News linked to both this project and an event.
According to CoinDesk, Utexo, an infrastructure project supported by Tether, plans to issue USDT on the Bitcoin network this month. Utexo has obtained a commercial license to issue USDT on Bitcoin and plans to provide corresponding APIs, SDKs, and cloud infrastructure for exchanges, wallets, and payment service providers. Based on the RGB protocol and the Bitcoin UTXO model, Utexo will keep most transaction data off-chain, with a focus on supporting three types of applications: private USDT transfers, direct swaps between native BTC and USDT, and borrowing using native BTC as collateral without wrapping BTC to other blockchains. USDT was first issued on the Bitcoin network via the Omni protocol in 2014, after which Ethereum and Tron gradually became its primary circulating networks. Following the issuance of USDT on the Bitcoin mainnet, Utexo also plans to further expand to the Lightning Network.
Perp DEX protocol Variational posted on X: "With the Swap feature now officially live (and more trading markets continuing to roll out), our next major initiative is the Omni trading API. Previously, all trading could only be done through the frontend interface. Soon, traders will be able to programmatically trade across the 550+ traditional finance and crypto markets already available on Omni."
Google AI for Developers 发布一款 Chrome 扩展，结合 Nano Banana 与 Gemini Omni，将网络内容转化为交互式视觉百科全书。该扩展在 Antigravity 中使用 Gemini 3.7 Flash 构建，用户浏览网页时高亮任意文本，即可快速生成丰富的视觉化释义，辅助深度学习。
Odaily News - Analyst qinbafrank posted on X platform, stating that the latest earnings reports from CoreWeave (CRWV) and Nebius show the AI cloud computing (CSP) industry is entering a phase of rapid expansion. The competitive focus is shifting from simply providing GPU leasing to building AI infrastructure platforms that encompass computing power, software, data, and operational capabilities.Currently, AI computing demand still significantly exceeds short-term deliverable supply. Meanwhile, pricing power for AI computing is strengthening, but price increases are mainly concentrated on high-value resources. CoreWeave stated that prices for various GPU computing SKUs rose by approximately 25% on average in July; Nebius disclosed that prices for previous-generation GPUs increased by over 30% compared to Q1, with new contracts signed in Q2 averaging over $20 million in annualized revenue per MW, some projects reaching $20 million to $25 million, and short-term emergency capacity prices even reaching $40 million to $50 million per MW.However, price increases are mainly occurring in short-term capacity, next-generation GPUs, large-scale clusters, and production-grade AI inference scenarios. Traditional low-priority, long-term locked-in bare computing power has not seen concurrent price increases. From a profitability model perspective, project-level returns on AI computing are becoming clearer, but overall corporate return on invested capital (ROIC) still needs time to be validated. Nebius has for the first time disclosed relatively clear project payback periods, while CoreWeave is reducing GPU investment pressure through long-term contracts and asset-level financing. However, both companies remain in a high-capital-expenditure phase, with depreciation and financing costs continuing to compress profit margins.Nevertheless, an increasing number of individual projects are achieving closed-loop economic models, indicating that the AI infrastructure business model is gradually maturing. Additionally, both CoreWeave and Nebius are upgrading toward becoming "AI infrastructure operating systems." Future CSP competition will no longer be just about renting out GPU hours but will cover complete service systems including AI training, inference, storage, networking, model deployment, monitoring, security governance, and Agent runtime environments.In terms of capital models, the two companies are also taking different paths: Nebius leans more toward an asset-light model, building AI data centers through capital partners while providing AI infrastructure operations and software capabilities itself; CoreWeave, on the other hand, is promoting a hybrid cloud model through its Omni strategy, deploying complete AI cloud platforms to customers' own data centers and GPU resources, placing greater emphasis on enterprise-level and sovereign AI delivery.Overall, the AI cloud computing industry is evolving from "GPU rental providers" to "AI infrastructure platforms." Short-
NVIDIA announced on X platform that it has launched the open-source multimodal model Nemotron 3 Nano Omni today. The model adopts a 30B-A3B mixture-of-experts (MoE) architecture, supports a 256K context window, and can uniformly process video, audio, image, and text inputs. Compared to open-source omnimodal models at a similar interaction level, this model achieves up to a 9x increase in throughput, significantly reducing inference costs and improving scalability. Nemotron 3 Nano Omni is now available on Hugging Face, OpenRouter, and NVIDIA NIM, and has been adopted by enterprises including Aible, Applied Scientific Intelligence, and H Company.