Renault Duster sales declined in July despite year-on-year growth

River AI has successfully raised $1.1 billion in funding to scale its full-featured artificial intelligence platform. The round was led by General Catalyst and AMP PBC, with strategic support from NVIDIA and AMD Ventures. Y Combinator and Temasek also participated in the financing.

The Palo Alto-based company was founded by Igor Babushkin, who previously co-founded xAI. Before that, Babushkin worked on generative modeling and reinforcement learning at Google DeepMind, and also managed large-scale training processes at OpenAI before helping launch xAI.

The funds raised by River will be directed towards product development and expanding the company's operations. River creates infrastructure that gives developers and enterprises greater control over their AI models. The company's strategy focuses on training, deployment, hardware, and personalized AI products.

To achieve this, River uses an API specifically designed for creating custom models. The platform offers fine-tuning using LoRA and reinforcement learning for advanced open-weight models. This allows developers to adapt models without building extensive infrastructure themselves.

The company claims that enterprises can complete complex reinforcement learning sessions in 15–20 minutes. Furthermore, River states that its platform costs two to four times less than closed-source alternatives. These processes include fast weight transfer and stable sampling during training. River also manages elastic computing resources as workloads change, allowing developers to focus more on improving model performance.

Trained models can transition directly into production environments through the River platform. The company uses token-based billing for training and inference, which is intended to reduce costs associated with unused GPU power.

Babushkin stated that the company is convinced of the need to make AI more accessible and open. He also emphasized that AI should work for the benefit of users, not the laboratories that create it. Therefore, River aims to give users greater control over intelligence.

The company is implementing a broader strategy that goes beyond enterprise software. It is developing hardware designed to bring personal AI closer to users. Work is also underway on products focused on personalization and continuous learning.

The funding round also attracted major semiconductor companies. NVIDIA and AMD Ventures joined the round as strategic investors. Their participation reflects the significance of computing infrastructure for River's expansion.

General Catalyst CEO Hemant Tanenya noted the growing importance of open-weight models for AI leadership. He also highlighted River's commitment to giving users greater control. Thus, the investment supports a broader trend toward more accessible AI development.

The founders of River have extensive experience in cutting-edge AI research and development. Babushkin worked on generative modeling and reinforcement learning at Google DeepMind, and later helped lead large training programs at OpenAI before co-founding xAI. The team also includes specialists from xAI and Tesla, giving River experience in deep learning and reinforcement learning, supporting ambitions to develop AI infrastructure at multiple levels.

River positions its platform around this demand, aiming for enterprises to customize models without needing to maintain expensive infrastructure teams. The token-based pricing model is also aimed at increasing predictability of computing costs.

July was the fourth consecutive month of growth. In June, Western carriers accounted for the transportation of 34.4% of crude oil, according to data from Kommersant newspaper.

Greek carriers are the main among Western companies in the transportation of Russian oil. Analysts quoted by Russian press note that the average price for Urals crude oil transported to the Primorsk port (in the Baltic Sea) in July was $52.93, which is the lowest price in five months.

At the beginning of July, prices dropped to $39.7 per barrel. This allowed deals to be conducted within the maximum limit of $60 per barrel set by the United States, as well as within the limit of $44.1 per barrel imposed by the European Union, the United Kingdom, and Canada as sanctions against Russia after the start of the war in Ukraine in 2022.

According to Kommersant, maritime exports of Russian oil reached 4.3 million barrels per day in July. This is 7% less than in June, but 26% more than in the same month last year. This figure represents the second largest monthly export volume in 2026.

Exports to China increased by 18% compared to June and by 12% year-on-year, reaching 1.01 million barrels per day. At the same time, exports to India decreased by 58% compared to June and by 39% compared to July 2025, amounting to 994,000 barrels per day.

Nevertheless, exports of Russian oil to Singapore more than doubled in July compared to June, reaching 456,000 barrels per day.