ai/” target=”_blank” rel=”noopener”>SiMa.aiA Silicon Valley-based startup that produces embedded machine learning system-on-chip (SoC) platforms, today announced that it has raised a $70 million extension funding round as it plans to bring its second-generation chipset , built specifically for multimodal generative ai processing. , to the market.
According to Gartner, the global market for ai-enabled chips is expected to increase ai-chips-revenue-to-reach-53-billion-dollars-in-2023″ target=”_blank” rel=”noopener”>more than double by 2027 to $119.4 billion compared to 2023. However, only a few players have started producing dedicated semiconductors for ai applications. Most of the prominent contenders initially focused on supporting ai in the cloud. However, various reports predicted significant growth in the edge ai market, meaning that the ai calculations processed by hardware are closer to the data collection source than in a centralized cloud. SiMa.ai, named after Seema, the Hindi word for “limit”, strives to take advantage of this shift by offering its cutting-edge ai SoC to organizations across industrial manufacturing, retail, aerospace, defence, agriculture and medical attention.
The San Jose-based startup, which targets the market segment between 5W and 25W of power usage, launched its first ML SoC to incorporate ai and ML through an integrated combination of software and hardware. This includes its proprietary chipset and no-code software called ai/palette-software/” target=”_blank” rel=”noopener”>Pallette. The combination has already been used by more than 50 companies around the world, Krishna Rangasayee, founder and CEO of SiMa.ai, told TechCrunch.
The startup touts that its current generation of ML SoC delivered the highest FPS/W results in the MLPerf benchmark across the closed-split, edge, and power categories of MLPerf Inference 4.0. However, the first generation chipset focused on classic computer vision.
As demand for GenAI grows, SiMa.ai will introduce its second-generation ML SoC in the first quarter of 2025 with an emphasis on providing its customers with multi-modal GenAI capability. The new SoC will be an “evolutionary change” from its predecessor with “some architectural tweaks” over the existing ML chipset, Rangasayee said. He added that the fundamental concepts would remain the same.
The new GenAI SoC would adapt to any framework, network, model and sensor, similar to the company's existing ML platform, and will also support any modality, including audio, voice, text and image. It would function as a single-edge platform for all ai across computer vision, transformers and multi-modal GenAI, the startup said.
“You can't predict the future, but you can pick the vector and say, hey, that's the vector I want to bet on. And I want to continue evolving around my vector. That is the approach we took architecturally,” Rangasayee said. “But fundamentally, we haven't moved away from or had to drastically change our architecture. This is also the benefit of us adopting a software-centric architecture that allows for greater flexibility and agility.”
SiMa.ai has Taiwan's TSMC as a manufacturing partner for its first and second generation ai chipsets and Arm Holdings as a supplier for its computing subsystem. The second-generation chipset will be based on TSMC's 6nm process technology and will include Synopsys EV74 embedded vision processors for pre- and post-processing in computer vision applications.
The startup considers traditional companies such as NXP, Texas Instruments, STMicro, Renaissance and Microchip technology and Nvidia, as well as ai chip startups such as Hailo, among the competition. However, it considers Nvidia its main competitor, as do other ai chip startups.
Rangasayee told TechCrunch that while Nvidia is “fantastic in the cloud,” it hasn't created a platform for the edge. He believes Nvidia lacks adequate software and power efficiency for cutting-edge ai. Similarly, he claimed that other startups building ai chipsets do not solve system problems and only offer machine learning acceleration.
“Among all our peers, Hailo has done a really good job. And it's not about us being better than them. But from our perspective, our value proposition is quite different,” he stated.
The founder went on to say that SiMa.ai offers higher performance and better energy efficiency than Hailo. He also said that SiMa.ai's system software is quite different and effective for GenAI.
“As long as we solve customer problems, and we're better at doing it than anyone else, we'll be in a good place,” he said.
SiMa.ai's new all-equity financing, led by Maverick Capital and featuring participation from Point72 and Jericho, expands on the startup's $30 million Series B round, initially announced in May 2022. Existing investors including Amplify Partners, Dell Technologies Capital, Fidelity Management and Lip -Bu Tan also participated in the additional investment. With this fundraising, the startup founded five years ago has raised a total of $270 million.
The company currently has 160 employees, 65 of whom are at its R&D center in Bengaluru, India. SiMa.ai plans to increase that workforce by adding new roles and expanding its R&D capacity. It also wants to develop a marketing team for Indian clients. Additionally, the startup plans to scale its customer support teams globally, starting with Korea and Japan and in Europe and the US.
“The computational intensity of generative ai has precipitated a paradigm shift in data center architecture. The next phase of this evolution will be the widespread adoption of ai at the edge. Just as the data center has been revolutionized, the edge computing landscape is poised for a complete transformation. SiMa.ai possesses the essential trifecta of a world-class team, cutting-edge technology and forward momentum, positioning it as a key player for clients navigating this tectonic shift. “We are excited to join forces with SiMa.ai to take advantage of this once-in-a-generation opportunity,” said Andrew Homan, senior managing director at Maverick Capital, in a statement.
