system, connecting all the components — servers, storage devices and other hardware — into a single, cohesive, powerful computing unit. NVIDIA ConnectX-8 SuperNIC Burstein’s Hot Chips session will dive into how NVIDIA networking technologies — particularly NVIDIA ConnectX-8 SuperNICs — enable high-speed, low-latency, multi-GPU communication to deliver market-leading AI reasoning performance at scale. As part of the NVIDIA networking platform, NVIDIA NVLink, NVLink Switch and NVLink Fusion deliver scale-up connectivity — linking GPUs and compute elements within and across servers for ultra low-latency, high-bandwidth data exchange. NVIDIA Spectrum-X Ethernet provides the scale-out fabric to connect entire clusters, rapidly streaming massive datasets into AI models and orchestrating GPU-to-GPU communication across the data center. Spectrum-XGS Ethernet scale-across technology extends the extreme performance and scale of Spectrum-X Ethernet to interconnect multiple, distributed data centers to form AI super-factories capable of giga-scale intelligence. Connecting distributed AI data centers with NVIDIA Spectrum-XGS Ethernet. At the heart of Spectrum-X Ethernet, CPO switches push the limits of performance and efficiency for AI infrastructure at scale, and will be covered in detail by Shainer in his talk. NVIDIA GB200 NVL72 — an exascale computer in a single rack — features 36 NVIDIA GB200 Superchips, each containing two NVIDIA B200 GPUs and an NVIDIA Grace CPU, interconnected by the largest NVLink domain ever offered, with NVLink Switch providing 130 terabytes per second of low-latency GPU communications for AI and high-performance computing workloads. An NVIDIA rack-scale system. Built with the NVIDIA Blackwell architecture, GB200 NVL72 systems deliver massive leaps in reasoning inference performance. NVIDIA Blackwell and CUDA Bring AI to Millions of Developers The NVIDIA GeForce RTX 5090 GPU — also powered by Blackwell and to be covered in Blackstein’s talk — doubles performance in today’s games with NVIDIA DLSS 4 technology. NVIDIA GeForce RTX 5090 GPU It can also add neural rendering features for games to deliver up to 10x performance, 10x footprint amplification and a 10x reduction in design cycles,  helping enhance realism in computer graphics and simulation. This offers smooth, responsive visual experiences at low energy consumption and improves the lifelike simulation of characters and effects. NVIDIA CUDA, the world’s most widely available computing infrastructure, lets users deploy and run AI models using NVIDIA Blackwell anywhere. Hundreds of millions of GPUs run CUDA across the globe, from NVIDIA GB200 NVL72 rack-scale systems to GeForce RTX– and NVIDIA RTX PRO-powered PCs and workstations, with NVIDIA DGX Spark powered by NVIDIA GB10 — discussed in Skende’s session — coming soon. From Algorithms to AI Supercomputers — Optimized for LLMs NVIDIA DGX Spark Delivering powerful performance and capabilities in a compact package, DGX Spark lets developers, researchers, data scientists and students push the boundaries of generative AI right at their desktops, and accelerate workloads across industries. As part of the NVIDIA Blackwell platform, DGX Spark brings support for NVFP4, a low-precision numerical format to enable efficient agentic AI inference, particularly of large language models (LLMs). Learn more about NVFP4 in this NVIDIA Technical Blog. Open-Source Collaborations Propel Inference Innovation NVIDIA accelerates several open-source libraries and frameworks to accelerate and optimize AI workloads for LLMs and distributed inference. These include NVIDIA TensorRT-LLM, NVIDIA Dynamo, TileIR, Cutlass, the NVIDIA Collective Communication Library and NIX — which are integrated into millions of workflows. Allowing developers to build with their framework of choice, NVIDIA has collaborated with top open framework providers to offer model optimizations for FlashInfer, PyTorch, SGLang, vLLM and others. Plus, NVIDIA NIM microservices are available for popular open models like OpenAI’s gpt-oss and Llama 4,  making it easy for developers to operate managed application programming interfaces with the flexibility and security of self-hosting models on their preferred infrastructure. Learn more about the latest advancements in inference and accelerated computing by joining NVIDIA at Hot Chips.  
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  • يا جماعة، نحب نشارك معاكم حاجة جديدة في عالم الـ AI!

    اليوم، تكلمنا عن مقال مهم حول كيفية اختيار النماذج الأساسية لـ Generative AI. مع اتساع الخيارات المتاحة، احنا كمنظمات نواجه تحديات كبيرة في الاختيار. المقال هذا يقدم لنا منهجية تقييم شاملة مستخدمين Amazon Bedrock، لنجمعو بين النظريات والتطبيقات العملية. هذا الشي راح يعاوننا كبيانات علماء ومهندسين ML لنختار النموذج الأنسب لاحتياجاتنا.

    شخصياً، من تجربتي، كان عندي صعوبات في اختيار النماذج قبل ما أتعرف على الطرق الصحيحة. الذكاء الاصطناعي عالم زاخر بالفرص، ولازم نكونو جاهزين نستغلوها أحسن استغلال.

    الذكاء الاصطناعي قدامنا، ويحب منك شوية تفكير في اختياراتنا!

    https://aws.amazon.com/blogs/machine-learning/beyond-the-basics-a-comprehensive-foundation-model-selection-framework-for-generative-ai/

    #ذكاء_اصطناعي #AI #MachineLearning #AmazonBed
    🌟 يا جماعة، نحب نشارك معاكم حاجة جديدة في عالم الـ AI! 🌟 اليوم، تكلمنا عن مقال مهم حول كيفية اختيار النماذج الأساسية لـ Generative AI. مع اتساع الخيارات المتاحة، احنا كمنظمات نواجه تحديات كبيرة في الاختيار. المقال هذا يقدم لنا منهجية تقييم شاملة مستخدمين Amazon Bedrock، لنجمعو بين النظريات والتطبيقات العملية. هذا الشي راح يعاوننا كبيانات علماء ومهندسين ML لنختار النموذج الأنسب لاحتياجاتنا. شخصياً، من تجربتي، كان عندي صعوبات في اختيار النماذج قبل ما أتعرف على الطرق الصحيحة. الذكاء الاصطناعي عالم زاخر بالفرص، ولازم نكونو جاهزين نستغلوها أحسن استغلال. الذكاء الاصطناعي قدامنا، ويحب منك شوية تفكير في اختياراتنا! https://aws.amazon.com/blogs/machine-learning/beyond-the-basics-a-comprehensive-foundation-model-selection-framework-for-generative-ai/ #ذكاء_اصطناعي #AI #MachineLearning #AmazonBed
    aws.amazon.com
    As the model landscape expands, organizations face complex scenarios when selecting the right foundation model for their applications. In this blog post we present a systematic evaluation methodology for Amazon Bedrock users, combining theoretical fr
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  • "الذكاء ليس القدرة على الحصول على المعرفة فقط، بل القدرة على استخدامها بحكمة."

    يا جماعة، اليوم حبيت نشارك معاكم موضوع جديد وشيق: "A hazard analysis framework for code synthesis large language models". المقال يتحدث عن كيفية استخدام نماذج اللغة الكبيرة لتحليل المخاطر المرتبطة بتوليد الكود. يعني باختصار، كيفاش نضمنو أن الكود الذي نكتبو يكون آمن وفعّال.

    شخصياً، عندي تجربة مع هالنوع من النماذج، ولقيت أنه لما نفهمو المخاطر المحتملة، نقدر نطورو حلول أفضل ونقللو من الأخطاء. فعلاً، الإبداع لازم يترافق مع الوعي بالمخاطر.

    فكروا في هالموضوع، خليكم دايماً حذرين وأنتوما تتعاملو مع التكنولوجيا.

    https://openai.com/index/a-hazard-analysis-framework-for-code-synthesis-large-language-models

    #تحليل_المخاطر #CodeSynthesis #LanguageModels #تقنية #Innovation
    🌟 "الذكاء ليس القدرة على الحصول على المعرفة فقط، بل القدرة على استخدامها بحكمة." 🌟 يا جماعة، اليوم حبيت نشارك معاكم موضوع جديد وشيق: "A hazard analysis framework for code synthesis large language models". المقال يتحدث عن كيفية استخدام نماذج اللغة الكبيرة لتحليل المخاطر المرتبطة بتوليد الكود. يعني باختصار، كيفاش نضمنو أن الكود الذي نكتبو يكون آمن وفعّال. شخصياً، عندي تجربة مع هالنوع من النماذج، ولقيت أنه لما نفهمو المخاطر المحتملة، نقدر نطورو حلول أفضل ونقللو من الأخطاء. فعلاً، الإبداع لازم يترافق مع الوعي بالمخاطر. فكروا في هالموضوع، خليكم دايماً حذرين وأنتوما تتعاملو مع التكنولوجيا. https://openai.com/index/a-hazard-analysis-framework-for-code-synthesis-large-language-models #تحليل_المخاطر #CodeSynthesis #LanguageModels #تقنية #Innovation
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  • واخا، راكم شفتو الجديد من Framework!

    شوفو، الشركة هذي لي دايماً تدهشنا، خرجت لينا متربية جديدة: أول ديزكتوب PC صغير و زيد على ذلك أصغر لابتوب عندهم! و لكن يا جماعة، كاين حاجة كبيرة جاية في الطريق. يوم 26 أوت، راح يدمو لنا إعلان مباشر على يوتيوب، و يقولوا بلي "شيء كبير تحسن". واش راح تكون المفاجأة هذي؟ Framework 16؟

    شخصيا، كيما نحب نبدل في الكومبيوترات، نحب نعرف واش الجديد لي راح يجي. كيما كنت نتنقل كل مرة مع عربة صغيرة في حومتي، ونحب نحمل كل شيء، هذي التحديثات تخلي حياتنا أسهل و تفتح لنا آفاق جديدة.

    صحيح بلي الحياة عبارة عن تطور مستمر، و مع كل تحديث، راح نكتشف أكثر و أكثر.

    https://www.theverge.com/news/763037/framework-is-teasing-a-big-update-for-august-26th-could-it
    🥳 واخا، راكم شفتو الجديد من Framework! 😍 شوفو، الشركة هذي لي دايماً تدهشنا، خرجت لينا متربية جديدة: أول ديزكتوب PC صغير و زيد على ذلك أصغر لابتوب عندهم! و لكن يا جماعة، كاين حاجة كبيرة جاية في الطريق. يوم 26 أوت، راح يدمو لنا إعلان مباشر على يوتيوب، و يقولوا بلي "شيء كبير تحسن". واش راح تكون المفاجأة هذي؟ Framework 16؟ 🎉 شخصيا، كيما نحب نبدل في الكومبيوترات، نحب نعرف واش الجديد لي راح يجي. كيما كنت نتنقل كل مرة مع عربة صغيرة في حومتي، ونحب نحمل كل شيء، هذي التحديثات تخلي حياتنا أسهل و تفتح لنا آفاق جديدة. صحيح بلي الحياة عبارة عن تطور مستمر، و مع كل تحديث، راح نكتشف أكثر و أكثر. https://www.theverge.com/news/763037/framework-is-teasing-a-big-update-for-august-26th-could-it
    www.theverge.com
    Framework, the modular computer company, just released its first delightful tiny desktop PC, on top of its smallest laptop yet. But it’s already teasing its next big live announcement on YouTube for August 26th at 8am PT / 11am ET, saying it’ll revea
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