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According to the Financial Times on August 28, Nvidia's competitors are taking action to break Nvidia's monopoly in the artificial intelligence chip market. They have raised hundreds of millions of dollars and launched new products in the hope of sharing the fruits of the booming development of artificial intelligence technology.

A host of smaller companies including Cerebras, d-Matrix and Groq are hoping to grab a piece of the multibillion-dollar AI chip market from Nvidia, which has so far dominated the first wave of investment with its graphics processing units (GPUs).

They expect that as chatbots and other generative AI applications become more popular, the demand for AI inference—the computing power needed for models like OpenAI’s ChatGPT and Google’s Gemini to generate responses to queries—will grow exponentially.

Nvidia’s Hopper GPUs are ideally suited to the resource-intensive task of training top AI models and have become one of the world’s hottest commodities.

Cerebras, d-Matrix and Groq are focused on designing cheaper, more specialized chips for running AI models.

On Tuesday, Cerebras announced the launch of its new Cerebras Inference Platform based on the CS-3 chip, which is about the size of a dinner plate.

Cerebras claims its solution is 20 times faster at AI inference than Nvidia’s current-generation Hopper chip at a fraction of the price, citing tests conducted by benchmarking provider Artificial Analysis.

Cerebras CEO Andrew Feldman told the Financial Times: "The way to beat an 800-pound gorilla is to bring a better product to market. In my experience, the better product usually wins, and we have already taken important customers away from Nvidia."

Rather than using a separate high-bandwidth memory chip like Nvidia uses, the CS-3 chip offers an alternative architecture that builds the memory directly into the chip wafer.

Feldman said that limitations on memory bandwidth are a fundamental constraint on the speed of inference on AI chips. Combining logic and memory into one large chip can achieve results that are orders of magnitude faster, he said.

d-Matrix, founded by Sid Sheth in 2019, has also launched a new round of funding less than a year after raising $110 million in a Series B round led by Singapore state fund Temasek.

Sheth said the company plans to raise $200 million or more later this year or early next. d-Matrix is ​​in the early stages of the fundraising process and said the final amount of money raised may change.

d-Matrix plans to fully launch its own chip platform Corsair by the end of this year.

Sheth said the company is pairing its products with open software such as Triton, which competes with Nvidia’s Cuda, a widely used software platform that gives developers tools to build AI applications and optimize the performance of its chips.

Nvidia’s largest customers support the use of open software such as Triton. “Application developers don’t like being locked into one specific tool,” Sheth said. “People are realizing that Nvidia has a monopoly on Cuda for training.”

Groq, another AI inference competitor led by former founding members of Google’s Tensor Processing Unit team, raised $640 million this month from investors led by BlackRock Private Equity Partners at a valuation of $2.8 billion.

Despite the hype surrounding the sector, semiconductor startups face challenges breaking into the market, one venture capitalist warned.

SoftBank bought chipmaker Graphcore last month for just over $600 million, according to people familiar with the matter, less than the roughly $700 million in venture capital the company had raised since its founding in 2016.

Groq and Cerebras were also founded in 2016.

“Public investors have been eager to find and back the next Nvidia,” said Peter Hébert, co-founder and managing partner of venture capital firm Lux Capital. “This is not just about chasing the latest trend. The momentum has also benefited several venture-funded chip startups that have been working for nearly a decade.”