FuriosaAI, a South Korean startup, is scaling production of its RNGD AI inference chip to compete in a market dominated by Nvidia.FuriosaAI, a South Korean startup, is scaling production of its RNGD AI inference chip to compete in a market dominated by Nvidia.

FuriosaAI takes on Nvidia with a new AI chip

2026/01/03 17:25
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As competition heats up in a market long dominated by Nvidia, FuriosaAI, a South Korean semiconductor startup creating artificial intelligence inference chips, plans to start producing its newest processor on a commercial scale this month.

Founded in 2017, the company is led by June Paik, a former Samsung Electronics memory-chip engineer. Paik began focusing on artificial intelligence about a decade ago while recovering from a torn Achilles tendon suffered during a Samsung company soccer event. During months of rehabilitation, he took online artificial intelligence courses offered by Stanford University. After returning to work, Paik left Samsung to pursue an AI-related venture.

“I left with absolute certainty that I had to get into the AI space,” Paik said. 

According to Paik, the idea for FuriosaAI took shape after discussions with former colleagues at a computing conference in Seoul, where artificial intelligence was a central topic. He later partnered with a former Samsung colleague and an associate with experience in algorithms, and the company was launched the same year.

Furiosa chip demonstrates efficiency for large AI models

Furiosa’s current chip, designated RNGD, short for “renegade,” is aimed at the inference phase of artificial intelligence, which involves running trained AI models. Nvidia’s graphics processing units (GPUs) currently dominate the broader AI computing market, particularly in training large models, but startups such as Furiosa are targeting inference as a potential area of competition.

The company’s latest funding round values Furiosa at close to $700 million. Meta Platforms approached Furiosa about a potential acquisition last year, but no deal was reached. OpenAI demonstrated the use of a Furiosa chip at a recent event in Seoul. while LG’s AI research division is testing the chip and said it showed “excellent real-world performance.” Furiosa said it is currently in discussions with potential clients.

According to Paik, Furiosa’s chips deliver performance comparable to Nvidia’s sophisticated GPUs while drawing less power. This would reduce the overall expense of putting AI systems into operation. The technology sector shouldn’t depend so heavily on a single chip manufacturer for AI computing, Paik argues.

“A market dominated by a single player—that’s not a healthy ecosystem, is it?” Paik said.

Paik began his career at Advanced Micro Devices (AMD), where he worked on GPU design, before returning to South Korea in 2013 to join Samsung. There, he led a small team developing new memory-chip products.

Hanjoon Kim, now Furiosa’s chief technology officer, previously worked with Paik at Samsung and later joined him in founding the company. Kim said Paik emphasized rapid decision-making and long-term goals during Furiosa’s early development.

South Korea positions itself for AI and inference growth

With strong software capabilities and semiconductor knowledge from homegrown firms like Samsung and SK Hynix, South Korea is putting a lot of emphasis on AI development. The government has made the development of AI a top priority, hoping to become a technological leader alongside China and the United States. The government of South Korea arranged for Nvidia to finalize a significant GPU supply deal, while OpenAI recently opened an office in Seoul.

During Furiosa’s beginning years, Paik frequently cited “Blitzscaling: The Lightning-Fast Path to Building Massively Valuable Companies,” a book popular in Silicon Valley. He used it to stress the importance of quick decisions and bold moves to dominate markets as an early entrant.

At Stanford’s respected Hot Chips conference in 2024, Paik introduced Furiosa’s RNGD chip during a keynote presentation, calling it an answer to what he termed “sustainable AI computing.” Paik shared information demonstrating the chip could operate Meta’s Llama large language model with power efficiency exceeding Nvidia’s top-tier chips by more than double.

“It was a moment where we felt we could really move forward with our chip with confidence,” Paik said.

Looking back now, Paik views his Achilles injury as a pivotal moment. “I think it could have been a blessing in disguise,” he said.

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