The computer chip industry over the last couple of decades has seen its innovation stem from just a few top players like Intel, AMD, NVIDIA, and Qualcomm. In this same time span, the VC industry has shown waning interest in start-up companies that made computer chips.
copyright by insidebigdata.com
The risk was just too great; how could a start-up compete with a behemoth like Intel which made the CPUs that operated more than 80% of the world’s PCs? In areas that that Intel wasn’t the dominate force, companies like Qualcomm and NVIDIA were a force for the smartphone and gaming markets.
The recent resurgence of the field of artificial intelligence (AI) has upended this status quo. It turns out that AI benefits from specific types of processors that perform operations in parallel, and this fact opens up tremendous opportunities for newcomers. The question is – are we seeing the start of a Cambrian Explosion of start-up companies designing specialized AI chips? If so, the explosion would be akin to the sudden proliferation of PC and hard-drive makers in the 1980s. While many of these companies are small, and not all will survive, they may have the power to fuel a period of rapid technological change.
There is a growing class of start-ups looking to attack the problem of making AI operations faster and more efficient by reconsidering the actual substrate where computation takes place. The graphics processing unit (GPU) has become increasingly popular among developers for its ability to handle the kinds of mathematics used in deep learning algorithms (like linear algebra) in a very speedy fashion. Some start-ups look to create a new platform from scratch, all the way down to the hardware, that is optimized specifically for AI operations. The hope is that by doing that, it will be able to outclass a GPU in terms of speed, power usage, and even potentially the actual size of the chip.
Accelerated Evolution of AI Chip Start-ups
One of the start-ups that is well-positioned to enter the battlefield with the giant chip makers is Cerebras Systems. Not much is known publicly about that nature of the chip the Los Altos-based startup is building. But the company has quietly amassed a large war chest to help it fund the capital-intensive business of building chips. In three rounds of funding, Cerebras has raised $112 million, and its valuation has soared to a whopping $860 million. Founded in 2016, with the help of 5 Nervana engineers, Cerebras is chock full of pedigreed chip industry veterans. Cerebras co-founder and CEO Andrew Feldman previously founded SeaMicro, a maker of low-power servers that AMD acquired for $334 million in 2012. After the acquisition, Feldman spent two and a half years as a corporate vice president for AMD. He then started up Cerebras along with other former colleagues from his SeaMicro and AMD days. Cerebras is still in stealth mode and has yet to release a product. Those familiar with the company say its hardware will be tailor-made for “training” deep learning algorithms. Training typically analyzes giant data sets and requires massive amounts of compute resources. […]
read more – copyright by insidebigdata.com
The computer chip industry over the last couple of decades has seen its innovation stem from just a few top players like Intel, AMD, NVIDIA, and Qualcomm. In this same time span, the VC industry has shown waning interest in start-up companies that made computer chips.
copyright by insidebigdata.com
The recent resurgence of the field of artificial intelligence (AI) has upended this status quo. It turns out that AI benefits from specific types of processors that perform operations in parallel, and this fact opens up tremendous opportunities for newcomers. The question is – are we seeing the start of a Cambrian Explosion of start-up companies designing specialized AI chips? If so, the explosion would be akin to the sudden proliferation of PC and hard-drive makers in the 1980s. While many of these companies are small, and not all will survive, they may have the power to fuel a period of rapid technological change.
There is a growing class of start-ups looking to attack the problem of making AI operations faster and more efficient by reconsidering the actual substrate where computation takes place. The graphics processing unit (GPU) has become increasingly popular among developers for its ability to handle the kinds of mathematics used in deep learning algorithms (like linear algebra) in a very speedy fashion. Some start-ups look to create a new platform from scratch, all the way down to the hardware, that is optimized specifically for AI operations. The hope is that by doing that, it will be able to outclass a GPU in terms of speed, power usage, and even potentially the actual size of the chip.
Accelerated Evolution of AI Chip Start-ups
One of the start-ups that is well-positioned to enter the battlefield with the giant chip makers is Cerebras Systems. Not much is known publicly about that nature of the chip the Los Altos-based startup is building. But the company has quietly amassed a large war chest to help it fund the capital-intensive business of building chips. In three rounds of funding, Cerebras has raised $112 million, and its valuation has soared to a whopping $860 million. Founded in 2016, with the help of 5 Nervana engineers, Cerebras is chock full of pedigreed chip industry veterans. Cerebras co-founder and CEO Andrew Feldman previously founded SeaMicro, a maker of low-power servers that AMD acquired for $334 million in 2012. After the acquisition, Feldman spent two and a half years as a corporate vice president for AMD. He then started up Cerebras along with other former colleagues from his SeaMicro and AMD days. Cerebras is still in stealth mode and has yet to release a product. Those familiar with the company say its hardware will be tailor-made for “training” deep learning algorithms. Training typically analyzes giant data sets and requires massive amounts of compute resources. […]
read more – copyright by insidebigdata.com
Share this: