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PGA Tour unleashes AI revolution with AWS to transform golf viewing experience for fans worldwide
Fox Business· 2026-01-18 20:16
The PGA Tour has taken its partnership with Amazon Web Services to the next level. Since 2021, the PGA Tour and AWS have partnered together to deliver technical breakthroughs that are reshaping golf’s digital landscape.But as the golf season kicked off Thursday with the Sony Open in Hawaii, the Tour has modernized operations and scaled up production capabilities using AWS AI infrastructure in a live production environment. CLICK HERE FOR MORE SPORTS COVERAGE ON FOXBUSINESS.COM The expanded partnership will ...
刚刚,Geoffrey Hinton成为第二位引用量破百万的科学家
3 6 Ke· 2026-01-16 02:25
在他之前,只有他的老搭档、另一位「深度学习教父」Yoshua Bengio 达成了这一成就。目前,Hinton 的引用量仍在以惊人的速度增长,每一次引用都代 表着他对人工智能领域不可磨灭的贡献。从反向传播算法的推广到 AlexNet 的惊艳问世,从获得图灵奖到斩获 2024 年诺贝尔物理学奖,Hinton 的职业生 涯几乎就是一部现代 AI 的发展史。 这一数字不仅是学术影响力的量化,更是对这位 78 岁长者一生执着探索的最高致敬。 刚刚,Geoffrey Hinton 正式成为历史上第二位 Google Scholar 引用量突破 100 万大关的计算机科学家。 | TITLE | CITED BY | YEAR | | --- | --- | --- | | | * | | | Imagenet classification with deep convolutional neural networks | 188837 | 2012 | | A Krizhevsky, I Sutskever, GE Hinton, | | | | Advances in neural information proce ...
Gorilla Technology to Host Live Investor Webinar and Q&A on January 28
TMX Newsfile· 2026-01-15 14:00
Core Insights - Gorilla Technology Group Inc. will participate in an investor webinar on January 28, 2026, to discuss its latest milestones and strategic objectives for 2026 [1][2]. Company Overview - Gorilla Technology Group Inc. is a global solution provider specializing in AI-driven Security Intelligence, Network Intelligence, Business Intelligence, and IoT technology, with over 24 years of operating history and 29 granted patents [3]. - The company is headquartered in London, U.K., and offers a wide range of solutions across various sectors, including Government & Public Services, Manufacturing, Telecom, Retail, Transportation & Logistics, Healthcare, and Education [4]. Financial Performance - Gorilla has a growing pipeline exceeding $7 billion, driven by strong demand for GPU-as-a-Service infrastructure, AI-powered smart cities, and mission-critical security platforms [3]. - Recent milestones include a $1.4 billion multi-year partnership to deploy AI-ready data centers in Southeast Asia and continued expansion of public safety programs in Asia and Latin America [3]. - The company reaffirmed its 2025 revenue guidance of $100-$110 million with EBITDA margins of 20-25% and expects 2026 revenue to range from $137 million to $200 million, reflecting increasing scale and sustained momentum [3].
Magnite and Cognitiv Announce Deep Learning Integration for Real-Time Curation
Globenewswire· 2026-01-06 13:00
Core Insights - Magnite and Cognitiv have announced a partnership to enhance real-time data integration, improving curation capabilities within Magnite's ClearLine solution, which allows media buyers to access premium video inventory more effectively [1][2] Company Overview - Magnite is the largest independent sell-side advertising company, providing technology for publishers to monetize content across various formats including CTV, online video, display, and audio [4] - Cognitiv is a leading advanced performance partner utilizing deep learning to predict consumer behavior and optimize advertising strategies [5] Industry Context - The media landscape is becoming increasingly fragmented across multiple channels such as streaming TV, audio, display, and mobile, necessitating advanced solutions for effective media curation [2] - The complexity of the programmatic ecosystem is driving demand for AI solutions that can enhance content signals and streamline workflows for buyers [3]
Kara Büyünün Ardında | Burak Sina Akbudak | TEDxIzmir Fen Lisesi Youth
TEDx Talks· 2025-12-22 15:39
bir Karabü'den bahsedeceğim ya da başka bir de işte nasıl firmalar bütçelerini daha karabük olarak nitlendirdiğimiz bir şey için çarşı ediyorlar ya da nasıl bir sürü do işlem alanında yıllarını vermiş araştırmacılar eee sırf bu şirketlerin açığı yüzünden maalesef e hayata küsü ya da çalışmalarını eee devam ettiremiyor ve doğru tahmin ettiniz diye tahmin ediyorum. Eee ve bugün biraz yapay zeka konuşacağız. eee, bir adım adım yapay zeka oluştururken e hangi adımlara dikkat ediyoruz. Eee, ya da evet yani bir y ...
MicroCloud Hologram Inc. Develops Quantum-Enhanced Deep Convolutional Neural Network Image 3D Reconstruction Technology
Prnewswire· 2025-12-18 15:30
Core Viewpoint - MicroCloud Hologram Inc. has launched a quantum-enhanced deep convolutional neural network image 3D reconstruction technology system, which integrates quantum computing with deep learning to improve the precision and adaptability of 3D model generation [1][8]. Group 1: Technology Overview - The new system consists of six core modules: quantum-optimized dataset preparation, quantum-assisted feature extraction, quantum-enhanced parameter generation, quantum-accelerated 3D reconstruction, quantum-precision model evaluation, and an interactive application interface [2]. - The quantum-optimized dataset preparation module is crucial for ensuring high-quality 3D model data, which is essential for the deep learning algorithm to accurately learn morphological features [3]. - The quantum-assisted feature extraction module utilizes quantum convolutional neural networks to efficiently extract higher-level features from input images, overcoming limitations of traditional algorithms [4]. - The quantum-enhanced parameter generation module maps high-dimensional feature vectors to three-dimensional space, allowing for refined control over model attributes such as shape and size [5]. - The quantum-accelerated 3D reconstruction module generates high-precision 3D models by leveraging quantum computing's parallel processing capabilities [6]. - The quantum-precision model evaluation module optimizes algorithm parameters based on error measurements, enhancing the robustness of the 3D reconstruction model [7]. Group 2: Competitive Advantages - Compared to traditional 3D reconstruction algorithms, the new system offers significant advantages in precision and adaptability, enabling better alignment with actual needs through quantum-accelerated training on large datasets [8]. - The technology has broad application prospects across various fields, including medical diagnostics, robotics, and manufacturing, with potential integration into augmented and virtual reality technologies [9][10]. Group 3: Company Background - MicroCloud Hologram Inc. focuses on holographic technology and has a cash reserve exceeding 3 billion RMB, with plans to invest over 400 million USD in quantum computing and related technologies [11]. - The company aims to become a global leader in quantum holography and quantum computing technology [11].
美国 IT 硬件-专家洞察:AI 数据中心需要多少内存-U.S. IT Hardware-Expert Insight How much memory do AI Data Centers need
2025-12-15 01:55
Summary of Key Points from the Webinar on AI Data Center Memory Demand Industry Overview - The discussion centers around the U.S. IT Hardware industry, specifically focusing on AI data centers and their memory requirements [1][12]. - The webinar featured Gunjan Shah, a former Senior Cloud Engineer at Google, who provided insights into memory demand for AI workloads [1][12]. Core Insights Memory Demand in AI - Training AI models requires significantly more memory than inference, with medium-sized models consuming approximately 1TB of memory during training compared to much lower demands during inference [2][15]. - The rapid adoption of AI has led to a sharp increase in memory demand and prices, particularly for components like HBM (High Bandwidth Memory) and DRAM [3][21]. - Innovations in model architectures and memory technologies are expected to help manage memory demand sustainably in the long term [3][18]. Shift from HDDs to SSDs - Due to HDD shortages, many hyperscalers are transitioning to SSDs, which are 5 to 10 times more expensive but offer superior performance and lower operational costs [4][38]. - SSDs provide benefits such as reduced power consumption and minimal cooling requirements, contributing to a lower total cost of ownership (TCO) [4][40]. Emerging Memory Technologies - High Bandwidth Flash (HBF) is an emerging technology that aims to provide fast, non-volatile memory, potentially lowering energy consumption and cooling costs for AI inference workloads [5][18]. Investment Implications - Companies such as Seagate Technology (STX), Western Digital (WDC), SanDisk (SNDK), Samsung, SK Hynix, and Micron have been rated with specific price targets based on their performance in the memory market [7][8][9][10][11]. - STX is rated Outperform with a price target of $370, while WDC is rated Market-Perform with a target of $170 [8][9]. Additional Insights Memory Usage Breakdown - The memory footprint for training is heavily reliant on model weights, activations, and gradients, while inference requires only temporary tensors and KV caches [15][16]. - The demand for storage during training is significantly higher, with requirements ranging from terabytes to petabytes depending on the model size [24][25]. Market Dynamics - The demand for memory is outpacing supply, leading to increased prices for HBM, DRAM, and SSDs [21][29]. - Hyperscalers are signing multi-year purchase agreements and vertically integrating into chip design to secure memory supplies [29][36]. Comparison of AI Models - Gemini 3.0 is currently outperforming ChatGPT 5.0 in various benchmarks, attributed to its optimized training and architecture [33][34]. - The U.S. is leading in AI model development compared to China, with significant differences in performance and resource availability [35][36]. Cost Considerations - Despite the higher initial costs of SSDs, their lower operational costs and performance benefits make them more economical for performance-critical tasks over time [40][42]. - The TCO for SSDs is favorable due to lower power consumption, reduced cooling needs, and higher reliability compared to HDDs [40][42]. Conclusion - The AI data center memory landscape is evolving rapidly, driven by increasing model sizes and the need for efficient memory solutions. The shift from HDDs to SSDs and the emergence of new memory technologies are key trends to watch in this sector.
X @Avi Chawla
Avi Chawla· 2025-12-14 19:17
AI Engineering Resources - Stanford 提供 6 份 AI 工程师必备的速查表 [1] - 速查表涵盖监督/非监督机器学习 [1] - 速查表涉及深度学习 [1] - 速查表包含机器学习技巧与窍门 [1] - 速查表包括概率与统计 [1] - 速查表覆盖代数与微积分 [1]
X @Avi Chawla
Avi Chawla· 2025-12-14 14:30
AI Resources - Stanford provides 6 must-read cheat sheets for AI Engineers [1] - The cheat sheets cover Supervised/Unsupervised ML, Deep Learning, ML Tips & Tricks, Probability & Statistics, Algebra & Calculus [1] Social Sharing - The author encourages readers to reshare the content [1] - The author shares tutorials and insights on DS, ML, LLMs, and RAGs daily [1]
X @Avi Chawla
Avi Chawla· 2025-12-14 06:47
AI Engineering Resources - Stanford provides 6 must-read cheat sheets for AI Engineers [1] - The cheat sheets cover Supervised/Unsupervised ML, Deep Learning, ML Tips & Tricks, Probability & Statistics, Algebra & Calculus [1]