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为什么 AI Agents 按结果定价这么难?
Founder Park· 2025-08-08 12:22
Core Viewpoint - The concept of performance-based pricing for AI Agents is currently unattainable due to the lack of necessary technological, organizational, and cultural infrastructure [10][11][12]. Group 1: Attribution Challenges - Attribution of success in AI projects is complex, as multiple variables and human collaboration make it difficult to determine who deserves credit for outcomes [16]. - Establishing an attribution system requires advanced capabilities, including autonomous coding by AI Agents and well-defined product requirements [17][18]. - Tracking the value created by AI over time poses significant challenges, as existing infrastructure is inadequate for maintaining causal links [19]. Group 2: Measurement Feasibility - Even if attribution issues are resolved, measuring outcomes remains fundamentally challenging due to time delays in realizing benefits [20]. - Many valuable outcomes are subjective and difficult to quantify, leading to a focus on easily measurable but less significant results [21]. - Introducing performance-based pricing can alter team behavior, potentially leading to dysfunction similar to issues seen with KPIs and OKRs [22]. Group 3: Trust Deficit - Performance-based pricing necessitates unprecedented trust between suppliers and users, requiring transparency in sensitive business metrics [23]. - Suppliers need access to client systems for verification of claimed outcomes, raising significant security and privacy concerns [24]. - Disputes over outcomes and attribution lack a legal framework for resolution, complicating the implementation of performance-based agreements [25]. Group 4: Organizational Resistance - Most organizations are structurally unprepared for performance-based pricing due to procurement resistance and existing accounting practices [28][29]. - Financial teams may resist paying more for suppliers who create additional value, reflecting a zero-sum mindset deeply embedded in corporate culture [29]. Group 5: Market Structure Issues - The current AI market structure, dominated by a few suppliers, makes personalized performance agreements impractical [30]. - Standardizing outcome-based pricing across various use cases and industries is unfeasible, leading suppliers to default to usage-based pricing [32]. Group 6: Path Forward - A mixed pricing model that gradually incorporates performance elements is seen as a more realistic approach, despite its inherent complexities [36]. - Initial steps include starting with measurable agent metrics and building trust through data transparency [37][38]. - Over time, the proportion of performance-based pricing could increase as attribution systems mature, but this transition will require significant effort and investment [39]. Group 7: Key Insights - The vision for performance-based pricing in AI is valid, as it aligns incentives and fosters genuine value creation, but the path to realization is longer and more complex than anticipated [41].
PROS (PRO) Q2 EPS Jumps 86 Revenue Up 8%
The Motley Fool· 2025-08-01 21:54
Core Insights - PROS Holdings reported Q2 2025 results that exceeded Wall Street estimates for both revenue and earnings, with GAAP revenue of $88.7 million and non-GAAP EPS of $0.13, significantly higher than the consensus forecast of $0.06 [1][2] Financial Performance - GAAP revenue increased by 8.2% year-over-year from $82.0 million in Q2 2024 to $88.7 million in Q2 2025 [2] - Non-GAAP EPS rose by 85.7% from $0.07 in Q2 2024 to $0.13 in Q2 2025 [2] - Subscription revenue grew by 12% year-over-year, reaching $73.3 million, showing acceleration from the previous quarter [1][5] - Non-GAAP subscription gross margin improved to 80% in Q2 2025, up from 79.6% in Q2 2024 [6] Company Overview and Growth Strategy - PROS Holdings specializes in AI-driven enterprise software for pricing, quoting, and revenue management, targeting complex sectors like airlines and manufacturing [3] - The company focuses on technological leadership in AI and cloud computing, investing heavily in R&D to drive product innovation [4][7] Operational Highlights - The company secured new contracts with clients such as Air Greenland and Lennox, while expanding existing relationships with American Airlines and BASF [5] - Adjusted EBITDA showed strong improvement, although free cash flow declined due to timing of collections and increased commercial activities [8] Future Outlook - For Q3 2025, PROS Holdings expects GAAP revenue between $90.5 and $91.5 million, indicating approximately 10% growth at the midpoint [9] - The company raised its full-year subscription revenue outlook, projecting Subscription ARR for FY2025 to be between $310 million and $313 million [9] - Non-GAAP EPS for Q3 2025 is forecasted to be between $0.15 and $0.17, with adjusted EBITDA expected at $11 to $12 million [9]
X @Crypto Rover
Crypto Rover· 2025-07-17 19:28
AI & Cryptocurrency Overview - $WAVE is highlighted as a potentially promising AI investment within the cryptocurrency space [1] - The project has implemented a burn mechanism, with 25% of tokens already burned [1] - $WAVE generates over 88 $SOL in daily revenue from its AI Agents & BOTS [1] Revenue & Tokenomics - Revenue from AI Agents & BOTS will be used for buy-backs and token burning, similar to $HYPE and $BONK [1] - AI bots are being utilized by memecoins like USELESS and FARTCOIN, as well as approximately 4,000 other coins [1] Contract Information - The contract address (CA) for $WAVE is provided: 4GeDKXRW4uygk4XKWvPNMSrBhwPWnNwHDBmFaKH8bonk [1]
BERNSTEIN:AI vs. Human_ 评估 150 多家初创企业的人工智能产品- 颠覆剧本
2025-07-15 01:58
Summary of the Indian AI Startup Ecosystem Industry Overview - The report focuses on the Indian AI startup ecosystem, highlighting the rapid growth and potential of AI technologies in various sectors such as investment management, research, logistics, and media [1][2][5]. Key Insights - **Startup Growth**: Approximately 4,500 AI startups exist in India, with 40% founded in the last three years. The combined funding for the analyzed startups is around $3.5 billion, with over 80% having raised at least $1 million [2][5][10]. - **Diverse Applications**: The AI landscape in India features a wide range of applications, with 27 distinct streams identified. Process automation is the most common use case, followed by content generation and data analytics [3][21][27]. - **Innovation vs. Customization**: A critical question raised is whether Indian AI startups are genuinely innovative or merely customizing existing solutions. This distinction is vital for identifying future industry leaders [7][20]. Notable Startups - The report highlights several promising startups across various sectors, including healthcare, advertising, logistics, finance, and content generation. These startups are expected to experience significant growth in the coming years [4][35]. - Examples include: - **Qure AI**: Focuses on medical imaging and diagnostics [35]. - **Shipsy**: An AI-powered logistics platform [35]. - **Wokelo**: Provides generative AI for investment research [35]. - **Kroop Ai**: Develops solutions for deepfake detection [35]. Funding Landscape - The funding environment for AI startups in India is robust, with 81% of the analyzed startups having raised over $1 million and 40% securing more than $5 million [14][10]. - The majority of startups are in the early or growth stages, indicating a healthy pipeline for future development [11][14]. Challenges and Opportunities - **Market Positioning**: Despite being a hub for tech talent, India lacks major product-based tech companies, primarily hosting IT services firms. The emergence of AI startups presents an opportunity to shift this narrative [6][31]. - **Global Relevance**: The report emphasizes the potential for Indian AI startups to achieve global relevance, with many already serving international clients [1][5]. Conclusion - The Indian AI startup ecosystem is vibrant and diverse, with significant funding and a wide array of applications. While challenges remain in terms of innovation and market positioning, the potential for growth and global impact is substantial [31][34].
X @s4mmy
s4mmy· 2025-07-11 16:31
AI Token Market Trends - AI tokens are demonstrating significant strength as major cryptocurrencies break through price discovery, indicated by Nansen 24-hour net inflows [1] - Virtuals_io (ACP) is experiencing substantial momentum with 7-figure (millions of USD) net inflows, leading the leaderboard [1] - REI Network's Core 0.3 upgrade enhances research tooling, featuring "Agent2Agent non-linguistic communication" [2] - IO is reporting $16 million in network earnings (revenue) from 17 million compute hours delivered, signaling potential revenue-driven trends [3] Bittensor (TAO) Ecosystem - Bittensor's ecosystem is expanding with 129 subnets, requiring millions of USD worth of TAO to create a single subnet, effectively reducing circulating supply [3][4] - Compelling models are emerging within the TAO ecosystem, including Mentat Minds, Subnet 33 (ReadyAI), Subnet 50 (SynthdataCo), and Subnet 89 (Infinite Hash) [4][5] - Subnet 33 (ReadyAI) powers Seedphrase AI Agent, providing NFT insights [4] - Subnet 50 (SynthdataCo) powers the prediction engine for Mode's crypto trading co-pilot [5] - Subnet 89 (Infinite Hash) offers exposure to Bitcoin mining via a Bitcoin mining pool [5] Decentralized AI Infrastructure - IO is partnering with Genlayer to integrate decentralized GPU inference [3] - Bittensor subnets are gaining traction as decentralized open-source AI gathers momentum [3]
X @s4mmy
s4mmy· 2025-07-11 14:03
RT s4mmy (@S4mmyEth)As Bitcoin hits price discovery it's important to pay attention to the coins showing strength.Nansen 24-hour net inflows show that AI tokens continue to run hard as majors break:i) @virtuals_io : ACP + Decentralized Governance.Once again 7-figure net inflows and top of the leaderboard as ACP gathers momentum.The first phase of governance proposals passed highlighting an engaged veVIRTUAL holder base.Expect more to come as innovative teams launch agents to disrupt their respective industr ...
Jefferies:人工智能会抢走我们的工作吗?
2025-07-04 01:35
Summary of Key Points from the Conference Call Industry Overview - The focus of the conference call is on the integration of AI across various sectors, particularly in the context of corporate strategies and employee sentiments regarding AI adoption [1][2]. Core Insights 1. **CEO Pressure and AI Integration** - A significant 74% of CEOs believe they could lose their jobs within two years if they do not deliver measurable AI-driven business gains [5] - 54% of CEOs acknowledge that at least one competitor has already implemented a superior AI strategy [5] - 92% of CEOs feel their company would benefit from adding or replacing a board member with an AI subject matter expert [5] 2. **AI Mentions in Corporate Discourse** - In the first half of 2025, 243 unique US stocks referenced AI agents a total of 478 times, with the highest mentions in Information Technology, Consumer Discretionary, and Financials [2][9]. - The top three sub-industries discussing AI agents are Data Processing & Outsourced Services, IT Consulting & Other Services, and Broadline Retail [2][12]. 3. **Employee Sentiment** - There has been a notable increase in negative employee feedback regarding AI, with 48% of AI mentions in Glassdoor reviews of non-tech companies being negative [6][25]. - Overall and Senior Management Glassdoor ratings have declined over the past two years, particularly in Real Estate and Information Technology [27]. 4. **AI Strategy and Implementation Challenges** - 37% of CEOs report delays in AI initiatives, while 32% have canceled or abandoned projects due to regulatory uncertainty [5]. - 35% of AI initiatives are perceived as "AI washing," providing little to no real business value [5]. 5. **Future Outlook and Strategic Priorities** - 78% of CEOs have prioritized AI strategy and execution as a core part of their company's 2025 business goals [5]. - 86% of CEOs are confident that pre-built "off the shelf" AI agents can be as effective as custom-built solutions [5]. Additional Important Insights - The cumulative mentions of AI in Glassdoor reviews have been increasing, with a significant rise noted since 2024 [6][19]. - The sectors with the most negative AI mentions include Health Care (54% negative), Real Estate (58% negative), and Financials (52% negative) [25]. - The decline in Glassdoor ratings for senior management is particularly pronounced in Real Estate and Information Technology, indicating potential issues with leadership perception in these sectors [27]. This summary encapsulates the critical points discussed in the conference call, highlighting the current state of AI integration in various industries, the pressures faced by CEOs, and the evolving sentiments of employees regarding AI initiatives.
摩根大通:首席投资官调查_半导体、美国硬件_半导体行业专家评论
摩根· 2025-07-04 01:35
Investment Rating - The report maintains a bullish outlook on the semiconductor industry, particularly driven by sustained strong AI spending intentions from CIOs [7]. Core Insights - The 2025 CIO Survey indicates that approximately 68% of CIOs plan to allocate more than 5% of their IT budgets to AI compute hardware within three years, up from around 25% currently [7]. - AI-related compute spending as a percentage of CIO IT budgets is projected to rise to 15.9% in three years, reflecting a growth rate of 41%, which surpasses the semiconductor revenue growth outlook of 30-35% [7]. - Cloud spending is also expected to increase to 38% of IT budgets over the next five years, indicating a healthy business environment for Cloud Service Providers (CSPs) [7]. - Despite some caution regarding spending in the second half of 2025 due to geopolitical dynamics, the overall sentiment remains positive for a multi-year spending cycle in AI infrastructure [7]. Summary by Sections TMT Themes - Telecom sector saw a net increase in long positions, with a low positioning ratio indicating potential for growth [3]. - AI Data Centers have reached all-time high positioning, reflecting strong demand [3]. Semiconductor Insights - Chroma ATE is expected to secure metrology toolset orders from TSMC, indicating confidence in its market position [10]. - The semiconductor sector is experiencing a resurgence in demand for AI servers, driven by Nvidia GPUs and AWS ASICs [20]. Market Dynamics - Hedge funds have shown a modest increase in net buying, with North America being a significant contributor [2]. - The report highlights a potential risk of de-grossing among equity long/short funds, which could impact market dynamics [4].
How Rakuten AI for Business AI Builds Production-Ready Agents with LangGraph
LangChain· 2025-06-24 16:30
[Music] So my name is Yuk Kaji and I'm reading the product and engineering and rakuten as a general manager AI for business. So at Rakuten uh we are building a suite of AI product uh that empower both our employee and our customers. So we have built the racketen AI for business to support our business client in essential business operation from market analysis to customer support. So in addition uh we have built our internal generative AI platform designed for over 70 plus uh business across Japan and beyon ...
AI Agents Unlocked: CACEIS Redefines Client Conversations With VAST Data and NVIDIA
NVIDIA· 2025-06-12 18:34
AI应用与客户服务 - CASE 作为欧洲领先的资产服务公司,利用 AI Agent 捕捉客户交流的真实含义 [1] - 传统 AI 转录遗漏了超过 60% 的客户会议关键信息 [2] - AI Agent 使用 Nemo Retriever 从多模态数据源提取上下文,并利用 Llama Neatron 创建包含完整细节和个人信息修订后的两个版本 [2] - 客户关系 Agent 可以检测情绪、分析异议并触发后续行动,以帮助领导者进行指导 [3] - 产品分析 Agent 使用修订后的数据和人口统计信息来识别 VIP 功能请求并生成 Jira 工单 [3] 技术与合作 - CASE 与 Vast Data 和 Nvidia 合作构建 AI Agent [1] - 借助 NVIDIA Nemo 数据飞轮和 Vast AI 操作系统,Agent 可以不断学习和改进 [4] - VAST 和 NVIDIA 帮助企业为每位员工构建定制 AI Agent [4] 数据处理与安全 - AI Agent 在使用数据的同时,保护访问控制 [3] - AI Agent 可以处理完整细节和个人信息修订后的数据,满足不同角色的需求 [2][3]