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Omni is a social app that gathers all the social media features and rewards users for using them.
CoreWeave and Nebius Earnings Reveal AI Cloud Computing Trends: Supply Shortage Persists, CSPs Move Toward "AI Infrastructure Operating Systems"
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-
Variational Secures $50 Million Series A Funding, Led by Dragonfly Capital
decentralized derivatives trading platform Variational has announced the completion of a $50 million Series A funding round. The round was led by Dragonfly Capital, with participation from Bain Capital Crypto and Coinbase Ventures. Headquartered in the Cayman Islands, the company is dedicated to building an on-chain derivatives protocol for institutional and traditional finance traders. By aggregating liquidity from both traditional finance and crypto markets, it aims to provide instantly tradable on-chain markets for real-world assets such as oil and commodities. Its core product, the Omni platform, adopts a zero-fee model and incorporates a liquidity pool mechanism to enhance market depth and execution efficiency.Variational stated that its goal is not to directly compete with centralized exchanges, but rather to connect multi-source liquidity through a "brokerage-style" model, including traditional finance market makers and major crypto trading platforms, in order to solve the "liquidity cold start" problem for on-chain markets. (Fortune)
Google 发布 Chrome 扩展 Nano Banana 与 Gemini Omni 打造可视化百科
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。
CoreWeave and Nebius Earnings Reveal AI Cloud Computing Trends: Supply Shortage Persists, CSPs Move Toward "AI Infrastructure Operating Systems"
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 Launches Nemotron 3 Nano Omni Model, Boosting Multimodal Inference Efficiency by 9x
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.
Related news
Google 发布 Chrome 扩展 Nano Banana 与 Gemini Omni 打造可视化百科
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。
CoreWeave and Nebius Earnings Reveal AI Cloud Computing Trends: Supply Shortage Persists, CSPs Move Toward "AI Infrastructure Operating Systems"
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-
Amazon Restructures AI Strategy, Gradually Phasing Out Most Nova Flagship Models and Betting on Frontier Model R&D
According to Business Insider, citing sources familiar with the matter, Amazon is comprehensively adjusting its artificial intelligence strategy. Following layoffs in the AGI department and the closure of related laboratories, the company is further consolidating fragmented model R&D directions. The company plans to gradually phase out most internal flagship Nova models, including Premier, Omni, Reel, and Canvas, and will concentrate engineering and compute resources on new frontier model development plans.
Variational Secures $50 Million Series A Funding, Led by Dragonfly Capital
decentralized derivatives trading platform Variational has announced the completion of a $50 million Series A funding round. The round was led by Dragonfly Capital, with participation from Bain Capital Crypto and Coinbase Ventures. Headquartered in the Cayman Islands, the company is dedicated to building an on-chain derivatives protocol for institutional and traditional finance traders. By aggregating liquidity from both traditional finance and crypto markets, it aims to provide instantly tradable on-chain markets for real-world assets such as oil and commodities. Its core product, the Omni platform, adopts a zero-fee model and incorporates a liquidity pool mechanism to enhance market depth and execution efficiency.Variational stated that its goal is not to directly compete with centralized exchanges, but rather to connect multi-source liquidity through a "brokerage-style" model, including traditional finance market makers and major crypto trading platforms, in order to solve the "liquidity cold start" problem for on-chain markets. (Fortune)
NVIDIA Launches Nemotron 3 Nano Omni Model, Boosting Multimodal Inference Efficiency by 9x
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.