From AI infra with @GoKiteAI, to signing tools from @cubistdev, to @snowpeerio new API, builders are reimagining what’s possible.Join us live right here on 9/29 at 12p ET for Episode 2 of Building on Avalanche with @BreevieGotRekt and @AvalancheFDN to see it all come to life. https://t.co/F62qamdzAb ...

今年下半年希望 Crypto AI 的一些大融资项目能尽快抓住降息前的好时机发空投 + TGE 吧。之前从陆老师那儿了解到从决策终端解决的 AI infra 项目 Allora @AlloraNetwork 算是融资背景非常豪华，目前已经拿到了包括 Polychain、Framework、Delphi Digital 在内的 3500 万美元融资，TGE 预计在 8 月除了融资背景之外，团队背景和资源也不错，是由 Chainlink 核心成员组成的，还联合了 Coinbase、LayerZero 等项目成员，他们做的这个项目简单来说，“我们不生产模型，而是模型的指挥官”，就像 AI 版的 Chainlink。如果把 Chainlink 比作数据聚合层，Allora 就是 Agent 聚合层这就是传承吗（bu），看看具体项目机制吧👉 核心机制：Model Coordination Network（MCN）Allora 自身不生产模型，而是不断容纳市面上优质的 AI Agent 让他们协同推理、最终输出一个最优答案- 模型互评：每个模型不仅输出自己的答案，还会预测其他模型可能的表现，用来判断谁更靠谱- 动态激励： ...

Core Insights - Qingcheng Jizhi, a leading player in the AI infrastructure sector, has successfully completed a new financing round exceeding 100 million yuan, marking its third round of funding within a year [1][3] - The investment was led by a prominent industry player, with participation from various influential capital sources in the computing power industry, indicating strong market interest in AI infrastructure [1][4] - The CEO of Qingcheng Jizhi highlighted that the funding will enhance the company's capabilities in product development, ecosystem building, and market expansion [2][4] Company Overview - Qingcheng Jizhi was established in December 2023 and focuses on developing intelligent computing system software, acting as a crucial link between intelligent computing and applications [3][6] - The company is led by a team from Tsinghua University, with its CEO being a PhD graduate from the same institution [3][6] Financing Strategy - The company has adopted a "small steps, quick runs" financing strategy due to the rapid changes in the AI infrastructure industry and the high demand for cash flow to support product development [4][6] - This strategy has attracted multiple investors who are optimistic about the company's technological capabilities [4][5] Technological Advancements - Qingcheng Jizhi's software solutions provide a full-stack approach to optimize underlying computing power, enhancing model training and inference efficiency while reducing costs for AI application development [6][7] - The company has developed the "Bagualu" high-performance model training system, which has shown significant acceleration in training tasks on large-scale domestic computing clusters [6][7] - The "Chitu" inference engine has been optimized for domestic computing power, achieving low latency and high throughput, thus supporting diverse application scenarios [6][7] Market Demand - The demand for computing power in the AI market has shifted from primarily training large models to a significant increase in inference power requirements [7][8] - Qingcheng Jizhi is addressing the diverse needs of clients, from small enterprises seeking cost-effective solutions to large organizations requiring comprehensive computing power solutions [8]