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PPIO联合创始人姚欣获聘“光谷全球产业合伙人” PPIO以普惠算力助力武汉AI创新
Zheng Quan Ri Bao Wang· 2026-01-27 13:14
此外,PPIO未来将联合武汉本地园区、高校与孵化机构,为初创企业及中小企业提供门槛更低、成本 更可控的算力支持,助力将高成本算力转化为"可负担"的创新要素,推动更多企业从0到1的AI场景创新 实践。目前PPIO已支撑全球超过32万+开发者及数千家企业的AI算力需求。 本报讯 (记者袁传玺)1月25日,"2026光谷AI产业发展峰会"在中国光谷举办。PPIO联合创始人兼CEO 姚欣受邀出席,并获东湖高新(600133)区正式授牌,受聘为"光谷全球产业合伙人",成为助力光谷链 接全球产业资源的重要伙伴之一。峰会上,姚欣还主持了主题为《武汉如何抓住AI浪潮的机会》的圆 桌论坛,分享了对AI趋势与区域创新发展的深度洞察。 作为从武汉走出来的创业者,姚欣获东湖高新区正式授牌,受聘为"光谷全球产业合伙人",将为光谷链 接和引入更多优质产业资源。"湖北作为国家算力网络的中部枢纽,把供给侧能力系统化、规模化,这 对中国AI产业非常关键。但算力真正进入产业,还需要把'建得出来'变成'用得起来、用得好、用得 省'。PPIO的价值正是在'算力运营'和'算力调度'层,把供需两侧打通,提升算力周转效率。"姚欣表 示。 PPIO将依托其 ...
Akamai(AKAM) - 2025 Q3 - Earnings Call Transcript
2025-11-06 22:30
Financial Data and Key Metrics Changes - Akamai reported Q3 2025 revenue of $1.055 billion, representing a 5% year-over-year increase as reported and a 4% increase in constant currency [4][20] - Non-GAAP operating margins improved to 31%, and non-GAAP earnings per share was $1.86, up 17% year-over-year as reported and in constant currency [4][20] - Non-GAAP net income for Q3 was $269 million, with a non-GAAP EPS of $1.86, exceeding guidance by $0.20 [21][24] Business Line Data and Key Metrics Changes - Cloud Infrastructure Services (CIS) revenue was $81 million, up 39% year-over-year as reported and in constant currency, accelerating from a 30% growth rate in Q2 [6][19] - Security revenue reached $568 million, up 10% year-over-year as reported and 9% in constant currency, with high-growth security products generating $77 million, an increase of 35% year-over-year [20][14] - Delivery revenue was $306 million, down 4% year-over-year as reported and in constant currency, but showing improved trends [20] Market Data and Key Metrics Changes - International revenue was $525 million, up 9% year-over-year, representing 50% of total revenue in Q3 [20] - Foreign exchange fluctuations positively impacted revenue by $4 million sequentially and $8 million year-over-year [20] Company Strategy and Development Direction - Akamai is transitioning from a CDN pioneer to a leader in cloud security and distributed cloud computing, with a focus on AI inference capabilities [5][10] - The launch of Akamai Inference Cloud aims to support the growing demand for AI inference on the internet, positioning the company to leverage its distributed architecture [7][11] - The company emphasizes the importance of reliability, aiming for five nines of uptime, which is critical for attracting major clients like banks [75] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in the growth of CIS and high-growth security solutions, anticipating continued strong demand for AI-related services [20][24] - The company expects Q4 revenue to be in the range of $1.065 billion to $1.085 billion, reflecting a 4%-6% increase as reported [23] - Management noted that the AI inference market is at a transition point, with significant growth expected as AI systems are adopted at scale [10][12] Other Important Information - Akamai's CapEx for Q3 was $224 million, representing 21% of revenue, as the company continues to invest in its CIS business [21] - The company has not repurchased any shares in Q3 but has spent $800 million year-to-date on share buybacks, marking the largest annual buyback in its history [21][22] Q&A Session Summary Question: Guidance on security and compute growth - Management reiterated security growth at about 10% and compute growth slightly under 15% for the year, with momentum in CIS [28] Question: Insights on Akamai Inference Cloud - Management indicated strong interest and demand for AI applications, with many customers looking to adopt inference capabilities [30][32] Question: Hiring strategy for sales reps - The company is continuing to hire sales reps to support new business sales in security and compute, with a transformation expected to be largely complete by Q2 next year [36][37] Question: Confidence in benefiting from capacity constraints at hyperscalers - Management highlighted Akamai's unique platform and extensive points of presence, which allow it to provide faster services compared to hyperscalers [41][42] Question: Opportunities in API Security - Management confirmed ongoing efforts to extend API security into new agentic protocols, with strong interest from customers [44] Question: CapEx requirements for inference - Management noted that CapEx will closely follow revenue and demand, with expectations for similar gross margins to current compute margins [46][47] Question: Traffic mix and future trends - Management indicated that video delivery currently dominates traffic, but AI applications are expected to increase traffic significantly in the future [68][70]
Akamai Inference Cloud Transforms AI from Core to Edge with NVIDIA
Prnewswire· 2025-10-28 17:57
Core Insights - Akamai Technologies has launched Akamai Inference Cloud, a platform designed to enhance AI inference capabilities by moving processing closer to users and devices, thereby reducing latency and improving performance [1][2][4] Company Overview - Akamai Inference Cloud leverages Akamai's global edge network, which consists of over 4,200 locations, and NVIDIA's advanced AI infrastructure to provide scalable, low-latency AI processing [4][5] - The platform aims to support the next generation of AI applications, including personalized digital experiences and real-time decision systems, by enabling intelligent, agentic AI inference at the edge [2][3] Technological Advancements - The platform integrates NVIDIA RTX PRO Servers and BlueField DPUs, enhancing the ability to process AI workloads efficiently from core to edge [4][5] - Akamai Inference Cloud is designed to facilitate streaming inference and agentic AI workflows, allowing for near-instantaneous responses and improved user engagement [5][9] Market Positioning - The launch targets 20 initial locations globally, with plans for further expansion, positioning Akamai as a leader in edge AI processing [6] - The collaboration with NVIDIA aims to redefine AI inference by decentralizing data processing and routing requests to optimal models, enhancing the capabilities of smart commerce agents and financial decision-making [5][9]