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Nvidia’s New AI Chips Slash Training Times for Massive AI Models

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Nvidia’s latest generation of AI chips is making significant advances in training some of the world’s largest artificial intelligence systems, according to new benchmark data released on Wednesday by MLCommons, a nonprofit organization that tracks AI system performance.

The results show a dramatic drop in the number of chips required to train large language models (LLMs), highlighting Nvidia’s growing technological lead in this critical area of AI development. While much of the financial market’s current focus is on the booming sector of AI inference—where AI models answer user queries—training remains a core competitive battleground, especially for developing next-generation models with trillions of parameters.

Blackwell Chips Outperform Previous Generations

Nvidia’s new Blackwell chips demonstrated superior performance over its previous Hopper generation. In tests involving Meta Platforms’ open-source Llama 3.1 405B model, which is complex enough to simulate some of the most demanding AI training workloads, Nvidia’s Blackwell chips completed training tasks with more than double the speed per chip compared to Hopper.

In one benchmark, a system using 2,496 Blackwell chips completed the training run in just 27 minutes. By comparison, even though more than three times as many Hopper chips were used in previous tests, they only achieved faster results due to sheer scale rather than efficiency.

Nvidia and its partners were the only ones to submit data for models of this size, giving Nvidia a clear demonstration of its leadership in training capabilities for multi-trillion parameter models.

Changing Industry Trends in AI Training

Chetan Kapoor, chief product officer of CoreWeave, which collaborated with Nvidia on the results, noted that AI companies are moving away from building vast, homogenous data centers with 100,000 or more identical chips. Instead, they are increasingly assembling smaller, specialized subsystems that handle different aspects of the training process. This modular approach allows companies to speed up training times and manage extremely large model sizes more efficiently.

“Using a methodology like that, they’re able to continue to accelerate or reduce the time to train some of these crazy, multi-trillion parameter model sizes,” Kapoor explained at a press briefing.

Global Competition Also Heating Up

While Nvidia maintains a dominant position, competitors around the world are also pushing for breakthroughs. For example, China’s DeepSeek has recently claimed it can create competitive chatbots while using far fewer chips than many U.S. rivals, adding to the growing international race for AI supremacy.

MLCommons’ report also included results from Advanced Micro Devices (AMD) and others, though Nvidia’s Blackwell system stood out in the training category.

LinkedIn Lawsuit Over Customer Data Use for AI Models Dismissed

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A class action lawsuit against Microsoft’s LinkedIn, which accused the platform of using customers’ private messages to train artificial intelligence models, has been dismissed. The case was dropped by plaintiff Alessandro De La Torre on Thursday in the U.S. federal court in San Jose, California, just days after the suit was filed. LinkedIn had argued that the allegations were unfounded.

De La Torre’s lawsuit claimed that LinkedIn violated the privacy of its Premium users by disclosing their private messages to third parties involved in developing AI. He accused the platform of breaching its promise to use customer data only to enhance its services, not for external uses like AI training.

The issue came to light when LinkedIn updated its privacy policy in September, revealing that a new account setting would not affect data used in previous AI training. This disclosure sparked concerns among users about how their data was being handled.

However, LinkedIn clarified that it had not shared private messages with third parties for AI training. In a LinkedIn post, Sarah Wight, the company’s vice president and legal counsel, confirmed, “We never did that.” De La Torre’s legal team acknowledged the clarification, stating that users could take comfort in knowing their private messages had not been used for AI purposes.

Microsoft to Invest $3 Billion in India to Expand AI and Cloud Infrastructure

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Microsoft is set to invest $3 billion over the next two years to enhance its Azure cloud and artificial intelligence (AI) capabilities in India, CEO Satya Nadella announced on Tuesday. This marks the company’s largest investment in India to date, underscoring the strategic importance of the country, which offers a robust tech ecosystem and cost-effective expertise. The initiative also includes efforts to upskill the Indian workforce in AI, with plans to further train 10 million people in AI by 2030.

The investment comes on top of Microsoft’s previously announced $80 billion plan to build AI-enabled data centers for fiscal 2025. This expansion in India is seen as a critical component of Microsoft’s strategy to tap into the country’s growing tech talent, with over 20,000 employees across 10 Indian cities. Nadella emphasized the significance of India’s developer community, which is already the second-largest on GitHub, with projections to surpass the U.S. by 2028.

In Bengaluru, where Nadella was speaking at a conference, he highlighted India’s contributions to Microsoft’s AI projects, specifically in relation to GitHub Copilot, the company’s generative AI tool for developers. Nadella also stressed that India’s involvement in AI initiatives is second only to the U.S., showcasing the country’s vital role in the company’s global AI ambitions.

This investment is part of Microsoft’s broader efforts to ensure its AI technologies generate profitable returns. GitHub Copilot has already shown success, with a reported annual run-rate of $2 billion in July. The company is also focused on empowering India’s talent pool, with plans to further upskill millions and foster innovation in cloud and AI sectors.

The announcement reflects the strong ties between Microsoft and India, where Nadella, who is of Indian origin, enjoys significant respect. The “Microsoft AI Tour,” which Nadella is currently part of, has drawn large crowds, including tech professionals eager to see new product developments and interact with the company’s leadership.