WNS (WNS) 2025 Conference June 03, 2025 04:20 PM ET Speaker0 Well, good afternoon, everyone. My name is Dave Koning. I'm a senior research analyst at Baird covering payments and services. Thrilled to introduce WNS. We have Dave Mackie here. He just said he's been at WNS for fourteen years. I've been at Baird for twenty three, so there's a lot of years involved. And WNS, a leader in business process management, recently reaccelerated really nicely getting back on track to normalize growth. And why don't I tu ...

Group 1 - The event "Guarding My World - Together 'Child' Walk" was successfully held in Dalian, China, on Children's Day, focusing on children's safety and science education [1][2] - The "One Meter Science" initiative aims to shift the perspective of science education from teaching children to empowering them to engage with science [2][6] - The event featured 30 sets of children's science comics covering various safety themes, designed from a child's perspective to facilitate learning [2][10] Group 2 - The design of the comic display area encourages parents to engage with children at their level, promoting a more equal and understanding interaction [4][6] - The event included interactive zones such as the "Fire Safety Education Interactive Zone," where children learned self-protection skills related to recent fire incidents [10][11] - The "Potato Dou Serious Science" series has gained significant recognition, with over 21 billion views and numerous accolades, becoming a popular choice for family science education [22]

Core Insights - A new wave of AI-native companies is emerging globally, defined as those that integrate AI as a core product or service from inception, driving value creation and business innovation [1] - The research focuses on three key questions regarding the technologies, applications, and structural changes brought about by AI-native enterprises [1] Group 1: Overview of Global AI-native Ecosystem - The global generative AI landscape has formed three main foundational model ecosystems centered around OpenAI, Anthropic, and Google [2] - OpenAI's ecosystem is the largest, with 81 startups and a total valuation of approximately $63.46 billion, showcasing a diverse range of applications [2] - Anthropic's ecosystem consists of 32 companies valued at around $50.11 billion, focusing on enterprise-level applications with high safety and reliability requirements [3] - Google's ecosystem is the smallest, with 18 companies valued at about $12.75 billion, but it is growing rapidly due to its technological integration and vertical innovation [3] Group 2: Multi-model Access Strategy - Many AI-native companies are adopting multi-model access strategies to leverage the strengths of different foundational models and reduce dependency on a single ecosystem [4] - Companies like Anysphere and Jasper support multiple model integrations, enhancing their competitive edge [4] - These companies typically follow a B2B2B model, focusing on sectors like data, marketing, and finance, which allows them to cater to diverse client needs [4] Group 3: Self-developed Models - A growing number of companies are focusing on developing their own models, categorized into two types: unicorns targeting general models and those specializing in vertical markets [5][6] - Companies like xAI and Cohere aim for breakthroughs in foundational models, while others like Midjourney and Stability focus on niche applications [6] Group 4: Differentiated Ecosystem Strategies - The competition in generative AI has shifted from model capabilities to ecosystem building, with OpenAI, Anthropic, and Google each pursuing distinct strategies [8] - OpenAI emphasizes platform attractiveness, Anthropic focuses on safety, and Google leverages its integrated ecosystem for comprehensive solutions [9][10][11][13] Group 5: Developer and Channel Strategies - OpenAI provides a general development platform with a plugin ecosystem, incentivizing developers to innovate [14] - Anthropic emphasizes a B2B integration strategy centered on safety, using protocols to connect its models with external systems [15] - Google offers a full-stack AI development environment, integrating its models deeply into its product ecosystem [16][19] Group 6: Pricing Strategies - OpenAI employs an API billing model with subscription options, gradually lowering prices to expand its user base [23] - Anthropic uses a flexible pricing strategy, focusing on value for high-value clients while maintaining competitive pricing [24] - Google combines low pricing with cross-subsidization strategies to rapidly expand its market share [25] Conclusion - The ecosystem barriers and user stickiness in the AI industry are still in the early stages of formation, with significant potential for change as technology evolves [26]

Core Viewpoint - The company is facing challenges in the global optical fiber and cable market due to declining demand for traditional products, but it is also identifying opportunities in new technologies and international markets [1][3][5]. Business Review - In 2024, the global demand for optical fibers and cables continued to be under pressure, with domestic production decreasing by approximately 18.2% year-on-year [1]. - The company maintained a leading delivery share in the domestic market and stabilized core business revenue despite challenges, achieving a gross margin increase from 29.70% in 2023 to 31.68% in 2024 [3][8]. - The company is focusing on new fiber technologies to meet the growing demand for high-capacity and low-latency transmission, particularly in data centers and AI infrastructure [1][4]. International Strategy - The company has significantly increased its overseas business revenue from approximately RMB 398 million in 2014 to about RMB 4.12 billion in 2024, representing 33.8% of total revenue [5]. - The company has established a presence in key international markets with eight overseas bases and over 50 offices, enhancing its ability to respond to market demands [5]. Technological Innovation - The company is committed to technological innovation and smart manufacturing, with a focus on developing advanced optical fiber technologies and new product lines [4][6]. - The company is advancing in the third-generation semiconductor sector, with plans to produce 360,000 6-inch silicon carbide wafers annually, meeting the needs of approximately 144,000 electric vehicles [6]. Financial Performance - The company's net profit for 2024 decreased by approximately 47.9% to RMB 675.9 million, with a stable operating cash flow of about RMB 1.78 billion [8]. - The company maintains a healthy financial position with a debt-to-equity ratio of 41.4% as of December 31, 2024 [8]. Future Development - The company plans to continue consolidating its leading market position and optimize its business structure by leveraging new fiber products and international opportunities [8]. - The company aims to enhance its core competitiveness through diversified business expansion and international market engagement [8].

本文节选自彭博终端"彭博行业研究《2025年生成式AI展望》"，彭博终端用户可运行{NSN SWJ7Y1DWX2PS0 }阅读。如您还不是终 端用户，您可在文末"阅读原文"联系我们预约产品演示。 彭博行业研究 2025年生成式AI展望 生成式人工智能（AI）和大语言模型（LLM）的应用已经渗透到科技领域的各个环节并迅速发 展。预计到2032年， 这个市场将创造约1.8 万亿美元的收入。 彭博行业研究认为，随着由思维链和强化学习加持的推理模型更受青睐，LLM的应用可能从基 于文本的搜索扩大至各种图片、音频和视频的分析；除了LLM赋能的合同审查和客服聊天机器 人等现有用例外，集成写作和编程助手以及利用文本和语音提示词生成图像和视频的工具，也 将推动生成式 AI智能体在消费端和企业端的部署；DeepSeek问世后，大多数LLM公司都致力 于提高模型效率，从而实现大规模推理。 核心议题： 长按或扫描二维码 阅读完整报告 推理超过训练的时间有望提前： 推理支出超过训练支出的时间可能比我们之前的预测至 少提前三年。 大语言模型之间的差距缩小： OpenAI的GPT、谷歌的Gemini、Meta的Llama、 Anthro ...

Core Viewpoint - World Labs, co-founded by Fei-Fei Li, has open-sourced a core technology called Forge, a real-time 3D Gaussian Splatting renderer that operates seamlessly across various devices, including desktops, low-power mobile devices, and XR [1][6]. Group 1: Technology Overview - Forge is a web-based 3D Gaussian Splatting renderer that integrates with three.js, enabling fully dynamic and programmable Gaussian splatting [2]. - The underlying design of Forge is optimized for GPU, serving a role similar to traditional 3D graphics components known as "shaders" [3]. - The technology allows developers to handle AI-generated 3D worlds as easily as manipulating triangle meshes, according to Ben Mildenhall, co-founder of World Labs [5]. Group 2: Features and Capabilities - Forge requires minimal code to start and run, supporting multiple splat objects, cameras, and real-time animations/edits [4]. - It is designed as a programmable 3D Gaussian Splatting engine, providing unprecedented control over the generation, animation, and rendering of 3D Gaussian splats [8]. - The renderer employs a painter's algorithm for sorting splats, which is a core aspect of its design [13]. Group 3: Rendering Process - The key component managing the rendering process is ForgeRenderer, which compiles a complete list of splats in a three.js scene and determines the drawing order using an efficient bucket sort algorithm [14]. - Forge supports multi-view rendering by generating additional ForgeViewpoint objects, allowing for simultaneous rendering from different perspectives [15]. Group 4: Future Plans - World Labs aims to elevate multimodal AI from 2D pixel planes to full 3D worlds, with plans to launch its first product in 2025 [17]. - The company intends to develop tools beneficial for professionals such as artists, designers, developers, filmmakers, and engineers, targeting a wide range of customers from video game developers to film studios [17].

Core Viewpoint - The integration of generative artificial intelligence in the construction of the "Big Ideological and Political Course" is essential for enhancing educational quality and addressing contemporary challenges in education [1][2][3][4][5][6] Group 1: Emphasis on People-Centric Education - The focus on "people first" is crucial for innovation in education, aiming to cultivate digital youth capable of national rejuvenation in the context of AI 2.0 [1] - The combination of the "Big Ideological and Political Course" with generative AI can enhance the value of ideological education, guiding students to navigate the challenges posed by AI advancements [1] Group 2: Building a Value-Driven Platform - The rise of generative AI provides new avenues for disseminating various ideologies, necessitating a strong grasp of ideological teaching authority [2] - Emphasizing mainstream ideology and utilizing generative AI to transform teaching methods can effectively counter Western erroneous thoughts [2] Group 3: Enhancing Teacher Competence - The construction of the "Big Ideological and Political Course" requires an urgent upgrade in teachers' digital literacy to meet the demands of AI 2.0 [3] - Teachers must balance traditional educational values with innovative teaching methods, enhancing their digital competencies across various teaching dimensions [3] Group 4: Problem-Oriented Resource Allocation - A problem-oriented approach is essential for leveraging generative AI to address students' concerns and improve the effectiveness of ideological education [4][5] - The focus should be on creating targeted educational resources that align with students' needs and expectations [5] Group 5: Systematic Collaboration - A systematic perspective is necessary to integrate generative AI into the "Big Ideological and Political Course," promoting interdisciplinary collaboration [5][6] - The use of AI can facilitate the connection between classroom learning and real-world applications, enhancing the overall educational experience [5] Group 6: Global Perspective - The global application of generative AI in education highlights the need for a broader perspective in constructing the "Big Ideological and Political Course" [6] - Emphasizing the importance of telling China's story and promoting its values on the international stage can enhance cultural exchange and understanding [6]

此次分享会旨在帮助 古蔺县机关党建 工作人员深入了解人工智能技术在办公领域的应用，提升工作效率，推动区域数字化转型。 张孜铭老师作为 人工智能领域的资深专家 ，拥有丰富的学术背景和实践经验。他不仅是北京大学管理学硕士、新加坡国立大学金融工程 硕士，还担任《AIGC：智能创作时代》一书的作者，参与了多项国家级人工智能标准的起草工作。 在分享会上，张老师深入浅出地介绍了 人工智能的发展历程、技术原理以及在不同行业的应用案例 ，让在场的政府工作人员对AI有了更 全面、更深刻的认识。 在分享过程中，张老师着重讲解了 AI在办公场景中的应用 。他指出，随着人工智能技术的不断进步，AI工具已经能够帮助人们高效完成 文本生成、数据处理、图像设计等任务。 近日， 未可知人工智能研究院副院长张孜铭老师受邀前往上海交通大学四川研究院 ，为古蔺县"党建赋能 服务百强县"机关党建工作培 训班开展了一场以"DeepSeek实践工作坊：生成式人工智能本地化部署及AI agent创建 "为主题的分享会。 例如，通过AI生成PPT，可以在短时间内快速生成高质量的演示文稿，大大节省了制作时间；利用AI处理Excel数据，能够快速进行数据 分析 ...

Core Insights - Abridge AI Inc. is raising $300 million in a new funding round led by Andreessen Horowitz, bringing its valuation to $5.3 billion, nearly doubling from $2.75 billion earlier this year [2][5] - The company focuses on using AI to transcribe medical conversations, addressing inefficiencies in healthcare documentation and reducing administrative burdens on physicians [5][7] - Abridge has raised over $400 million in total venture capital, with significant interest from investors in AI applications that enhance professional productivity [5][11] Company Overview - Founded in 2018, Abridge faced initial challenges but gained traction following advancements in generative AI, particularly with the emergence of tools like ChatGPT [5][8] - The CEO, Shiv Rao, a former cardiologist, emphasizes the importance of reducing the time doctors spend on documentation, which can be as much as two hours daily [7][12] - Abridge's early investors include notable firms such as IVP, Elad Gil, Spark Capital, Bessemer Venture Partners, and Union Square Ventures [6] Market Dynamics - Despite a cautious approach to AI adoption in many sectors, large healthcare systems are rapidly signing contracts with Abridge, indicating a shift in procurement behavior [12] - The company has announced new healthcare system clients almost weekly since early 2024, showcasing a significant acceleration in demand [12][15] - Hospitals have praised Abridge's software as transformative, with executives describing it as "life-changing" and a major paradigm shift in their profession [15]

Core Insights - Meta has restructured its AI teams into two main groups: an AI product team led by Connor Hayes and an AGI Foundations team co-led by Ahmad Al-Dahle and Amir Frenkel, aiming to enhance product development speed and flexibility [2][3] - The restructuring is a response to increasing competition in the AI space from companies like OpenAI and Google, as Meta seeks to maintain its relevance in the rapidly evolving landscape [3][4] - Despite the restructuring, Meta faces significant challenges, including a talent exodus from its foundational AI research team, FAIR, which has seen 11 out of 14 core members leave [4][8] Team Structure and Focus - The AI product team will focus on consumer-facing applications across platforms like Facebook, Instagram, and WhatsApp, while the AGI Foundations team will work on broader technologies, including improvements to the Llama model [2][3] - FAIR remains independent but has lost key personnel, raising concerns about its future role within Meta's AI strategy [3][4] Talent and Competition - The departure of key researchers from FAIR has led to the emergence of competitors like Mistral, founded by former Meta researchers, which poses a direct challenge to Meta's AI initiatives [8][9] - Meta's recent AI model, Llama 4, has not received a warm reception, leading developers to explore faster-growing alternatives from competitors [9][11] Internal Dynamics and Leadership Changes - Joelle Pineau, who led FAIR for eight years, recently resigned, and her departure has highlighted internal concerns regarding Meta's AI leadership and performance [9][11] - The integration of FAIR into product-focused teams has diminished its role in exploratory research, leading to a shift in priorities towards generating AI-driven products rather than foundational research [18][19] Financial Commitment and Future Outlook - Meta plans to invest approximately $65 billion in AI projects by 2025, indicating a strong commitment to regaining leadership in the AI sector [24] - Despite significant investments, Meta lacks a dedicated reasoning model, which is becoming increasingly important as competitors prioritize such capabilities [27]