Zebra Technologies (NasdaqGS:ZBRA) Q4 2025 Earnings call February 12, 2026 08:30 AM ET Company ParticipantsBill Burns - CEOGuy Hardwick - DirectorJoseph Giordano - Managing DirectorMike Steele - VP of Investor RelationsNathan Winters - CFOPiyush Avasthy - Equity Research Senior AssociateConference Call ParticipantsAndrew Buscaglia - Senior Analyst of US Industrial TechnologyBrad Hewitt - VP and Equity AnalystJim Ricchiuti - Managing Director and Senior Equity Research AnalystKeith Housum - Equity Research A ...

Zebra Technologies (NasdaqGS:ZBRA) Q4 2025 Earnings call February 12, 2026 08:30 AM ET Company ParticipantsBill Burns - CEOGuy Hardwick - DirectorJoseph Giordano - Managing DirectorMike Steele - VP of Investor RelationsNathan Winters - CFOPiyush Avasthy - Equity Research Senior AssociateConference Call ParticipantsAndrew Buscaglia - Senior Analyst of US Industrial TechnologyBrad Hewitt - VP and Equity AnalystJim Ricchiuti - Managing Director and Senior Equity Research AnalystKeith Housum - Equity Research A ...

Zebra Technologies (NasdaqGS:ZBRA) Q4 2025 Earnings call February 12, 2026 08:30 AM ET Speaker9Good day, and welcome to the fourth quarter and full year 2025 Zebra Technologies Earnings Conference Call. All participants will be in listen-only mode. Should you need assistance, please signal a conference specialist by pressing the star key followed by zero. After today's presentation, there will be an opportunity to ask questions. Please note, this event is being recorded. I would now like to turn the confere ...

Group 1 - The core viewpoint of the news is that Lingyun Technology experienced a decline in stock price and trading volume, with significant financing activities indicating a high level of market interest despite the drop [1] - On January 26, Lingyun Technology's stock fell by 3.33%, with a trading volume of 533 million yuan. The financing buy-in amount was 62.39 million yuan, while the financing repayment was 69.33 million yuan, resulting in a net financing outflow of 6.94 million yuan [1] - As of January 26, the total financing and securities lending balance for Lingyun Technology was 734 million yuan, with the financing balance accounting for 3.82% of the circulating market value, indicating a high level compared to the past year [1] Group 2 - As of January 9, the number of shareholders for Lingyun Technology was 31,800, an increase of 1.79% from the previous period, while the average circulating shares per person decreased by 1.76% to 14,482 shares [2] - For the period from January to September 2025, Lingyun Technology achieved an operating income of 2.127 billion yuan, representing a year-on-year growth of 34.30%, and a net profit attributable to the parent company of 133 million yuan, up 18.46% year-on-year [2] - Since its A-share listing, Lingyun Technology has distributed a total of 92.28 million yuan in dividends [2]

Core Insights - The Food Robotics Market is projected to grow from USD 3.77 billion in 2024 to USD 11.07 billion by 2032, reflecting a compound annual growth rate (CAGR) of 14.38% [2][12]. - The growth is driven by advancements in robotics technologies, culinary innovation, and increased demand for automation in food production, logistics, and quality assurance [3][4]. Technological Innovations Driving Market Expansion - Innovations in machine vision, artificial intelligence, and adaptive end effectors are enhancing the capabilities of robotic systems, allowing them to perform complex tasks with minimal human intervention [6]. - Energy-efficient systems and recyclable components are aligning with global sustainability initiatives, making robotics a key driver for resilient food supply chains [6]. Strategic Segmentation Insights - Different types of robotics, such as articulated, Cartesian, delta, and Scara systems, have unique capabilities that can be leveraged for specific operational demands [7][8]. - Understanding these distinctions allows stakeholders to identify strategic investment opportunities and improve competitive positioning [8]. Regional Dynamics and Market Opportunities - The Americas are leading in innovations related to smart cold chain networks, while Europe, the Middle East, and Africa are integrating robotics due to stringent safety regulations and rising labor costs [9]. - In the Asia-Pacific region, the demand for scalable automation is driving growth, necessitating tailored market entry strategies [9][10]. Market Insights - The food robotics market is expected to triple in size by 2032, presenting significant investment opportunities in automation solutions [14]. - The report emphasizes the importance of understanding regional dynamics and infrastructure for effective market strategies [14]. Key Applications of Food Robotics - Deployment of AI-enabled robotic arms for precision tasks in confectionery and chocolate decorating [15]. - Adoption of autonomous mobile robots for inventory monitoring in food warehouses [15]. - Integration of vision-guided robotics for automated quality inspection of fresh produce [15]. - Use of collaborative robots in quick service restaurants to streamline meal assembly [15]. - Development of temperature-controlled robotic arms for safe handling of frozen foods [15]. - Implementation of cloud-connected robotics for predictive maintenance in food processing [15]. - Deployment of AI-driven robotic solutions in meat processing to reduce waste [15]. - Emergence of end-to-end automation solutions in dairy production [15]. - Customization of robotic systems for automated bakery workflows [15]. - Integration of UV sterilization modules on food robotics equipment to enhance sanitation [16].

Core Insights - Cognex positions itself as a technology leader in the machine vision sector, which is a subsegment of factory automation [2][3] - The company has been shifting towards a direct sales approach over the past few years, broadening its customer base [3] - Cognex differentiates itself through its software capabilities and enhanced customer experience, contributing to attractive growth and strong profit margins [3]

Core Insights - The article discusses the significant advancements in computer vision and the challenges faced in deploying high-precision models in resource-constrained environments, such as robotics and autonomous driving, due to increased computational demands and energy consumption [2][3]. - It highlights the limitations of existing global representation learning paradigms, which process all pixels of an image or video simultaneously, leading to inefficiencies in energy and computational resources [3]. - The article introduces the AdaptiveNN architecture, which emulates human-like adaptive vision by modeling visual perception as a sequential decision-making process, allowing for efficient and flexible machine visual perception [7][11]. Group 1: Challenges in Current Computer Vision Models - High-precision models require activation of millions of parameters, resulting in increased power consumption, storage needs, and response delays, making them difficult to deploy in real-world applications [2]. - The global parallel computation paradigm leads to a significant energy efficiency bottleneck, as the computational complexity grows with the input size, making it challenging to balance high-resolution input, performance, and efficient inference [3]. Group 2: Insights from Human Visual System - Human vision operates through selective sampling of key areas rather than processing all visual information at once, which significantly reduces computational overhead and allows for efficient functioning even in resource-limited scenarios [5]. - The concept of "active observation" proposed by researchers emphasizes the need for AI systems to adopt a human-like approach to visual perception, focusing on task-driven observation [5]. Group 3: Introduction of AdaptiveNN - AdaptiveNN architecture models visual perception as a multi-step sequential decision process, allowing the model to focus on specific areas of interest and accumulate information progressively [11]. - The architecture combines representation learning with self-rewarding reinforcement learning, enabling the model to optimize its attention and decision-making without additional supervision [15][16]. Group 4: Performance and Efficiency of AdaptiveNN - In extensive experiments, AdaptiveNN achieved up to 28 times reduction in inference costs while maintaining accuracy comparable to traditional static models, demonstrating its potential for efficient visual perception [7][22]. - The model's attention mechanism automatically focuses on discriminative regions, enhancing interpretability and aligning closely with human visual behavior [22][26]. Group 5: Broader Implications and Future Research - The findings from AdaptiveNN provide insights into cognitive science, particularly in understanding human visual behavior and the mechanisms behind visual decision-making [25]. - The architecture's application in embodied intelligence models shows significant improvements in reasoning and perception efficiency, suggesting a promising direction for future research in AI and cognitive science [29].

Group 1 - The conference is designed for both specialists and generalist investors, starting with introductory questions for those unfamiliar with Cognex [1] - Cognex is identified as a competitor in the machine vision market, which is explained for the audience [2]

Summary of Zebra Technologies FY Conference Call Company Overview - **Company**: Zebra Technologies (NasdaqGS: ZBRA) - **Event**: FY Conference Call on November 18, 2025 - **Key Speakers**: Nathan Winters (CFO), Mike Steele (VP of Finance and Investor Relations) Core Industry Insights - **Industry**: Technology and Automation Solutions for Frontline Operations - **Vision**: Transition from "Enterprise Asset Intelligence" to "Enabling Intelligent Operations" to reflect the company's evolution and current offerings [4][6] Key Points and Arguments 1. **Resegmentation of Business**: Zebra has resegmented its operations into two new segments: Connected Frontline and Asset Visibility and Automation, to better align with its current strategy and offerings [6][8] 2. **ELO Acquisition**: The $1.3 billion acquisition of ELO aims to enhance the frontline experience by integrating mobile computing with point-of-sale solutions, expected to generate $400 million in revenue and provide immediate accretive benefits [9][10] 3. **Demand Environment**: The company is experiencing uneven demand across regions, with strong performance in North America and Asia-Pacific, while Europe shows tepid demand, particularly in Germany and France [12][14] 4. **Customer Capital Planning**: Zebra maintains a two- to three-year roadmap with strategic customers, indicating a stable outlook for project deployments, although uncertainty remains regarding the timing of capital expenditures [15][16] 5. **Growth Projections**: The company anticipates a long-term compound annual growth rate (CAGR) of 5%-7%, driven by market leadership in mobile computing and expansion into new markets [25][26] 6. **RFID Technology**: Zebra sees RFID as a significant growth opportunity, with double-digit growth in recent years, emphasizing its role in inventory management and theft prevention [46][48] 7. **Machine Vision**: The integration of machine vision technologies is expected to enhance Zebra's competitive positioning, particularly in high-end inspection markets [52][53] 8. **Healthcare Market**: Adoption in healthcare is slower due to the nature of the industry, but Zebra remains optimistic about long-term growth opportunities, especially with the ELO acquisition [61][63] 9. **Omnichannel Retail**: The company has fully absorbed capacity constraints from previous years and is seeing a return to normal business levels, with ongoing discussions about technology refreshes and new applications [65][67] Additional Important Insights - **Tariff Mitigation**: Zebra has successfully reduced the expected gross profit headwinds from tariffs from $70 million to less than $25 million through proactive pricing and supply chain diversification [31][32] - **AI Integration**: The company is leveraging AI to enhance internal productivity and develop customer-facing applications, focusing on frontline worker solutions [35][39] - **Market Challenges**: Manufacturing remains subdued, with muted growth due to economic uncertainty, particularly in Europe and automotive sectors [57][59] This summary encapsulates the key insights and strategic directions discussed during the Zebra Technologies FY Conference Call, highlighting the company's focus on innovation, market adaptation, and long-term growth potential.

Core Insights - Kyocera Corporation has developed a Triple Lens AI-Based High-Resolution Depth Sensor for close imaging [1] - The new sensor utilizes three lenses and proprietary AI technology to detect semi-transparent, thin, and fine line-shaped objects [1] - This technology improves the accuracy of measuring distance and size of objects that are difficult to detect with traditional methods [1] Company Overview - Kyocera Corporation is led by President Hideo Tanimoto [1] - The company is publicly traded on the Tokyo Stock Exchange under the ticker 6971 [1] Industry Implications - The introduction of advanced imaging technology like the Triple Lens AI-Based Depth Sensor may enhance applications in various fields, including robotics, medical imaging, and manufacturing [1] - The ability to accurately measure previously hard-to-detect objects could lead to innovations in product design and quality control processes [1]