and led the round. ’ , . and also joined the funding for Tenstorrent, which aims to rival semiconductor giant in the creation of chips for AI., , , and other investors also participated in the deal.

Santa Clara, California-based Tenstorrent was founded in 2016 and the company has since raised more than $1 billion, .

Keller, one of the most acclaimed engineers in the semiconductor industry, the company in 2021 as president and chief technology officer, and was named CEO in early 2023. He had previously worked at , , — where he led the development of the A4 and A5 processors, which powered the iPhone 4 — and , where he was the lead architect of its K8 microarchitecture.

Bloomberg that Tenstorrent’s latest funding was $700 million total and its post-money valuation is about $2.6 billion.

Tenstorrent it plans to use the new capital to “build out open-source AI software stacks, hire developers, expand its global development and design centers, and build systems and clouds for AI developers.”

The company is just the latest startup at the intersection of chips and AI to raise big from investors this year. Others include:

• In October, , a startup that uses light to link chips together and to do calculations for the deep learning necessary for AI, locked up a $400 million Series D led by new investor at a $4.4 billion valuation.
• raised nearly $275 million — mainly from the German government — in July.
• In March, optical interconnectivity startup raised a $175 million Series C led by ’s . Celestial’s photonic fabric platform helps separate compute and memory, making processing extensive AI faster and more energy-efficient.
• San Francisco-based locked up a $120 million round led by and in June.
• That was after Israel-based AI chipmaker locked up a $120 million extension of its $136 million Series C in April. The new funding round was led by current and new investors including , and others.
• In February, San Jose, California-based , which is developing its AI inference chip for both the generative AI and automotive industries, raised a $102 million Series C co-led by and .
• Santa Clara, California-based , a developer of a laser manufacturing technology platform for the semiconductor industry, raised an $80 million Series B led by in July.
• Also in July, San Jose, California-based raised $75 million in an equity round co-led by the and .

In March, AI chip startup became one of the few venture-backed startups to go public this year. The company raised $713 million in an IPO on the when its shares priced at $36 each. The company has been trading above the $100-mark lately.

— Chris Metinko contributed to this report.

Related Crunchbase Pro list:

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• Hailo Raises $120M In Latest Sign Of Chip Investing Frenzy
• Astera Shares Soar Following IPO
• DreamBig Latest Chip Startup To Go Big — Raises $75M 

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This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding rounds here.

Just as the holiday season begins, a sleighful of companies unveiled large funding rounds. Of course, it was led by two well-known AI startups — including , which had its second massive haul of cash in just six months.

1. , $5B, artificial intelligence: Generative AI startup xAI raised $5 billion in a funding round valuing it at $50 billion, reported. The new round includes investment from the , , and . It was just in May ’s startup officially announced its long-awaited fundraise — making it the second-most-valuable generative AI company in the world behind only competitor . The $6 billion round valued the company at $24 billion post money.

2. , $4B, artificial intelligence: has agreed to invest another $4 billion in AI startup Anthropic — a rival with its AI assistant Claude. Last fall Amazon agreed to invest up to $4 billion in Anthropic — giving the Seattle-based e-commerce and cloud titan a minority stake in Anthropic. The immediate investment was  $1.25 billion, with the remaining $2.75 billion in funding coming earlier this year. That deal included Anthropic naming its primary cloud provider, as well as using AWS Trainium and Inferentia chips to build, train and deploy its models. This new investment means Amazon will have invested $8 billion into Antropic, retaining its minority stake in the startup, per an Anthropic .

3. , $800M, IT management: LogicMonitor, which provides IT observability and monitoring, took in $800 million in new equity and debt from an investor consortium that includes , and others. The deal is part of selling a minority stake in the company, which is now valued at about $2.4 billion. The IT infrastructure company will use the fresh cash for M&A activities and entering new markets globally. Vista bought LogicMonitor in May 2018 for about $415 million.

4. , $300M, cybersecurity: After raising a $300 million Series C led by at a $1.4 billion valuation in April, data security startup Cyera closed another $300 million windfall at more than twice its previous valuation. The New York-based company announced a $300 million Series D led by and at a $3 billion valuation. While a cybersecurity company, Cyera is certainly riding the AI wave. The startup has an AI-powered data security platform that helps security teams at companies understand what data they have and how it’s used, as well as how to secure it across a complex digital landscape. Of course, the reliance on data has only become stronger as companies drive AI initiatives. Founded in 2021, Cyera has raised $760 million to date, per the company.

5. , $175M, enterprise software: Kong, a developer of cloud API technologies, closed $175 million in an up-round Series E led by and that valued the company at $2 billion. The round was a mix of primary and secondary transactions, with no exact amount given for the primary investment. The funding comes as companies are being overwhelmed with more APIs as AI business applications grow. Founded in 2009, Kong has raised $345 million, per the San Francisco-based company.

6. , $130M, biotech: It was just in June that Enveda Biosciences first landed on this list, after raising a $55 million round that included as an investor. The Boulder, Colorado-based startup is back this week after raising a $130 million Series C funding round led by and . The company uses AI-powered tools to identify a wide range of molecules produced by living organisms to create medicines. Founded in 2019, Enveda has raised $360 million, .

7. , $125M, customer service: AI for contact centers is big right now and Palo Alto, California-based Cresta is the latest startup to raise massive money. The company locked up a $125 million Series D led by new investors and . The Cresta platform gives customers real-time insights and behavioral best practices to help human agents, while also automating mundane tasks using virtual agents. Founded in 2017, Cresta says it has raised more than $270 million.

8. , $115M, semiconductor: AI networking chip startup raised a $115 million Series C led by as it inches closer to its newest chip release early next year. The round comes just about 14 months after the Mountain View, California-based firm closed a $125 million Series B led by that also included investment from . The new Series C investors include some of the biggest names in the chip world: and . Enfabrica also announced its new “groundbreaking” ACF SuperNIC chip. The startup’s networking infrastructure helps tie AI chips together — allowing for the consistent flow of data needed for modern AI workloads.

9. , $100M, sports: Los Angeles-based League One Volleyball, which is set to start a pro volleyball league early next year, raised $100 million in a deal led by . Founded in 2019, the company has raised $160 million, .

10. , $75M, enterprise software: San Jose, California-based Spectro Cloud, which allows customers to deploy and manage Kubernetes in production, completed a $75 million Series C funding led by the growth equity arm at . Founded in 2019, the company has raised $143 million, .

Big global deals

The biggest round outside the states came from across the pond.

• London-based , a commercial platform for the travel and hospitality industry, raised a $370 million Series C.

Methodology

We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the seven-day period of Nov. 16 to Nov. 22. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

Illustration:

It was just the latest sign of chip startups being able to raise big money as once again one of the most foundational technologies grab investors’ attention around the world, mainly thanks to AI.

Global venture funding to semiconductor chips appears well on its way to bouncing back this year after a forgettable 2023. Thus far this year, VC-backed chip startups have raised nearly $5.3 billion in just 175 deals, per Crunchbase .

Those numbers are well ahead of the pace from last year, when such startups saw less than $8.8 billion in 490 deals. In 2022, chip startups locked up almost $10.9 billion in 447 deals.

More big rounds could be in the way, as it was last week that smartphone-maker is leading a round of at least $300 million for Toronto-based AI chip startup .

US chip boom

U.S. startups are playing a key role in the surge of funding. Domestic startups have raised almost the same amount of money — about $1.2 billion — in nearly the same number of deals — 24 to 22 — compared to all of last year, per .

It is important to note that number is greatly helped out by , which focuses on semiconductor process development and integrated photonic devices and systems. The company landed a financial package of $620 million from the Australian Commonwealth and governments this spring to build a quantum computer at a location in Brisbane, Australia. The round is actually a mix of equity, grants and loans.

Even without that round, U.S. startups would be ahead of last year’s pace. While many of the biggest rounds this year went to Chinese chipmakers like , and , some large financings also went to U.S.-based semiconductor startups, including:

• In March, optical interconnectivity startup raised a massive $175 million Series C led by ’s . Celestial’s photonic fabric platform helps separate compute and memory, making processing extensive AI faster and more energy-efficient.
• In February, San Jose, California-based , which is developing its AI inference chip for both the generative AI and automotive industries, raised a $102 million Series C co-led by and .
• In March, Santa Clara, California-based , a chiplet interconnect developer, raised a $60 million round co-led by and .

“Semi used to be a four-letter word in the Valley, but now it’s sexy,” said , founding managing partner at San Francisco-based . Along with its Recogni investment, the deep-tech firm’s portfolio includes Palo Alto, California-based .

AI effect

Of course what is leading to this renewed investor interest is the key driver of so many things in the tech world — AI.

Artificial intelligence is the driving reason chip giant is now a $3 trillion-plus company. And while shares of — which provides data and memory connectivity solutions for some of the biggest chipmakers in the world, including and — are off their highs, they are still well above their IPO price from March. Astera’s IPO, in particular, was seen as a bellwether offering for both the semiconductor and AI industries.

Both those companies show there is significant public investor interest in the chip market — and that usually translates to VC interest in the private markets.

“While the full promise of AI commercialization has not been fully evidenced, the ‘FOMO’ of (the) AI race is pushing a lot of hot money into the value chain from AI applications to data infrastructure to semiconductors,” said , founding partner at New York-based , an investor in wireless-device chip manufacturer .

“Given that at-scale AI application often requires retooling or new build of infrastructure, there is a strong cyclical demand for semis at the moment,” Gu added.

While the space has become more competitive to invest in, it also has become more creative in terms of financing, with more hybrid deals and investors analyzing the risks and capex in more granular details for the industry, Gu said.

Viswanathan added that the semi and hardware space as it relates to AI has been inundated with capital of late and is somewhat “over-inflated.”

Despite the influx of money and investors in the space, Viswanathan said there are opportunities at the silicon and hardware level. That includes startups looking to make AI inference — a model’s ability to use new data to make predictions and draw conclusions — more efficient.

However, it is important to remember chipmaking can be an expensive proposition and it is an industry dominated by a few big players like Nvidia.

While those in the AI space may be looking for an alternative to Nvidia, it can be a difficult market for any startups to make headway.

Nevertheless, it seems at least for now investors are willing to take that risk.

Related Crunchbase Pro lists:

Related reading:

• Astera Shares Soar Following IPO
• Chip Startup Celestial AI Lands Massive $175M Series C
• Generative AI Chip Designer Recogni Locks Up $102M

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At a certain level of computational complexity, regular central processing units don’t cut it. They’ll do the math just fine, but they’ll take a long time to do it. Graphics cards were designed for massively parallel computing operations, like rendering and driving the multiplying number of pixels on our ever-denser visual displays; and it just so happens that that architecture is well-suited to doing machine learning math quickly.

But there are plenty of applications where running a bunch of graphics processing units (GPU) in a data center is not practical. Take an autonomous vehicle for example: It doesn’t make sense to pipe all the data streaming off the onboard cameras and LIDAR sensors up to a cloud service, wait for it to process, and then get piped back into a car’s onboard computer. At 60 miles and hour, that kind of latency could be lethal.

As the world becomes more data-driven and our tech uses inference to be more responsive, a new generation of computer chips is required to make all the math-magic happen. At a certain scale of computational complexity, or in situations where electrical consumption has to be kept to a minimum, GPUs don’t cut it either.

Headquartered in Tel Aviv, Israel, is one of several companies vying for its spot in the competitive market for specialized artificial intelligence chips built for computing on the edge: automotive applications, mobile devices, AI-augmented home devices and industrial use cases.

Today the company announced that it’s raised $60 million in Series B funding. The round was led by existing backers but saw participation from new strategic investors including the venture arm of robotics and automation company , Japanese IT conglomerate and London-based VC .

The company says that its new funding will “bolster the ongoing global rollout of its breakthrough Hailo-8 Deep Learning chip and to reach new markets and industries worldwide.”

Hailo says its chip is capable of up to 26 trillion operations per second while drawing less than 5 watts at full utilization. supports popular machine learning frameworks like and and meets several compliance standards for automotive applications.

According to the company, the chip’s “Structure-Defined Dataflow Architecture translates into higher performance, lower power, and minimal latency, enabling more privacy and better performance for smart devices operating at the edge, including partially autonomous vehicles, smart cameras, smartphones, drones and AR/VR platforms.”

“This immense vote of confidence from our new strategic and financial investors, along with existing ones, is a testimony to our breakthrough innovation and market potential,” said , CEO and co-founder of Hailo. “The new funding will help us expedite the deployment of new levels of edge computing capabilities in smart devices and intelligent industries around the world, including areas such as mobility, smart cities, industrial automation, smart retail and beyond.”

Since its inception in February 2017, the company has raised $88 million in total funding, inclusive of the round announced today. In January 2019, the company closed led by Chinese venture firm . No additional details about the company’s revenue or valuation was disclosed.

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At sufficient scale, the computational complexity of machine learning model training overwhelms general-purpose CPUs. The work will get done; it might just take a long time. Data scientists and machine learning researchers have long used graphics processing units (GPUs) because of their highly parallelized architecture and relatively abundant on-chip memory available.

But as industry and research groups alike seek more efficiency and need to accommodate ever-larger quantities of information, more specialized computing hardware is required for the task.

Headquartered in Bristol, U.K., is in the business of producing silicon purpose-built for munching through machine-learning math at high rates of speed and using less electricity than GPUs. Benchmarks for Graphcore’s (IPU) that it offers notably less latency and higher computational throughput, and uses less power than GPUs.

The company that it raised an additional $150 million in fresh investor capital in an extension of its Series D round. The extension was led by ; new investors and joined in as well. The deal also saw participation from a number of prior investors. The was closed in December 2018, netting the company $200 million.

The Series D extension values Graphcore at $1.95 billion, according to the company. Taken together, the company has raised $460 million, according to Crunchbase data. The company’s shareholders include the likes of , , , various associated with , , and , among .

In a press release provided to Crunchbase News by the company, Graphcore highlighted a number of milestones from 2019. In partnership with strategic investor Dell Technologies, the companies co-developed and launched the DSS8440, a production-ready server built around Graphcore’s IPUs. Alongside Microsoft, another strategic investor, the company launched the Microsoft Azure IPU-Cloud service, as well as the IPU-Bare Metal Cloud service it launched in partnership with . The company’s publicly announced customers include Microsoft, , Carmot Capital, and European search engine company .

The company says the new round brings its cash reserves up to $300 million. Graphcore has plotted for itself an ambitious growth plan. According to its press release, the company has devoted significant resources to research and development efforts. The company doubled headcount in its Bristol headquarters, as well as its engineering center in Oslo, Norway. It says its sales and support office in Palo Alto, California also saw similar up-scaling in 2019. The company also opened a new sales, support and engineering office in Beijing, alongside an engineering center in Cambridge, U.K., and an operations facility in Taiwan.

“Demand for our Intelligence Processor Unit products is increasing at existing and new customers and the outlook for our business in Fiscal 2020 is extremely positive. The major investments that we have made during 2018 and 2019 will help us to meet this strong demand by extending the capabilities of our technology and ecosystem, and will support long-term revenue growth and returns for our investors,” said Graphcore CEO Nigel Toon in a statement.

The company declined to answer questions from Crunchbase News about its revenue and profitability, whether it has its own fabrication facilities, what the company’s future exit prospects might look like and whether it may be affected by Brexit or the emerging SARS-CoV-2 virus situation in Asia.

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