Eos Energy Enterprises, Inc. (NASDAQ:EOSE) is one of the stocks Jim Cramer commented on. Mentioning that they bought the stock last year, a caller asked what is going on with it. Here’s what Cramer had to say in response: Sell it. I mean, it’s just a kind of classic, that’s a year of magical thinking, magical investing stock. We don’t want to touch that one. But it is in Edison, New Jersey, which is where, by the way, Edison was born. It just happens to be a great coincidence. Stock market data. Photo ...

Core Insights - The article presents a counter-consensus viewpoint from Fei-Fei Li, emphasizing that large language models alone cannot lead to Artificial General Intelligence (AGI), and that spatial intelligence is a more foundational path [4][5][6]. Group 1: AGI Route Debate - Language is not the entirety of intelligence and is not its foundation; spatial intelligence, which has evolved over 500 million years, is crucial for AI development [5][6]. - If AI only possesses language capabilities, it will remain confined to the digital realm; true AGI requires understanding and interaction with the three-dimensional physical world [6]. Group 2: Redefining World Models - The newly introduced spatial intelligence model, Marble, can process multimodal inputs and create a navigable, interactive 3D world with physical consistency, differing from traditional video models [7][8]. - Marble has applications in various fields, including game development, visual effects, and even therapeutic settings for conditions like OCD [8]. Group 3: Scaling Law and Data Challenges - The slower development of physical world AI compared to language models is attributed to the noise in physical data and the difficulty in large-scale data acquisition [8][9]. - World Labs employs a hybrid data strategy, combining existing internet data with synthetic and real-world data to overcome these challenges [8][9]. Group 4: General Robotics vs. Autonomous Driving - General robotics is viewed as a higher-dimensional challenge compared to autonomous driving, which operates primarily in a 2D space [10][11]. - The core task of general robots involves interaction in 3D space, which presents significant technical challenges [10][11]. Group 5: AI as a Fundamental Infrastructure - AI is likened to electricity, with its success not measured by model size but by its ability to empower civilization and improve individual lives [11][12]. - The goal of World Labs is to integrate spatial intelligence into various industries, aiming for significant advancements by 2026 [12].

Eos Energy Enterprises Update Summary Company Overview - **Company**: Eos Energy Enterprises (NasdaqCM:EOSE) - **Industry**: Energy Storage Core Points and Arguments - **Energy Demand and System Strain**: The current energy system is under strain due to rising demand and expectations, which were not anticipated in the original grid design. This creates limitations for cities, industries, and data centers [1][2] - **Energy Storage as a Foundation**: Eos emphasizes that energy storage should not be a backup but the foundation of energy systems. Properly implemented storage can eliminate variability issues, allowing for smoother energy management and faster scaling of operations [2][3] - **Redefining Energy Storage**: Eos is reshaping energy storage by focusing on density, flexibility, and safety. The company introduces a new era of energy storage that is not limited by size or space, enabling limitless potential [3][4] - **Innovative Design Philosophy**: The company has developed the Z3 module, which is designed from the ground up using zinc chemistry. This module is safe, durable, and flexible, integrating intelligence through the Eos Dawn OS for real-time response and adaptation [4][5] - **Eos in Density Architecture**: The Eos in Density architecture is designed to deliver approximately four times the energy of traditional systems, targeting one gigawatt hour per acre. This high-density storage solution is adaptable to various environments, from rural to urban settings [5][9] - **Scalability and Configuration**: The system can be configured to achieve significant energy storage capacities, such as 250 megawatt hours per acre in rural areas, 500 megawatt hours in suburban areas, and up to one gigawatt hour in urban environments [9][10] - **Operational Flexibility**: The Eos in Density system allows for charging and discharging over a range of 4 to 16 hours, supporting multiple cycles per day and responding to grid demands in as little as five milliseconds [10][11] - **Safety Features**: Safety is a core aspect of the Eos in Density system, utilizing non-flammable materials and ensuring that all components are designed for safe operation in high-value infrastructure settings [11][12] Additional Important Content - **Team Expertise**: The development of the Eos in Density system is backed by a team with over 15 years of experience in energy storage, focusing on pushing boundaries and testing assumptions to create a system that adapts to changing conditions [13][14] - **Real-World Application**: Eos aims to provide energy solutions that support larger ideas and faster progress without compromising on safety or efficiency, positioning energy as a driver of innovation rather than a limitation [13][14]

Core Insights - Eos Energy Enterprises, Inc. has launched Eos Indensity™, a new energy storage architecture designed to enhance scalability and performance in real-world applications [1][2][4] - The Eos Indensity Core™ is a modular and stackable building block that allows for gigawatt-scale storage, adapting to various site-specific challenges [3][5] Product Features - Eos Indensity™ incorporates Spatial Intelligence, a design framework that addresses the needs of built, human, and natural environments [2][4] - The system is engineered for flexibility, capable of supporting energy storage durations of 4 to 16+ hours, and is designed to handle complex cycling with rapid response times [8] - The architecture targets a density of 1 GWh per acre, which is approximately four times that of most other technologies [8] Safety and Sustainability - The energy storage solution utilizes non-flammable zinc chemistry and recyclable components, ensuring safety for mission-critical sites [8] - Eos aims to accelerate the shift towards energy independence with innovative solutions that are stable, secure, and scalable compared to conventional lithium-ion technology [7]

Core Viewpoint - ViewX has launched its innovative 15.6-inch Spatial Smart Display at CES 2026, which offers glasses-free 3D visuals and seamless switching between 2D and 3D modes, catering to various visual needs across multiple scenarios [1][7]. Product Features - The Spatial Smart Display utilizes a dual-mode intelligent display system and one-click 2D-to-3D conversion technology, ensuring excellent 2D image quality while eliminating moiré patterns common in traditional glasses-free 3D displays [4][5]. - It connects easily to a variety of devices, including laptops, desktops, gaming consoles, tablets, and smartphones, supporting major operating systems like Windows, macOS, and Android, thus providing true plug-and-play functionality [3][4]. - The display is powered by advanced AI algorithms that reconstruct natural depth information, resulting in rich and immersive 3D visuals [6]. Market Reception - The product received strong interest at CES 2026, with attendees impressed by its performance, color accuracy, and 3D depth effect, leading to extended hands-on sessions and discussions [7]. - ViewX aims to redefine human-computer visual interaction with the vision of "Everything in 3D," indicating a significant shift in 3D viewing experiences [7]. Future Plans - The ViewX Spatial Smart Display is set to launch in the U.S. market in the first half of 2026, with plans for a gradual global rollout thereafter [7].

Core Insights - The article discusses the launch of Depth Any Panoramas (DAP), a foundational model for panoramic depth estimation, which addresses the challenges of data scarcity and model generalization in spatial intelligence [1][19]. Data and Model Development - DAP is trained on an unprecedented scale of 2 million (2M) panoramic images, significantly surpassing previous datasets like Stanford2D3D and Matterport3D, which had only tens of thousands of images [6][7]. - The model utilizes a three-stage pseudo-labeling pipeline to refine the quality of depth estimation from unlabelled panoramic images, ultimately creating a robust training dataset [10][11]. Performance and Benchmarking - DAP has demonstrated superior performance in various benchmarks, achieving significant reductions in absolute relative error (AbsRel) and root mean square error (RMSE) across indoor and outdoor datasets [14][17]. - In zero-shot testing, DAP outperformed existing models, showcasing its strong generalization capabilities and effective depth prediction in complex environments [13][16]. Technological Innovations - The model incorporates advanced features such as a distance-adaptive range mask head, allowing it to adjust depth perception based on different application scenarios [16]. - DAP employs multi-dimensional geometric optimization techniques to ensure sharp edges and accurate geometric structures in depth maps, addressing common issues like depth holes and structural distortion [16]. Industry Implications - The introduction of DAP marks a significant milestone in panoramic depth estimation, enabling advancements in autonomous driving, robotics, and VR/AR content creation by providing a low-cost method for depth acquisition [19][20]. - The project has been made open-source, allowing broader access to its technology and fostering further innovation in the field of spatial intelligence [20].

在空间智能（Spatial Intelligence）飞速发展的今天，全景视角因其 360° 的环绕覆盖能力，成为了机器人导航、自动驾驶及虚拟现实的核心基石。然而，全景深度 估计长期面临 "数据荒" 与 "模型泛化差" 的瓶颈。 近日， 来自 Insta360 研究团队、加州大学圣地亚哥分校 (UCSD)、武汉大学以及加州大学默塞德分校的研究者 共同推出了 Depth Any Panora mas (DAP) 。这是首 个在大规模多样化数据集上训练的全景度量深度（Metric Depth）基础模型，不仅统一了室内外场景，更通过 200 万量级的数据引擎与创新的几何一致性设计，刷 新了多项 benchmark 纪录，在多种 open-world 场景下保持优异的效果。 模型对由 Gemini 或 DiT-360 等合成的全景图同样展现出了极佳的预测效果，生成的深度图边缘锐利、逻辑自洽，是空间 AIGC 链路中理想的几何基石。 除了静态 图像，DAP 在处理全景视频流时同样展现出了极佳的预测效果，具备优秀的帧间一致性与稳定性 。 论文标题：Depth Any Panoramas: A Foundation Mod ...

Core Insights - Realsee has launched Realsee3D, a dataset containing 10,000 indoor 3D scenes, aimed at supporting academic research and non-commercial purposes, potentially making it the largest spatial 3D dataset globally [1][3] - The dataset is designed to enhance research in indoor 3D perception, reconstruction, and scene understanding, addressing the existing gap in high-quality spatial data [3][6] Dataset Features - The Realsee3D dataset includes 10,000 unique indoor scenes, comprising 95,962 rooms and 299,073 viewpoints/RGB-D pairs, providing a rich resource for researchers [8] - It features panoramic RGB-D captures with complete room-level coverage and comprehensive annotations, including CAD drawings, floor plans, and semantic segmentation [8] - The dataset consists of 1,000 real-world scenes with diverse layouts and decoration styles, along with 9,000 procedurally generated scenes using over 100 designer-curated style templates [8] Research Applications - The dataset is suitable for core research directions in spatial intelligence, such as geometric reconstruction, multi-modal learning, and embodied AI, encouraging global researchers and developers to explore the future of spatial intelligence [6][7]

Core Insights - The company is rebranding to Inturai Ventures Corp to reflect its focus on the Inturai spatial intelligence platform [1] - The new ticker symbol "URAI" aligns with the company's development in defense, AI, and sensing technologies [1] - The business model is advancing in line with the commercialization of the platform and expansion into the military sector [1] Company Developments - The company has received conditional approval from the Canadian Securities Exchange for the name change [1] - The shift in focus towards Inturai technology marks a strategic pivot for the company [1]

AI Technology & Innovation - Tencent's 3D world generation model is now industry-leading, signifying a push into AI beyond language models [1] - World models represent a new frontier in AI, attracting major companies and researchers [2] - World models simulate reality, understanding depth, physics, and context from single images, unlike LLMs that describe reality [4] - World models may not require the same brute force GPU power as LLMs, applying learned rules instead of crunching probabilities [5] - Spatial intelligence, teaching machines to understand the world like humans, is a key concept behind world models [6] Market Potential & Applications - World models could open up entirely new markets and change the economics of AI [7] - Potential use cases include real estate (touring houses), interior design, digital twins, manufacturing, and autonomous driving [8][9] Competitive Landscape - Companies like Tencent, Google, Nvidia, and World Labs are actively involved in developing world models [2] - Meta's chief AI scientist is reportedly leaving to focus on world models [2] Cost & Efficiency - A basic 3D model can be generated quickly (within 5 minutes) from a single image, with options for more detailed models at a cost (e.g., $20 for more photos) [3][7][8]