Sohu: Why Etched Made the Biggest Bet in AI to Defeat nVidia

The video discusses etched’s Soo chip, a specialized AI hardware designed for running inference on Transformer models, claiming to outperform Nvidia’s latest GPUs by handling over 500,000 tokens per second. Etched’s strategic focus on Transformers and specialized hardware aims to simplify software, maximize performance, and potentially disrupt the dominance of Nvidia in the AI hardware space.

In the video, the focus is on the advancements in AI hardware, specifically with the emergence of etched and their new chip called Soo. Etched has made a big bet on specialized AI hardware, particularly geared towards Transformer models, which are at the core of the current AI revolution. The video discusses how optimizing Transformers for speed and token processing capacity has become a crucial question in the industry, with multiple startups and companies working on solutions. Nvidia has been a dominant force in AI hardware, but etched is positioning itself as a significant competitor by specializing in Transformers and claiming to outperform Nvidia’s latest GPUs.

Etched’s Soo chip is designed exclusively for running inference on Transformer models, offering a significant performance boost compared to Nvidia GPUs. The chip is capable of handling over 500,000 tokens per second, making it faster than Nvidia’s latest offerings like the h100 and b200. By focusing solely on Transformers, etched aims to simplify the software and maximize performance, leveraging the widespread use of Transformer models in AI applications. The company’s approach highlights the importance of specialized hardware for training and running large AI models efficiently.

The video delves into the technical aspects of etched’s Soo chip, emphasizing its superior performance metrics, such as being 20 times faster than equivalent Nvidia servers. Etched’s strategy of betting on Transformers as the future of AI models and developing specialized hardware and software aligns with the industry trend towards custom chips for specific AI tasks. The discussion also touches on the scalability challenges in AI model training and the potential for custom chips like Soo to surpass general-purpose GPUs in efficiency and performance.

Additionally, the video addresses the competitive landscape in AI hardware, comparing etched’s Soo chip with existing offerings from Nvidia, AMD, Google, and other players in the market. The focus on specialized AI chips, such as Asics optimized for Transformers, signals a shift towards more efficient and powerful hardware solutions tailored for specific AI tasks. Etched’s partnership with TSMC for production and supply chain readiness indicates a serious commitment to bringing their Soo chip to market and potentially disrupting the current dominance of Nvidia in the AI hardware space.

Overall, the video paints a picture of etched’s Soo chip as a game-changer in the AI hardware industry, offering significant performance advantages over existing solutions. By specializing in Transformers and developing custom hardware and software, etched aims to provide a more efficient and scalable alternative to traditional GPUs for AI model training and inference. The video underscores the importance of advancements in AI hardware, particularly in optimizing performance for specific AI tasks like Transformers, and suggests that chips like Soo could potentially reshape the landscape of AI hardware in the coming years.