Financial Data and Key Metrics Changes - Ares Management achieved a record $994 million in management fees for Q4 2025, totaling $3.7 billion for the full year, reflecting a 27% and 25% year-over-year growth respectively [30] - Fee-related earnings (FRE) for the full year increased by 30%, with a record $528 million in Q4, and FRE margins improved to 41.7% [32] - Realized income for Q4 reached a record $589 million, exceeding $1.8 billion for the full year, marking a 26% increase from 2024 [34] Business Line Data and Key Metrics Changes - The wealth management business saw AUM grow to over $66 billion, a 69% increase year-over-year, driven by strong performance across various strategies [9] - The real estate group raised more than $16 billion for the year, including over $7 billion in Q4, with significant commitments in various funds [19] - The secondaries group raised $12.9 billion for the full year, with AUM increasing by 45%, nearly doubling in size since the acquisition of Landmark [23] Market Data and Key Metrics Changes - Ares Management's total AUM reached over $622 billion, a 29% increase year-over-year, with significant fundraising activities contributing to this growth [7] - The company reported a record $36 billion in fundraising for Q4, contributing to a total of $113 billion for the year [6] - Deployment across real assets more than doubled from approximately $10 billion in 2024 to over $23 billion in 2025 [11] Company Strategy and Development Direction - Ares Management is focused on expanding its investment platform and geographic reach, with strategic enhancements including new products and operational efficiencies [9] - The acquisition of GCP has positioned Ares as a top three global owner and operator of industrial real estate, enhancing its real estate and digital infrastructure offerings [9] - The company aims to leverage its diversified product suite to capture growth opportunities across various asset classes and geographies [14] Management's Comments on Operating Environment and Future Outlook - Management expressed optimism about the improving transaction environment and pent-up demand for private equity sponsors seeking liquidity solutions [12] - The company anticipates strong demand for its investment strategies in 2026, supported by a substantial dry powder of $156 billion [29] - Management highlighted the resilience of its credit portfolios, with strong fundamentals and improving metrics across various strategies [46] Other Important Information - Ares Management plans to launch its fourth U.S. Senior Direct Lending Fund later in 2026 and its seventh European Direct Lending Fund in early 2027 [18] - The company has initiated over 25 AI projects aimed at enhancing investment decision-making and operational efficiency [9] - Ares has been added to the S&P 500 Index, reflecting its growth and market position [9] Q&A Session Summary Question: Impact of software AI disruption on deployment efforts - Management expressed confidence in their software investments, emphasizing the differentiation between various software companies and their resilience against disruption [49][51] Question: Wealth channel performance and sentiment - Management noted strong flows in January and February, with broad-based demand across private credit and core infrastructure products, indicating a positive sentiment despite market volatility [56][62] Question: Outlook for fundraising and deployment in real assets and secondaries - Management confirmed plans for significant fundraising in their flagship credit vehicles, with expectations for strong deployment opportunities in real estate and secondaries [68][70]

Financial Data and Key Metrics Changes - Revenue for Q3 2025 increased by 7% year-over-year, reaching $1.291 billion, exceeding guidance by $21 million [4][16] - Gross margin improved to 36.4%, and adjusted operating income margin rose to 17.7%, reflecting healthy margin expansion [4][19] - Adjusted diluted EPS grew 14% year-over-year to $0.97, surpassing the high end of guidance by $0.07 [4][19] Business Line Data and Key Metrics Changes - Advanced technology solutions revenue surged 20% year-over-year to $311 million, now accounting for 24% of total revenue [17] - Core business services revenue grew 3% year-over-year to $980 million, driven by digital operations and technology services [17] - Data tech and AI revenue increased by 9.3% year-over-year to $622 million, while digital operations revenue rose by 4.3% to $669 million [17] Market Data and Key Metrics Changes - Revenue growth was strongest in high-tech and manufacturing at 14%, followed by financial services at 3%, and consumer and healthcare at 1% [18] - Non-FTE revenue accounted for 47% of total revenue, benefiting from advanced technology solutions [18] Company Strategy and Development Direction - The company is focused on establishing itself as a global leader in advanced technology solutions through its Genpact Next framework [5][24] - Investments in partnerships and AI talent are accelerating growth, with partner-related revenue increasing by 56% year-over-year [13] - The company aims to sharpen its go-to-market focus in decision support services to enhance execution and market share [9] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in the strong demand signals across various client segments and the overall environment [26][28] - The company raised its full-year revenue guidance to a range of 6.1%-6.4% and adjusted diluted EPS to between $3.60 and $3.61, reflecting double-digit growth [15][23] - Management highlighted the importance of building trust with clients as they transition to agentic operations, emphasizing the need for process intelligence alongside AI [40] Other Important Information - The company returned $119 million to shareholders through share repurchases and dividends, representing 59% of free cash flow year-to-date [20] - The company is committed to returning at least 50% of cash flow to investors while maintaining flexibility for strategic investments [23] Q&A Session Summary Question: Can you comment on the bookings performance in Q3? - Management noted strong demand signals across new and existing clients, with five large deals closed in the quarter [26][27] Question: What are the primary reasons clients are not ready to launch agentic operations? - Clients often face issues with data readiness and process standardization, which are critical for implementing advanced technology solutions [31][32] Question: How is the competitive landscape evolving? - The company differentiates itself through last-mile expertise and a strong culture of client centricity and innovation [34][35] Question: Why is a significant portion of agentic work coming from new clients? - New clients are increasingly adopting agentic solutions, while existing clients are also absorbing these solutions, indicating a growing total addressable market [36][37] Question: How are contracts structured for agentic AI solutions? - The company is shifting towards non-FTE models and subscription-based structures for its software solutions [41][42]

Group 1 - The core viewpoint is that the next decade is likely to belong to artificial intelligence (AI), with the global AI market expected to reach nearly $400 billion by 2025 and surpass $1.8 trillion by 2030, reflecting a compound annual growth rate (CAGR) of 37.3% [2][6] - AI's rapid adoption is reshaping both consumer experiences and industrial structures, making it a key area for investment that can potentially navigate economic cycles [2][6] - The article introduces a series titled "Riding the AI Wave, Breaking the Cycle," aimed at providing a systematic perspective on policy trends, trading logic, valuation frameworks, and application implementation [2] Group 2 - The global AI market reached $196.6 billion in 2023 and is projected to grow to $1.81 trillion by 2030, representing a ninefold increase from 2023, driven by advancements in multimodal large models and embodied intelligence [6] - The growth of the AI industry is characterized by the collaborative expansion of hardware, software, and services [7] Group 3 - Hardware is expected to grow at a CAGR of 24.6%, driven by demand for AI chips and data centers, although profit margins may decline due to increased competition [10] - Software is projected to grow at a CAGR of 33.6%, fueled by the lowering of AI development barriers and the rise of generative AI, which has significantly increased demand for large language models and development platforms [11] - The services sector is anticipated to grow at a CAGR of 48.7%, as it plays a crucial role in bridging the gap between AI technology and its practical application in businesses [12] Group 4 - The future of AI will see a shift towards service providers that can offer end-to-end AI solutions, particularly those with deep vertical industry knowledge [13] - Deep learning is expected to grow at a CAGR of 33.5%, driven by architectural innovations and the increasing availability of computational power [16] - Natural language processing (NLP) is experiencing the fastest growth at a CAGR of 48.7%, thanks to breakthroughs in large models and their applications [18] Group 5 - Mergers and acquisitions (M&A) in the AI sector are on the rise, driven by companies seeking to enhance specific capabilities and the interest of private equity and venture capital in AI's long-term growth potential [24] - The increase in M&A activity is attributed to factors such as the need for large-scale language models, the competitive landscape for data and computational resources, and the tightening of global regulations [25][29] Group 6 - Software and related services companies are the most sought-after M&A targets due to their central role in the AI value chain, offering direct delivery of AI capabilities [30] - The future of AI M&A is expected to evolve from a focus on acquiring technology and teams to a more integrated approach that emphasizes ecosystem building [31] Group 7 - The global AI market is transitioning from a trial phase to a commercialization phase, with growth opportunities emerging in infrastructure upgrades, industry empowerment, and innovative applications [33] - AI is moving towards industry-specific solutions, with significant advancements expected in sectors such as healthcare, manufacturing, and finance [35] - Generative AI is transforming human-computer interaction, leading to new business models and applications [36] Group 8 - The Chinese market is becoming a central battleground for AI transformation, supported by policy, talent, and industrial advantages [38] - The narrative of AI is evolving, focusing on reconstructing an intelligent world rather than merely replicating the internet [39]

Summary of Key Points from Conference Call Records Industry Overview - The AI industry chain and AIDC sector are significant drivers in the technology sector, with overseas cloud vendors' capital expenditures exceeding expectations, leading to growth in sub-sectors like optical modules, PCBs, and liquid cooling [1][2][3] - North American cloud vendors such as AWS, GCP, and Microsoft are increasing capital expenditures, with AWS expected to reach $118 billion in annual capital spending, a 20% year-on-year increase [1][13] - The A-share market is optimistic, driven by China's economic transformation and capital market reforms, with significant growth in the technology sector [2][6] Key Insights and Arguments - The introduction of ISIC chips is reshaping the supply chain landscape, providing more opportunities for domestic suppliers, particularly in liquid cooling and power supply sectors [1][7] - The demand for 800G optical modules is projected to exceed 20 million units in 2025 and potentially reach over 40 million in 2026, benefiting companies like ZTE and NewEase [2][19] - The AI server market is experiencing rapid growth, with China's market size surpassing $56 billion, accounting for nearly 40% of the global market [2][26] Investment Opportunities - The AIDC industry has seen a surge in computing power demand, with ByteDance's daily computing power usage expected to rise significantly, leading to increased capital expenditure in various equipment [4][10] - Companies like Shengke Communication are positioned to benefit from the expansion of AI clusters, with potential market increments of 15 billion RMB by 2027 [1][18] - Liquid cooling technology is gaining traction in the automotive parts sector, with companies like Zhongding actively entering the server liquid cooling market [2][23] Emerging Trends - The communication industry is expected to grow rapidly, with significant demand for optical modules and network devices, driven by the increasing interconnectivity of machines [19][20] - The diesel engine market is facing tight supply and demand, with existing companies like Cummins and MTU seeing substantial performance improvements [2][22] - The AI application landscape is evolving, with a notable increase in daily token consumption, driving demand for underlying computing power [25][28] Additional Important Insights - The liquid cooling market is expanding into civilian applications, with companies like AVIC Optoelectronics leveraging military experience to enter sectors like data communication and renewable energy [30] - The quartz fiber material market is dominated by companies like Feilihua, which has a strong position due to its military background and technological advancements [32][34] - The overall market is expected to remain active, with quality assets in technology, new consumption, and innovative pharmaceuticals likely to attract incremental capital [6][10]

Financial Data and Key Metrics Changes - The company reported strong portfolio performance with positive NOI and EBITDA growth, indicating resilience in its financials [3][4] - The alternative credit business is valued at $40 billion, reflecting a robust position in the market [3] Business Line Data and Key Metrics Changes - Direct lending portfolios maintain a loan-to-value ratio of 42%, suggesting a strong backing by institutional equity [7][30] - The company has seen a 61% increase in deployment despite a 7% decline in US M&A volumes, showcasing effective management of capital [25][26] Market Data and Key Metrics Changes - Credit spreads have widened by 50 to 75 basis points post-Liberation Day, but the total return in direct lending remains attractive at around 10% [18][21] - The secondary market for private equity is experiencing significant growth, with an estimated $160 billion in secondary deployment last year, indicating a healthy demand for liquidity solutions [62] Company Strategy and Development Direction - The acquisition of GCP enhances the company's position in industrial real estate and digital infrastructure, aligning with its strategic roadmap for growth in Asia and data centers [57][58] - The company aims to double its asset-based finance business to $75-80 billion, focusing on sub-investment grade and investment grade opportunities [36][38] Management's Comments on Operating Environment and Future Outlook - Management expresses cautious optimism about the economy, noting strong fundamentals despite concerns over inflation and economic growth [4][5] - The company maintains its five-year fee-related earnings growth guidance of 16% to 20%, reflecting confidence in its business model and market position [85][86] Other Important Information - The company emphasizes the importance of maintaining a balance between retail and institutional fundraising to ensure sustainable growth and performance [78][79] - Management highlights the educational efforts made to improve investor understanding of asset-based finance, which is crucial for market expansion [42][44] Q&A Session Summary Question: What are the biggest risks to the private credit market? - Management believes that private credit is one of the last places to see losses due to the high quality of borrowers and the structure of the market [8][9] Question: How is the integration of the GCP acquisition progressing? - The acquisition is on track to enhance the company's capabilities in industrial real estate and data centers, with significant growth potential identified [57][58] Question: How does the company manage the conflict between retail and institutional flows? - The company focuses on building investment capacity to ensure that it can meet the demands of both retail and institutional investors without compromising performance [78][79]

Core Viewpoint - The ultimate goal of AI is not just to assist in coding but to gain control over the entire software lifecycle, from conception to deployment and ongoing maintenance [6][54]. Group 1: AI's Impact on Coding - The critical point where AI will replace human coding is expected to arrive within the next 1-2 years [7]. - AI's capabilities should extend beyond coding to encompass the entire software lifecycle, including building, deploying, and maintaining systems [7][10]. - Current backend systems are designed with the assumption of human programmer involvement, making them unsuitable for AI use [7][12]. Group 2: Evolution of AI-Native Infrastructure - An evolutionary model (L0-L5) is proposed to describe the progression of AI infrastructure [7][14]. - The future software paradigm will trend towards "Result-as-a-Service," where human roles shift from engineers to quality assurance, while AI handles generation and maintenance [7][54]. - AI is transitioning from being a tool user to becoming a system leader, indicating a significant shift in its role within software development [18][54]. Group 3: Challenges in Current Systems - Existing backend tools are fundamentally designed for human interaction, which limits AI's operational efficiency [12][13]. - Current systems often present ambiguous error messages that are not machine-readable, creating barriers for AI [12][13]. - The lack of standardized error codes and automated recovery mechanisms in traditional systems hinders AI's ability to function autonomously [12][13]. Group 4: Stages of AI Capability Development - The L0 stage represents AI being constrained by traditional infrastructure, functioning like an intern mimicking human actions [18][20]. - The L1 stage allows AI to perform actions through standardized interfaces but lacks a comprehensive understanding of system architecture [21][22]. - The L2 stage enables AI to assemble systems by understanding module relationships, marking a shift from task execution to system assembly [27][30]. Group 5: Future Infrastructure Requirements - To achieve true AI-Native infrastructure, systems must be designed to eliminate human-centric assumptions and allow AI to operate independently [14][57]. - The infrastructure must provide a complete system view, enabling AI to query and manage all components effectively [31][45]. - AI must have the autonomy to design and manage the entire infrastructure, transitioning from a service manager to a system architect [39][45].

以下文章来源于晚点对话 ，作者程曼祺 晚点对话 . 最一手的商业访谈，最真实的企业家思考。 阿里云 CTO、通义实验室负责人 周靖人 "大模型已经从早期阶段的初期，进入早期阶段的中期，不可能只在单点能力上改进了。" Qwen3 旗舰模型，MoE（混合专家模型）模型 Qwen3-235B-A22B，以 2350 亿总参数、220 亿激活参数，在 多项主要 Benchmark（测评指标）上超越了 6710 亿总参数、370 亿激活参数的 DeepSeek-R1 满血版。更小 的 MoE 模型 Qwen3-30B-A3B，使用时的激活参数仅为 30 亿，不到之前 Qwen 系列纯推理稠密模型 QwQ- 32B 的 1/10，但效果更优。更小参数、更好性能，意味着开发者可以用更低部署和使用成本，得到更好效 果。图片来自通义千问官方博客。 （注：MoE 模型每次使用时只会激活部分参数，使用效率更高，所以有 总参数、激活参数两个参数指标。） Qwen3 发布前，我们访谈了阿里大模型研发一号位，阿里云 CTO 和通义实验室负责人，周靖人。他 也是阿里开源大模型的主要决策者。 迄今为止，Qwen 系列大模型已被累计下载 3 ...