Etched’s Market Value Surges to $21 Billion Within Just One Month

Etched announced on Tuesday that it has secured another $700 million in funding, bringing its total valuation to $21 billion. The round was led by Jane Street, following the investment firm’s earlier testing and acquisition of the startup’s AI hardware.
Even by the standards of the AI industry, this rapid increase in valuation is particularly impressive. The company was valued at $5 billion back in December, and it raised $300 million in its Series C funding at a valuation of $10.3 billion in July. Just one month later, investors have doubled its valuation to $21 billion, an increase of nearly $11 billion.
Etched delivers its AI technologies as complete systems, which it refers to as “frontier inference clusters.” For comparison, its competitor Nvidia labels its similar systems as AI factories.
Co-founder and COO Robert Wachen told TechCrunch that investors are so enthusiastic because Etched has developed two entirely new components from scratch to accelerate inference — the computational process that occurs after a user submits a prompt.
“Inference takes place in two distinct stages,” Wachen explained, “prefill and decode.” During the mathematically intensive “prefill phase,” the system must interpret the prompt along with its context. In the memory-intensive “decode” phase, the system generates output tokens, which represent the actual response displayed to the user.
Etched has created a prefill chip that operates at low voltage, enabling it to incorporate more transistors without encountering the typical heat issues associated with other high-end AI chips. This design allows it to process more tokens more quickly. The company has also developed a new type of memory and an interconnect system for the decode process, which it calls cluster-scale memory.
“This architecture allows multiple chips to connect together and share a single memory pool, all at extremely high speeds with very low latency,” Wachen said. As a result, Etched claims its solutions offer both higher performance and reduced costs.
The company is still working to overcome the misconception that originated in its early days, when it was believed to embed specific models directly into its chips. While that was initially its goal, it is no longer the case — Etched’s systems are now capable of running any frontier model.
In the blog post announcing the latest funding round, investment firm Jane Street stated, “We conducted tests on the chip and are satisfied with the initial results. Etched’s unique approach to inference provides the precision required to handle our most demanding workloads. We are also excited to have our own deployment of these systems in our datacenter.”
Other investors in Etched include Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, Peter Thiel, Tiger Global, Bain Capital Ventures, Neo, Stripes, Primary, Positive Sum, Diffusion, Argo, and Blackstone.
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Etched announced on Tuesday that it has secured another $700 million in funding, bringing its total valuation to $21 billion. The round was led by Jane Street, following the investment firm’s earlier testing and acquisition of the startup’s AI hardware.
Even by the standards of the AI industry, this rapid increase in valuation is particularly impressive. The company was valued at $5 billion back in December, and it raised $300 million in its Series C funding at a valuation of $10.3 billion in July. Just one month later, investors have doubled its valuation to $21 billion, an increase of nearly $11 billion.
Etched delivers its AI technologies as complete systems, which it refers to as “frontier inference clusters.” For comparison, its competitor Nvidia labels its similar systems as AI factories.
Co-founder and COO Robert Wachen told TechCrunch that investors are so enthusiastic because Etched has developed two entirely new components from scratch to accelerate inference — the computational process that occurs after a user submits a prompt.
“Inference takes place in two distinct stages,” Wachen explained, “prefill and decode.” During the mathematically intensive “prefill phase,” the system must interpret the prompt along with its context. In the memory-intensive “decode” phase, the system generates output tokens, which represent the actual response displayed to the user.
Etched has created a prefill chip that operates at low voltage, enabling it to incorporate more transistors without encountering the typical heat issues associated with other high-end AI chips. This design allows it to process more tokens more quickly. The company has also developed a new type of memory and an interconnect system for the decode process, which it calls cluster-scale memory.
“This architecture allows multiple chips to connect together and share a single memory pool, all at extremely high speeds with very low latency,” Wachen said. As a result, Etched claims its solutions offer both higher performance and reduced costs.
The company is still working to overcome the misconception that originated in its early days, when it was believed to embed specific models directly into its chips. While that was initially its goal, it is no longer the case — Etched’s systems are now capable of running any frontier model.
In the blog post announcing the latest funding round, investment firm Jane Street stated, “We conducted tests on the chip and are satisfied with the initial results. Etched’s unique approach to inference provides the precision required to handle our most demanding workloads. We are also excited to have our own deployment of these systems in our datacenter.”
Other investors in Etched include Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, Peter Thiel, Tiger Global, Bain Capital Ventures, Neo, Stripes, Primary, Positive Sum, Diffusion, Argo, and Blackstone.
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