IBM recently launched its innovative IBM Enterprise Advantage service, a groundbreaking asset-based consulting offering that integrates proven AI tools with expertise to help companies quickly establish, govern, and scale custom internal AI platforms.

With IBM Enterprise Advantage, businesses can restructure workflows, streamline AI integration with existing systems, and scale new intelligent applications without altering their cloud providers, AI models, or core infrastructure. This flexibility extends across major cloud platforms such as Amazon Web Services, Google Cloud, Microsoft Azure, and IBM watsonx, enabling seamless expansion based on existing technology investments.

The service leverages the technical prowess and industry insights of IBM consultants, built upon the AI-driven delivery platform IBM Consulting Advantage. This platform has created a robust ecosystem of vertical industry AI agents and applications, serving over 150 client projects and enhancing consultant productivity by up to 50%.

For instance, Pearson, a leader in lifelong learning, customized an AI-driven platform through this service, combining human expertise with intelligent assistants to improve daily operational efficiency and enhance data-driven decision-making. Similarly, a manufacturing firm is advancing its generative AI strategy by identifying high-value application scenarios and achieving executive alignment on core strategies, resulting in the secure deployment of AI assistants for enterprise-wide scaling.

Mohamad Ali, IBM's Senior Vice President and head of IBM Consulting, highlighted that many companies strive to leverage AI but face challenges in achieving scalable commercial value. He emphasized that IBM has developed a practical guide through overcoming internal challenges with AI, providing clients with the confidence to deploy scalable AI solutions that yield tangible results. The Enterprise Advantage service is now officially available.

AI两周设计火箭发动机：商业航天迎来效率革命
米风感知 2026-01-21 11:47

2024年6月，迪拜人工智能工程公司LEAP 71利用其大型计算工程模型Noyron，仅用两周时间完成火箭发动机的设计并成功进行了点火测试。这一进展标志着航天制造业效率革命的开端。

Noyron的成功在于其将物理知识编码于统一框架，能够自主生成完整工程设计，整个过程无需人工干预，设计效率提升达数十倍。通过与Aconity3D合作，LEAP 71采用光粉末床熔融（L-PBF）技术，直接从AI设计到3D打印，有效制造复杂内部结构，从而将成本降低了50%以上。

该技术的具体应用表现令人瞩目。在蓝箭火箭发动机的仿真计算中，AI驱动方法显著提升效率，将传统需5000小时的模拟缩短到仅需5000秒，提升达3600倍。此外，LEAP 71通过收集测试数据反馈给Noyron，形成“设计-打印-测试-学习”的闭环，使得设计不断进化。

SpaceX作为行业先锋，已经将AI应用于火箭设计与制造中，显著降低了成本和开发时间。例如，猛禽发动机的成本从200万美元骤降至25万美元，其推力却翻倍。此外，通过AI和3D打印的协同，推动了火箭发动机设计的复杂性与性能提升。

这场以AI为驱动的航天制造革命正在改变传统航空航天的工作模式，大幅降低太空旅行成本，推动人类的深空探索进入更高效的新时代。

C114讯 1月20日消息（岳明）— Ookla最近发布的报告《AI时代的上行链路分析》探讨了在人工智能（AI）浪潮下，全球移动通信网络面临的新挑战，特别是上行链路的需求变化。随着生成式AI和实时视觉分析等应用的崛起，用户的音视频流不断上传至云端，导致上行链路流量呈指数级增长，对网络容量、延迟和稳定性提出了新要求。

报告指出，传统移动网络主要设计为满足用户的下载需求，但AI驱动的设备如智能眼镜和实时助手要求持续的上传能力，使上行链路变得至关重要。对此，网络运营商需重新审视资源分配策略，转变为更加关注上行链路的支持。

中国运营商在上行链路资源分配方面领先，而美国主要运营商的投入则较少。这种差异与市场需求、用户习惯和网络战略紧密相关。而技术上，TDD已成为5G中频网络的主流选择，尽管运营商的实际资源分配仍存在显著差异。

报告还指出，AI应用将带来巨大的网络需求变化，预计到2040年，上行流量将激增至35%。为了应对这一趋势，运营商需将上行作为核心战略指标，优化TDD技术，并加快上行增强技术的部署。同时，跨领域合作与前瞻性网络规划也是关键，以适应日益增长的AI流量需求。

On January 19, the Nantong Municipal Government held a "New Industrialization" conference focused on "AI+Manufacturing," marking its third consecutive year of initiating specialized efforts for new industrialization at the start of the year. This year's theme is more focused and clearer, reflecting the city's aim to integrate artificial intelligence into its robust manufacturing sector.

Nantong launched the "Action Plan for Advancing AI+Manufacturing," emphasizing a dual-driven approach combining AI application and service supply. The plan targets crucial areas such as marine engineering, new energy, and healthcare, aiming to create a vibrant AI industrial belt involving specialized parks and communities. By the year 2027, Nantong aims to establish a computational power of 30,000 PFLOPS, develop 30 industry-specific AI models, and produce 100 notable AI case studies, all contributing to a diversified AI-enabled manufacturing ecosystem.

Concrete applications of AI in manufacturing in Nantong already showcase tremendous benefits. For instance, Jiangsu Dasheng Group's intelligent textile factory has improved automation rates from 60% to 90%, drastically lowering defect rates. Meanwhile, Zhongtian Technology integrated AI across its operations, enhancing productivity by over 30% and extending these solutions to numerous other enterprises.

Nantong’s commitment to AI+Manufacturing positions it to leverage its profound industrial foundation, with incentives like substantial financial support for businesses utilizing smart computing. The city recognizes the importance of innovation and collaborative regional development, setting itself on a clear path toward becoming a pivotal player in China’s advanced manufacturing landscape by the end of the 14th Five-Year Plan.