A New Chip in Town: Extropic Seeks to Disrupt the Data Center Dominance with Thermodynamic Sampling Units (TSUs)
In a bid to challenge the likes of Nvidia, AMD, and Intel, startup Extropic has developed its first working chip, dubbed XTR-0, which harnesses thermodynamic electron fluctuations to model probabilities rather than traditional 1s and 0s. This exotic new approach promises energy efficiency that could be thousands of times better when scaled up.
The company's chips use probabilistic bits, or p-bits, which are limited in scale but demonstrate the potential of its novel computing method. In a paper posted to arXiv, Extropic lays out plans for a larger chip with 250,000 p-bits, dubbed Z-1, which could be used to create more efficient diffusion models for image and video generation and robot guidance.
Extropic's approach is being hailed as transformative by some industry experts, who see it as a game-changer for energy efficiency and density in AI workloads. However, the company's CEO, Guillaume Verdon, says that ignoring the energy requirements of building massive AI data centers ignores potential risks.
The startup has partnered with several key players, including Atmo, which is using its chips to forecast weather conditions more efficiently. With billions of dollars being poured into building data centers, Extropic is seeking to offer a far less costly alternative, one that could make all the difference in the quest for sustainable computing.
In essence, Extropic's TSUs aim to rethink how we process information and build the next generation of computing hardware β one that prioritizes efficiency over traditional performance metrics. With its XTR-0 chip now live, the company is poised to challenge the status quo and make a significant impact on the world of AI and data processing.
				
			In a bid to challenge the likes of Nvidia, AMD, and Intel, startup Extropic has developed its first working chip, dubbed XTR-0, which harnesses thermodynamic electron fluctuations to model probabilities rather than traditional 1s and 0s. This exotic new approach promises energy efficiency that could be thousands of times better when scaled up.
The company's chips use probabilistic bits, or p-bits, which are limited in scale but demonstrate the potential of its novel computing method. In a paper posted to arXiv, Extropic lays out plans for a larger chip with 250,000 p-bits, dubbed Z-1, which could be used to create more efficient diffusion models for image and video generation and robot guidance.
Extropic's approach is being hailed as transformative by some industry experts, who see it as a game-changer for energy efficiency and density in AI workloads. However, the company's CEO, Guillaume Verdon, says that ignoring the energy requirements of building massive AI data centers ignores potential risks.
The startup has partnered with several key players, including Atmo, which is using its chips to forecast weather conditions more efficiently. With billions of dollars being poured into building data centers, Extropic is seeking to offer a far less costly alternative, one that could make all the difference in the quest for sustainable computing.
In essence, Extropic's TSUs aim to rethink how we process information and build the next generation of computing hardware β one that prioritizes efficiency over traditional performance metrics. With its XTR-0 chip now live, the company is poised to challenge the status quo and make a significant impact on the world of AI and data processing.