Core Viewpoint - FuriosaAI, a South Korean chip startup, aims to compete with Nvidia by leveraging its unique Tensor Contraction Processor (TCP) architecture to enhance AI performance and efficiency [2][3]. Group 1: Company Overview - FuriosaAI was founded in 2017 by June Paik, a former engineer at Samsung and AMD, with a vision for dedicated chips for deep learning workloads [2]. - The company launched its first-generation Neural Processing Unit (NPU) in 2021, manufactured by Samsung using a 14nm process, which performed well in MLPerf benchmarks [2]. Group 2: Product Development - The second-generation chip, RNGD (Renegade), is being developed over a three-year project initiated in 2021, focusing on generative AI and language models [3]. - RNGD is manufactured using TSMC's 5nm process, featuring 48GB of HBM3 memory, 1.5TB/s memory bandwidth, and 512 TFLOPS of FP8 performance with a maximum power consumption of 180W [3]. Group 3: System Integration - FuriosaAI is working on a complete system based on the RNGD card, the NXT RNGD server, which will include eight RNGD cards, totaling 384GB of HBM3 memory and 4 petaFLOPS of FP8 performance at a thermal design power (TDP) of 3kW [4]. - The NXT RNGD server aims to outperform traditional GPU-based systems, targeting the same market as Nvidia's H100 GPU [4]. Group 4: Performance Comparison - The Nvidia H100 GPU features 80GB of HBM2 memory, 2TB/s memory bandwidth, and 1513 TFLOPS peak performance, with a TDP of 350W for PCIe versions and up to 700W for SXM versions [5]. - FuriosaAI claims that RNGD's performance exceeds Nvidia's by three times when running large language models on a per-watt basis [5]. Group 5: Architectural Innovation - The TCP architecture is designed to minimize data movement, which is a significant energy consumer, by maximizing data reuse stored in on-chip memory [6]. - The architecture improves abstraction layers to overcome limitations of traditional GPU architectures, ensuring efficient data access and high throughput [7]. Group 6: Market Adoption and Client Engagement - FuriosaAI has gained traction with clients like LG AI Research, which reported that RNGD could deliver approximately 3.5 times the tokens per rack compared to previous GPU solutions [8]. - The company has attracted attention from major cloud computing firms, including Meta, which expressed interest in acquiring FuriosaAI [8]. Group 7: Future Plans and Funding - FuriosaAI completed a $125 million bridge financing round, bringing total funding to $246 million, and is focusing on ramping up RNGD production for global customer engagement by early 2026 [9].