Black Semiconductor became the latest high-profile chip startup to raise about $275 million last week, mostly from the German government, for its next-generation chip technology.
It’s just the latest sign that one of the most fundamental technologies is once again catching the attention of investors around the world, thanks in large part to AI, and that chip startups are poised to raise huge amounts of money.
Global venture funding for semiconductor chips appears set to bounce back well this year after a forgettable 2023. So far this year, venture capital-backed semiconductor startups have raised roughly $5.3 billion across just 175 deals, according to Crunchbase data.
Those numbers are well ahead of last year’s pace, when such startups raised just under $8.8 billion across 490 deals. In 2022, semiconductor startups are set to raise roughly $10.9 billion across 447 deals.
More big rounds may be on the way, after smartphone maker Samsung was reported last week to be leading a funding round of at least $300 million in Toronto-based AI chip startup Tenstorrent.
The semiconductor boom in the United States
U.S. startups are playing a key role in the funding surge: Domestic startups raised roughly the same amount (about $1.2 billion) compared to all of last year, in roughly the same number of deals (24 vs. 22), according to Crunchbase.
It’s important to note that this figure is heavily helped by PsiQuantum, which focuses on semiconductor process development and integrated photonic devices and systems. The company secured a $620 million funding package from the Australian Federal and Queensland governments this spring to build a quantum computer in Brisbane, Australia. The round is actually a combination of equity, grants, and loans.
Even without this round, U.S. startups would have surpassed last year’s pace. While many of the largest rounds this year went to Chinese chipmakers, including ChangXin Memory Technologies, Unisoc and AaltoSemi, there were also significant funding rounds for U.S.-based semiconductor startups, including:
- In March, optical interconnect startup Celestial AI raised a whopping $175 million in Series C funding led by Thomas Tull’s US Innovative Technology Fund. Celestial’s photonic fabric platform decouples compute and memory to help make pervasive AI processing faster and more energy-efficient.
- San Jose, California-based Recogni, which develops AI inference chips for both generative AI and the automotive industry, raised $102 million in Series C funding in February, co-led by Celesta Capital and GreatPoint Ventures.
- In March, Santa Clara, Calif.-based chiplet interconnect developer Eliyan raised $60 million in a funding round co-led by Samsung Catalyst Fund and Tiger Global Management.
“Semiconductor used to be a rare word in Silicon Valley, but now it’s sexy,” says Sriram Viswanathan, founder and managing partner at San Francisco-based Celesta Capital, whose deep-tech portfolio includes Palo Alto, Calif.-based SambaNova Systems in addition to its Recogni investment.
AI Effects
Of course, the renewed investor interest is due to a key factor driving much of the technology world: AI.
Artificial intelligence is the driving force behind semiconductor giant Nvidia’s rise to a company now worth more than $3 trillion. Astera Labs, which provides data and memory connectivity solutions to the world’s largest chipmakers, including Intel and Taiwan Semiconductor Manufacturing Co., is trading below its peak but still well above its March IPO price, which was seen as a pioneering proposition for both the semiconductor and AI industries.
Both of these companies demonstrate the strong public investor interest in the chip market, which typically translates to venture capital interest in the private markets.
“While AI’s commercial viability is yet to be fully proven, the ‘FOMO’ of the AI ​​race is driving a lot of hot money into the value chain, from AI applications to data infrastructure to semiconductors,” said Lorin Ng, founding partner at New York-based Recharge Capital, which invests in wireless-device chip maker Airoha Technology.
“Large-scale AI applications often require retooling or building new infrastructure, so there is strong cyclical demand for semiconductors at the moment,” Gu added.
Gu said while competition for investment in the sector is intensifying, it is also becoming more creative in terms of fundraising, with more hybrid deals and investors conducting more in-depth analysis of industry risks and capital expenditures.
Viswanathan added that the AI-related semiconductor and hardware sector has been flooded with capital recently and is somewhat “overinflated.”
Viswanathan said that despite the influx of money and investors into the space, opportunities exist at the silicon and hardware level, including from startups looking to make AI inference — a model’s ability to use new data to make predictions and draw conclusions — more efficient.
But it’s important to remember that chip manufacturing is an expensive business and an industry dominated by a few big players like Nvidia.
Those in the AI ​​field may be looking for alternatives to Nvidia, but this could be a tough market for startups to navigate.
But for now, at least, investors seem willing to take that risk.
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Illustration: Dom Guzman
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