New AI “copilot” helps engineers design better structures (يفتح في تبويب جديد)
- الكاتب
- Zach Winn | MIT News
The system asks humans for feedback to increase trust in machine-generated designs for buildings and bridges.
تابع أحدث التطورات والنماذج والأبحاث والأدوات والتقنيات في عالم الذكاء الاصطناعي من مصادرها الأصلية.
مرتبة حسب تاريخ النشر الأصلي. ابحث وصفِّ دون إعادة تحميل الصفحة.
The system asks humans for feedback to increase trust in machine-generated designs for buildings and bridges.
What's new in research at Microsoft? Host Anson Ho explores the latest, including AI-powered universal translation, a breakthrough in a 31-year-old mathematics challenge, and advances making AI coding agents faster and more efficient.
Frontier video generation models work in a VAE latent space that compresses video in both space and time. This compression made training tractable, but now limits high-resolution, controllable, and interactive generation -- doubling resolution quadruples token count, conditions apply to groups of frames rather than individual ones, and each response must wait for the rest of its multi-frame block. We present PixVid…
How multimodal language models should encode visual input remains up for debate. Most models use a pretrained vision encoder, while some recent recipes train the encoder from scratch with the language model or remove it entirely. Vision encoders bundle together three design choices: a visual prior from upstream pretraining, dedicated vision capacity, and pre-fusion placement of that capacity (i.e., before the…
Model architecture shapes the scaling behavior, training efficiency, and inference cost of LLMs, making it a central focus of both industry and academia. In industry, teams such as those behind DeepSeek, Qwen, and Kimi routinely introduce architectural innovations, yet public reports rarely document which ideas succeeded, which were abandoned, and why. In academia, limited compute and inconsistent baselines often…
Decoder-only Large View Synthesis Models (LVSMs) with KV-cache have recently achieved state-of-the-art quality by regressing novel views from neural networks without reconstructing 3D geometry, while Test-Time Training (TTT) layers save computation but sacrifice quality. We propose Test-Time Baking (TTB), a strategy that learns to bake global scene information from cross-view attention into a lightweight MLP…
Vision language navigation (VLN) is very challenging for Unmanned Aerial Vehicles (UAVs) since small errors in 3D motion prediction can lead to navigation errors and collisions. Unable to fathom execution outcomes in 3D environments, existing methods often struggle to predict accurate navigation waypoints from language instructions. To solve this, we introduce the Prototypical Visual Imagination framework, shortened…
Institutional portfolios operate under investment policy statements that specify asset allocation constraints, often conditioned on market regime information. Deep reinforcement learning has been shown to optimize financial performance but typically does not enforce rule compliance, making it unsuitable for real-world deployment. Existing neurosymbolic methods such as Probabilistic Logic Policy Gradient (PLPG) offer…
Video diffusion models are able to generate samples with high-quality appearance and textural qualities. However, content produced by these methods is known to exhibit significant physical errors. This is because, in a classical video generation setting, all physical reasoning must take place simultaneously and exclusively within the diffusion process.We propose to resolve these issues by redistributing the task of…
Applying machine learning systems to new domains introduces bottlenecks in both labeled data acquisition and manual pipeline engineering. While recent MLE agents show promise in automating pipeline design, they have been studied almost exclusively in fully supervised settings, leaving them untested in realistic regimes where labeled data is scarce but unlabeled data is abundant. In this work, we introduce Agentic…
Given a set of LEGO parts and an image of an assembled object, our task is to infer the pose of each part to assemble the object. In contrast with traditional 3D reconstruction, doing so requires satisfying discrete physical constraints, which provide structure but render the problem combinatorial and highly sensitive to small pose errors. To learn a prior over how parts fit together, we train a set-conditioned…
Spatial intelligence requires connecting visual observations to the geometry, objects, and persistent state of an environment. Images alone leave these relationships implicit, while disconnected annotations make it difficult to study appearance, camera motion, and scene changes under a common reference. We introduce Spatial Foundry, a collection of 5,280 furnished residential 3D scene configurations with editable…
من arXiv وHugging Face Papers، مع الملخص الأصلي ورابط PDF الرسمي عند توفره.
Frontier video generation models work in a VAE latent space that compresses video in both space and time. This compression made training tractable, but now limits high-resolution, controllable, and interactive generation -- doubling resolution quadruples token count, conditions apply to groups of frames rather than individual ones, and each response must wait for the rest of its multi-frame block. We present PixVid…
How multimodal language models should encode visual input remains up for debate. Most models use a pretrained vision encoder, while some recent recipes train the encoder from scratch with the language model or remove it entirely. Vision encoders bundle together three design choices: a visual prior from upstream pretraining, dedicated vision capacity, and pre-fusion placement of that capacity (i.e., before the…
Model architecture shapes the scaling behavior, training efficiency, and inference cost of LLMs, making it a central focus of both industry and academia. In industry, teams such as those behind DeepSeek, Qwen, and Kimi routinely introduce architectural innovations, yet public reports rarely document which ideas succeeded, which were abandoned, and why. In academia, limited compute and inconsistent baselines often…
Decoder-only Large View Synthesis Models (LVSMs) with KV-cache have recently achieved state-of-the-art quality by regressing novel views from neural networks without reconstructing 3D geometry, while Test-Time Training (TTT) layers save computation but sacrifice quality. We propose Test-Time Baking (TTB), a strategy that learns to bake global scene information from cross-view attention into a lightweight MLP…
Vision language navigation (VLN) is very challenging for Unmanned Aerial Vehicles (UAVs) since small errors in 3D motion prediction can lead to navigation errors and collisions. Unable to fathom execution outcomes in 3D environments, existing methods often struggle to predict accurate navigation waypoints from language instructions. To solve this, we introduce the Prototypical Visual Imagination framework, shortened…
Institutional portfolios operate under investment policy statements that specify asset allocation constraints, often conditioned on market regime information. Deep reinforcement learning has been shown to optimize financial performance but typically does not enforce rule compliance, making it unsuitable for real-world deployment. Existing neurosymbolic methods such as Probabilistic Logic Policy Gradient (PLPG) offer…
نماذج من Hugging Face مع الجهة المطوِّرة والمهمة.
مستودعات وإصدارات مفتوحة المصدر من GitHub.
Arabic-aware RAG over a real, public SQU document: from-scratch normalisation + Light10 light stemming, measured against naive token matching with the same BM25 index -- 0.792 vs 0.048 recall@5. Animated web UI recorded live.
Chat in Arabic with Salah al-Din and Muhammad Ali Pasha as 3D talking avatars: RAG over Wikipedia, free Groq LLM, Edge TTS and Arabic viseme lip sync (FastAPI + Docker).
Karpathy's tiny GPT trained on pre-Islamic Arabic poetry, compared with Shakespeare.
langchain-typesafe 0.1.0 drops support for Python 3.10, which has reached end-of-life. The minimum supported version is now Python 3.11, and the minimum langchain-core version is now 1.8.0 (langchain 1.5.0 for the experimental extra). Users on Python 3.10 will continue to resolve langchain-typesafe 0.0.x. Changes since langchain-typesafe==0.0.2 release(typesafe): 0.1.0 (#41800) refactor(typesafe): deprecate…
langchain 1.5.0 drops support for Python 3.10, which has reached end-of-life. The minimum supported version is now Python 3.11, and the minimum langchain-core version is now 1.8.0. Users on Python 3.10 will continue to resolve langchain 1.4.x. Changes since langchain==1.4.10 release(langchain): 1.5.0 (#41798) fix(langchain): mark ModelRouterMiddleware as beta (#41797) feat(langchain): Remove EOL'd Python 3.10 from…
langchain-core 1.8.0 drops support for Python 3.10, which has reached end-of-life. The minimum supported version is now Python 3.11. Users on Python 3.10 will continue to resolve langchain-core 1.7.x. Changes since langchain-core==1.7.7 release(core): 1.8.0 (#41796) feat(core): Remove EOL Python 3.10 support (#41267) feat(core): add decision models (#41765)
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