In 2022, Etched, an AI chip startup established by three Harvard dropouts, has successfully completed a $300 million Series C funding round with a valuation of $10.3 billion, according to co-founder and COO Robert Wachen in a conversation with TechCrunch.  

The funding round was spearheaded by Sequoia, joined by Andreessen Horowitz, SK Hynix, Jane Street, Diffusion Capital, and several earlier investors. Notable backers include figures such as Peter Thiel, Andrej Karpathy, Dylan Field, Amjad Masad, among others. 

Back in December, Etched had a valuation of $5 billion after raising a $500 million round, indicating it has doubled its worth in roughly seven months. The firm claims this marks the highest valuation achieved for a Sequoia-led Series C. Last month, Etched revealed it had efficiently produced its proprietary chips, with its initial full systems currently being tested by clients, alongside already securing $1 billion in orders. 

Etched emerged during a period when conceptualizing a chip tailored specifically for AI models utilizing transformer technology (the backbone of most contemporary AI systems, such as ChatGPT and Claude) was deemed extraordinary, if not absurd. The startup continues to challenge the notion that its offerings — marketed as complete systems rather than standalone chips — are limited to chips intended for specific LLMs.  

This is inaccurate, Wachen clarifies. The systems are capable of operating any AI model, including Mixture of Experts models like DeepSeek and Qwen — a structure that distributes tasks among specialized sub-models instead of depending on a singular, large model — together with non-transformer types like Mamba, which is built on a different fundamental architecture known as a state-space model. (Interestingly, the concept of embedding parts of a particular AI model directly into silicon to enhance performance is no longer regarded as far-fetched. Google is reportedly exploring a similar idea with its Frozen v2 chip for Gemini.)

Nonetheless, Etched’s current distinction lies in its development of two new components from the ground up to accelerate inference — the computing operation that occurs once a user inputs a prompt.  

“Inference consists of two stages,” Wachen articulates, “prefill and decode.” The “prefill phase” focuses on comprehending the prompt, including its context. It is mathematically intensive and requires considerable computational power. The “decode” stage produces the output tokens (the direct answer that the user observes). While it demands less computation, it requires vast amounts of memory. 

Etched has developed a prefill chip that operates “drastically” faster, he assures, “by functioning at significantly lower voltage than any other AI chip. We refer to this as low-voltage inference.” Reduced voltage generates less heat, permitting the chip to accommodate more transistors.  

In terms of the decode process, Etched has designed an innovative type of memory and “interconnect technology that we term cluster-scale memory. This enables numerous chips to connect collectively and utilize a shared memory pool at remarkably high speed and low latency,” he claims. The outcome, as Etched promises, is elevated speed along with reduced costs.

Having launched before most of the tech sector (aside from Nvidia) grasped the specialized computational requirements of AI, the founders, CEO Gavin Uberti, Wachen, and Chris Zhu, encountered numerous skeptics who remained doubtful even after the company disclosed the successful production of its first batch of silicon by TSMC.

Much of this skepticism stems from the limited number of individuals who have had access to the systems. To date, access has been restricted to investors and initial customers. Indeed, this is how Etched attracted its group of renowned investors initially — by offering them private demonstrations in their office.

“Andrej Karpathy from Anthropic, Noam Brown from OpenAI, Geoffrey Hinton, along with all the investors in this funding round — these individuals all actually tried the hardware and are very enthusiastic about it,” Wachen states.  

Nevertheless, the journey has been challenging, and more obstacles lie ahead before the rack systems can be mass-produced and distributed. The trio is renowned for dropping out of Harvard to start Etched, without a clear understanding of how to secure funds (let alone the large amounts required) or how to hire effectively. 

“We had no clue how challenging it would be,” Wachen remarks. “I believe we still need to remain humbled by what it will demand to actually scale.” 

Wachen recalls arriving in the Bay Area after informing his parents of his decision to leave school for a startup, with no office or housing arranged. He was forced to sleep on the floor of a friend’s unfurnished residence. 

“I recall staying at my friend’s house, which was about to be sold, using a towel as a blanket,” he chuckles.  The founders ultimately set up the necessary servers for running the chip-design tools in an early employee’s garage, and “every time they needed to be rebooted, he would call his wife, and she would go and hit the reboot button.” 

Now, there are 400 employees thriving in an office, and Etched manages a 2 megawatt data center there. Furthermore, it has just opened a brand-new 80,000 square-foot, 10MW facility in Milpitas, situated not far from its primary San Jose office.

“Today, we are processing tokens in our lab, collaborating with some of the largest AI companies in the world,” he shares. 

Wachen also has a blanket now, along with a mattress “and even a pillow. Multiple pillows,” he jokes.  

More significantly, he and his co-founders have never allowed the naysayers to deter them. “It has come a long distance. The world is markedly different. However, I believe that when you truly believe something is achievable, and you dedicate yourself to it over time, you can accomplish it.”

Note: This narrative was updated to add a reference to the new 10MW facility.