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OpenAI to spend $100B on backup servers in five-year cloud push

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OpenAI plans to spend $100 billion over the next five years renting backup servers from cloud providers, according to The Information. The investment comes on top of the $350 billion the company has already projected for server rentals between now and 2030, underscoring the massive infrastructure costs of training and deploying advanced AI systems.

The spending spree reflects the global race for scarce computing capacity, benefiting cloud giants and chipmakers as AI developers scramble to secure the hardware needed to train and run ever-larger models. With backup capacity included, OpenAI expects to average $85 billion annually on server rentals over the next five years.

Executives told shareholders the servers are “monetizable,” meaning they could generate additional revenue not yet included in forecasts—either by enabling new research breakthroughs or handling spikes in product demand. Even so, OpenAI is projected to burn about $115 billion in cash through 2029, as it scales infrastructure to match the ambitions of ChatGPT and future AI models.

The enormous outlays highlight both the intensity of the AI arms race and the risks: investors are betting that today’s infrastructure bets will translate into tomorrow’s breakthroughs and revenue streams.

DeepSeek claims AI model trained for just $294,000, challenging U.S. rivals

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Chinese AI developer DeepSeek has disclosed that its reasoning-focused R1 model cost just $294,000 to train—dramatically below the hundreds of millions reportedly spent by U.S. leaders such as OpenAI. The figure, revealed in a Nature article co-authored by founder Liang Wenfeng, is the company’s first public estimate of training costs and is likely to reignite debate over China’s position in the global AI race.

According to the paper, R1 was trained on a cluster of 512 Nvidia H800 chips over 80 hours. DeepSeek acknowledged for the first time that it also owns Nvidia A100 GPUs, which were used in preparatory phases before training shifted to the China-specific H800s. The H800 was designed to comply with U.S. export restrictions that bar Nvidia from selling its more powerful H100 and A100 chips to China.

The cost revelation is striking: OpenAI CEO Sam Altman has said foundational models cost “much more” than $100 million to train, though OpenAI has never published detailed figures. DeepSeek’s claim of drastically lower costs fueled January’s investor selloff in global tech stocks, amid fears it could disrupt the market dominance of Nvidia and other AI giants.

Skepticism remains. U.S. officials have suggested DeepSeek may have obtained H100 chips despite restrictions, while U.S. companies have questioned whether its development relied on model distillation—a technique where one AI model learns from another. DeepSeek has admitted using Meta’s open-source Llama models and said its training data may have included content generated by OpenAI systems, though it insists this was incidental.

DeepSeek defends distillation as an efficient way to cut costs and expand access to AI by reducing the enormous energy and resource demands of large-scale training. Analysts note this could accelerate the spread of competitive AI models outside the U.S., though questions about intellectual property and national security will remain central to the debate.

ASML to Become Top Shareholder in Mistral AI With $1.5B Investment

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ASML, the Dutch maker of cutting-edge chipmaking equipment, will become the top shareholder in French startup Mistral AI after leading its latest €1.7 billion (~$2B) Series C funding round, sources told Reuters. ASML is committing €1.3 billion ($1.5 billion), securing a board seat at Mistral in the process.

The funding values Mistral at €10 billion ($11.7 billion) pre-money, making it the most valuable AI company in Europe. The deal underscores Europe’s push for technological sovereignty, reducing reliance on U.S. and Chinese AI models.

Founded in 2023 by Arthur Mensch (ex-DeepMind) along with Timothée Lacroix and Guillaume Lample (ex-Meta), Mistral has quickly positioned itself as Europe’s AI champion, competing with giants like OpenAI and Google. It was last valued above $6 billion in 2023 and has backing from Nvidia.

ASML, the sole supplier of extreme ultraviolet (EUV) lithography machines—vital for advanced chipmaking by firms like TSMC and Intel—could integrate Mistral’s AI-driven data analytics to improve its €180 million EUV systems. The partnership could bolster both firms: Mistral gains capital and industrial ties, while ASML sharpens its AI-enabled chipmaking capabilities.

The move highlights a rare strategic alignment of two European tech powerhouses. By tying together semiconductor infrastructure and AI model development, the partnership signals Europe’s intent to carve out a sovereign AI ecosystem in a field dominated by U.S. and Chinese players.