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Zhipu has acquired AI Infra company Zhongke Jiahe for hundreds of millions, fully addressing the shortcomings in underlying heterogeneous computing power engineering

According to "AI Technology Review," China's leading large model company Zhipu has invested hundreds of millions of yuan to acquire the AI heterogeneous computing power software infrastructure company Zhongke Jiahe. This move aims to completely address Zhipu's shortcomings in the underlying engineering and compiler capabilities of large models, in response to the structural shortage of computing power and high-concurrency inference challenges caused by a surge in user numbers.Zhongke Jiahe's technology originates from the Compiler Laboratory of the Institute of Computing Technology, Chinese Academy of Sciences, founded by Dr. Cui Huimin. Its core team has been deeply involved in the development of compilers for several domestic chips, including Loongson, Sunway, Cambricon, and Huawei Ascend. Zhongke Jiahe's core advantage lies in its virtual instruction set technology, which can unify different brands and models of chip ecosystems through middleware software, assembling scattered domestic chips into a unified ultra-large-scale cluster, thereby significantly improving overall computing power utilization; its SigInfer inference engine is claimed by the official source to reduce the inference latency of large models by up to 74 times.Recently, Zhipu's Coding Agent business has experienced explosive growth. The newly released GLM-5.2 large model saw a 27-fold increase in daily Token call volume during its first week on the aggregation platform, leading to the exposure of systemic engineering bottlenecks in its inference infrastructure under high concurrency and long context scenarios. After being placed on the U.S. Entity List, Zhipu has actively promoted domestic alternatives and has now completed inference adaptation for eight major domestic computing power platforms, including Huawei Ascend, PingTouGe, and Moore Threads. The acquisition of Zhongke Jiahe will not only directly improve Zhipu's unit Token inference cost and output quality but also provide core underlying compiler technology support for its previously rumored self-developed custom AI inference chip plan.

a16z invests in AI agent security company Runta

Venture capital firm Andreessen Horowitz (a16z) announced an investment in AI Agent security startup Runta, which aims to help businesses manage and constrain AI agents like "raising children." The specific investment amount has not been disclosed.Runta founder Guanlan Dai previously worked on the technical team at Cloudflare and was a founding engineer at API connection startup Kong. He stated that AI agents share similarities with growing children: they have the ability to perform tasks autonomously but also require boundaries, supervision, and permission management. Dai believes that just as parents provide home safety protection for children and limit their access to credit cards, businesses also need to restrict the important documents that AI agents can access, the range of operations they are allowed to perform, and the amount of disposable funds available at one time.Runta is developing a set of "AI Agent guardianship" infrastructure to help businesses manage AI agents' permissions, security risks, and behavioral boundaries, preventing autonomous AI systems from causing data leaks, erroneous operations, or financial losses during task execution. As businesses increasingly deploy AI agents with autonomous decision-making capabilities, establishing a trustworthy and secure agent management system is becoming a new infrastructure requirement. Runta aims to become the "parental control layer" of the AI Agent era, providing capabilities such as agent identity management, permission control, risk limitation, and operational supervision for businesses. Industry insiders believe that as AI agents evolve from simple assistants to autonomous entities capable of operating business systems, handling transactions, and executing complex tasks, the infrastructure market surrounding agent security, governance, and compliance may experience rapid growth.

The Ethereum institutional privacy technology company EthSystems has officially been established to create Ethereum privacy solutions for institutions

The Ethereum institutional privacy technology company EthSystems has officially launched and received strategic funding support from ecosystem backers such as Bitmine, Sharplink Gaming, Joe Lubin, and SNZ Holding.EthSystems focuses on developing privacy technologies for banks, asset management companies, and other regulated entities, enabling institutions to execute financial transactions on the Ethereum network at scale while protecting sensitive information such as transaction details and client identities.The company was founded by the core team of the Institutional Privacy Task Force (IPTF) of the Ethereum Foundation. The team has previously conducted a year-long open-source research and development publicly on the EthSystems website and has established partnerships with several central banks, regulatory agencies, large banks, and asset management institutions. EthSystems stated that while institutions have begun exploring stablecoins, tokenized assets, and Ethereum-based settlement solutions, large-scale adoption still faces privacy and compliance challenges.Financial institutions need more than just access to blockchain networks; they require a complete infrastructure that meets business confidentiality protection, regulatory requirements, and compatibility with existing financial systems. The goal is to create a "selective disclosure" privacy architecture that allows transaction participants to view only the information they are authorized to access, while retaining the core advantages of Ethereum's decentralization, security, and openness, and complementing two other organizations: Ethlabs, which focuses on the research and development of Ethereum's core protocol and infrastructure; Ethereum Institutional, responsible for institutional collaboration, education, market research, and ecosystem coordination; and EthSystems, which focuses on application layer technology, transforming institutional needs into practical privacy protocols and financial systems.
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