UiPath (NYSE:PATH) FY Conference January 13, 2026 11:00 AM ET Company ParticipantsAshim Gupta - CFO and COOConference Call ParticipantsScott Berg - Senior AnalystScott BergYes, we are goin g to get started. So wonderful. Hey, Alex, before you come up, can you grab the door for me? Thanks. I'd like a coffee with two sugars too. Totally kidding. Totally kidding. I don't drink coffee, so. Awesome. Thanks, everyone, for joining us today. My name is Scott Berg. I lead the enterprise software and SaaS research ef ...

Summary of CES 2026 Keynote Address by AMD CEO Dr. Lisa Su Industry Overview - The keynote was part of CES 2026, a major technology event showcasing innovations across various sectors, particularly focusing on AI and high-performance computing [1][4][5] - AMD is positioned as a central player in the global AI transformation, emphasizing its role in high-performance and AI computing [5][6] Core Points and Arguments AI and Computing Demand - AI is described as the most important technology of the last 50 years, with AMD prioritizing its development [15][16] - The number of active AI users has surged from 1 million to over 1 billion, with projections of reaching over 5 billion users [16][17] - Global compute infrastructure demand is expected to grow from approximately 1 Zettaflop in 2022 to over 100 Zettaflops by 2025, necessitating a further increase to over 10 Yottaflops in the next five years [17][19] - AI's integration into various sectors, including healthcare, education, and productivity, is highlighted as transformative [15][16] AMD's Technological Innovations - AMD's Helios platform is introduced as a next-generation rack scale solution designed for AI, featuring advanced MI455 GPUs and EPYC CPUs [23][30] - The MI455 GPU boasts 320 billion transistors and is designed for high performance, delivering up to 10 times more performance compared to previous generations [27][30] - The Helios rack is designed for optimal serviceability and reliability, weighing nearly 7,000 pounds and integrating cutting-edge technologies [24][25][26] Partnerships and Collaborations - AMD's collaboration with OpenAI is emphasized, showcasing the need for increased compute capacity to support advanced AI models [31][39] - Luma AI's CEO, Amit Jain, discusses their partnership with AMD, highlighting the efficiency and performance improvements achieved through AMD's hardware [50][59] Future Outlook - The demand for compute is expected to continue growing, with AMD's next-gen MI500 series already in development, promising a 1,000x increase in AI performance over four years [63][64] - The Ryzen AI 400 Series is introduced as the most advanced family of AI PC processors, set to enhance productivity and content creation capabilities [67][68] Additional Important Content - The keynote emphasizes the collaborative nature of innovation, stating that AI is not a solo act but a shared pursuit among industry leaders [2][4] - The importance of an open ecosystem for AI development is stressed, with AMD advocating for shared technology standards across hardware and software [48][49] - The potential of AI in personal computing is highlighted, with AI PCs becoming essential partners in productivity and creativity [65][66] This summary encapsulates the key themes and innovations presented during the CES 2026 keynote by AMD's CEO, focusing on the transformative impact of AI and the company's strategic advancements in computing technology.

-These companies investing trillions of dollars in CapEx. -Trillions of dollars in the race to build artificial intelligence support systems. -Trillions of dollars of our tech companies investing in building data centers in America. Westin: How far AI will take us and how fast may depend in part on a basic choice about the overall approach to sharing or withholding information, a choice often mentioned in passing, but one that investors may not have identified as key. -I want to see AI everywhere. You know, ...

Core Insights - Workday has launched a global developer network aimed at enhancing AI talent through access to tools, training, and certification [1][2] - Google Cloud has joined Workday Data Cloud, providing customers with secure, zero-copy access to HR and finance data for AI-driven insights [1][6] Developer Network and Training - The global developer network will allow a wider community to develop, certify, and apply Workday skills, facilitating hands-on experience in building AI-powered solutions [2][3] - Partnerships with universities and staffing firms will provide dedicated training paths and certifications, preparing learners for roles in the Workday Economy [3][4] Certification and Talent Connection - Developers completing the program will receive a Workday Pro Developer Certification and be listed in the Workday Talent Directory, connecting them with potential employers [4][5] Google BigQuery Partnership - The integration of Google BigQuery with Workday Data Cloud enhances customer flexibility in analyzing and activating Workday data [5][7] - Customers will benefit from direct access to Workday HR and finance data within Google Cloud, enabling predictive modeling without complex integrations [6][8] Planned Acquisition of Pipedream - Workday's planned acquisition of Pipedream aims to expand its open ecosystem, providing an integration platform for AI agents with over 3,000 pre-built connectors [9][10] - This acquisition, along with others, will enhance the ability to connect Workday data with external systems, fostering innovation across the platform [10][11] Availability Timeline - The global developer network is set to launch in early 2026, with the Workday Data Cloud available to early adopters in the first half of 2026 [12]

Core Insights - Broadcom is advancing an open ecosystem for VMware Cloud Foundation (VCF), enabling customers to build and extend modern private clouds with increased flexibility and adaptability across infrastructure layers [1][2] - The new VCF AI ReadyNodes and expanded ODM self-certification program aim to enhance participation from OEMs and ODMs, facilitating the adoption of next-generation technologies [2][4] Open Hardware Ecosystem - Broadcom is expanding its open hardware certification program to include VCF AI ReadyNodes, allowing for self-certification by ODM partners, which will enhance sourcing flexibility and reduce total cost of ownership [2][4] - Supermicro and OVHcloud are among the first to certify their systems as VCF AI ReadyNodes, which will streamline the migration to optimized GPU solutions for AI adoption [3][4] Edge Ecosystem Expansion - Broadcom is introducing new edge-optimized nodes for various applications, supporting the deployment of private cloud infrastructure closer to data generation points [4][5] Networking Strategy - A new strategy to unify network fabrics using standards-based EVPN and BGP networking will simplify operations in modern private clouds, enhancing interoperability and promoting cloud-like simplicity [6][7] - Collaboration with Cisco on the Nexus One fabric solution will provide customers with architectural flexibility and lower total cost of ownership [7][8] Open Source Contributions - Broadcom is a leading contributor to the Kubernetes community and has announced that VMware vSphere Kubernetes Service is now a Certified Kubernetes AI Conformant Platform, reinforcing its commitment to open standards [9][10]

Core Viewpoint - The partnership between Lyft and Waymo marks a significant trend in the industry, focusing on the integration of autonomous driving technology with ride-hailing services, aiming to enhance operational efficiency and reduce costs [2][4]. Group 1: New Model Implications - Lyft's Flexdrive subsidiary will manage all aspects of vehicle operations, including energy supply, maintenance, and scheduling, to maximize the efficiency of Waymo's autonomous vehicles while minimizing operational costs [3]. - Initially, passengers will use the Waymo app to request rides, but as the partnership develops, these autonomous vehicles will seamlessly integrate with the Lyft platform, creating a more efficient ride-hailing network [4]. Group 2: Operational Efficiency and Cost Reduction - Lyft's user data will help optimize routes for Waymo's vehicles, avoiding congested areas and improving travel efficiency, while Waymo will collect road data to enhance its technology [6]. - The collaboration is expected to increase the average daily operational hours of Waymo vehicles from 12 to 18 hours, with a projected 40% increase in daily service orders per vehicle [6]. - The unit cost per mile is anticipated to decrease by 35%, facilitating the broader adoption of autonomous vehicles in more cities [7]. Group 3: Competitive Landscape Transformation - The partnership signifies a shift from a "self-research and self-build" model to an open ecosystem, allowing companies to leverage each other's strengths and reduce resource waste [8][9]. - This collaboration is expected to accelerate the commercialization timeline of autonomous driving by 2-3 years, with overall R&D costs potentially decreasing by 40% [10]. Group 4: Future Trends and Industry Impact - The alliance embodies the "Mobility as a Service" (MaaS) concept, integrating technology and application layers to reshape the interaction between people, vehicles, and urban infrastructure [11]. - The partnership is set to drive the industry towards a new era of "unmanned mobility and intelligent services," creating a new growth blueprint for the global transportation sector [11].

Core Viewpoint - The domestic AI chip industry is experiencing significant growth driven by strong demand for AI inference, with leading companies accumulating inventory and securing key materials to prepare for future market developments [2][3]. Financial Performance - Haiguang Information achieved a revenue of 5.464 billion yuan in the first half of the year, a year-on-year increase of 45.21%, with a net profit of 1.201 billion yuan, up 40.78% [3]. - Cambrian's revenue surged to 2.881 billion yuan, marking a staggering year-on-year growth of 4347.82%, with a net profit of 1.038 billion yuan, compared to a loss of 530 million yuan in the previous year [3]. - Longxin Zhongke reported a revenue of 244 million yuan, a 10.9% increase year-on-year, but still faced a net loss of 294 million yuan, which is a 23.53% decline compared to the previous year [3]. Inventory and Contract Liabilities - Cambrian's inventory reached 2.69 billion yuan, accounting for 31.95% of total assets, with a 51.64% increase from the previous year [5]. - Cambrian's contract liabilities grew to 543 million yuan, representing 6.45% of total assets, a dramatic increase of 61223.22% year-on-year [5]. - Haiguang Information's contract liabilities rose by 242.1% to 3.091 billion yuan, making up 9.57% of total assets, driven by customer prepayments [5]. Market Dynamics - Domestic AI chip manufacturers are actively increasing inventory as part of strategic development considerations, with a focus on key raw materials like HBM and wafers [6][7]. - The domestic AI chip market is characterized by diverse technology routes, with companies like Haiguang Information and Cambrian competing in the GPU space, while others like Huawei HiSilicon and Cambrian focus on ASIC custom chips [7][8]. Commercialization Progress - Domestic AI chip companies have made notable strides in commercialization, with Huawei HiSilicon holding approximately 23% market share in the AI acceleration chip market in China [8]. - Cambrian's products are being deployed in key industries such as telecommunications, finance, and the internet, while Haiguang's CPU and DCU series are widely applicable in big data processing and AI [8][9]. Ecosystem Development - The development of a collaborative and open ecosystem is crucial for the sustained growth of the domestic AI chip industry, with companies like Haiguang Information emphasizing the need for deep collaboration across the supply chain [11][12]. - Increased marketing expenditures by Haiguang Information, which rose by 185.83% to 203.4 million yuan, reflect efforts to expand market presence and enhance ecosystem development [12].

Summary of Key Points from the Conference Call Company and Industry Overview - The conference primarily focuses on AMD (Advanced Micro Devices) and its advancements in AI technology and computing infrastructure, particularly in the context of data centers and high-performance computing [2][18][106]. Core Insights and Arguments 1. **AI Market Growth**: AMD anticipates the data center AI accelerator Total Addressable Market (TAM) to exceed $500 billion by 2028, with inference expected to grow over 80% annually, becoming the largest driver of AI compute [8][9][10]. 2. **Product Launches**: AMD introduced the MI 350 series, claiming a 4x generational leap in AI compute performance, with the MI 355 model supporting up to 520 billion parameters on a single GPU [42][45][46]. 3. **Performance Metrics**: The MI 355 series reportedly delivers 35x higher throughput for real-time applications and up to 4.2x higher performance for various AI applications compared to previous generations [47][48]. 4. **Strategic Partnerships**: AMD has established strong collaborations with major companies like Meta and Oracle, focusing on optimizing AI workloads and enhancing performance through integrated solutions [20][57][90]. 5. **Open Ecosystem Commitment**: AMD emphasizes the importance of an open ecosystem for AI development, highlighting its commitment to supporting open standards and frameworks to foster innovation [15][16][32]. Additional Important Content 1. **Customer Engagement**: AMD has seen significant adoption of its MI 300 and MI 355 products among top AI companies, with seven of the top ten model builders utilizing AMD's technology [20][19]. 2. **Sovereign Computing Initiatives**: AMD is actively engaging with governments and research institutions globally to build high-performance computing infrastructure, focusing on open standards and flexible architectures [106][107]. 3. **Acquisitions and Investments**: AMD has made strategic acquisitions to enhance its capabilities in AI and computing, including the acquisition of ZT and investments in various AI startups [17][18]. 4. **Future Outlook**: AMD is already in development for the MI 400 series, expected to launch in 2026, indicating a continuous commitment to innovation in AI computing [43]. This summary encapsulates the key points discussed during the conference, highlighting AMD's strategic direction, product advancements, and market positioning within the AI and computing landscape.