Rebellions

South Korean startup Rebellions to use open source software for carriers to quickly build AI stacks with its AI inferencing chips

Posted on by Alan Weissberger

South Korean chip startup Rebellions builds purpose-engineered Al accelerators to redefine energy-efficiency and scale in the age of large-scale Al.  It aims to deliver the best performance per dollar per watt possible for inferencing and lower both capex and opex associated with running AI infrastructure. The company has been very selective about where it has established office locations and staffing: Korea, Japan, Singapore, Saudi Arabia and the United States.

Their flagship semiconductor product is the Rebel100, which uses a predictive, software-controlled DMA engine tightly coupled with an on-chip mesh to prefetch KV data proactively. This enbales 2.7TB/s effective bandwidth and reduces token-level latency in 32K+ context LLMs.

Image Credit: Rebellions

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Gaining valuable experience in building an AI stack with SK Telecom, it’s  pairing its field experience with an open source-first software strategy it said can help carriers move faster without locking scarce engineering talent into yet another proprietary AI stack.   The company says it’s dedicated to using open-source software – everything from vLLM and OpenShift to PyTorch – with a “no forks” rule. The rule is designed to help customers avoid skills issues and ensure engineers don’t have to learn non-transferrable skills just to use its equipment.

Rebellions’ work with SK Telecom (SKT) has served as a foundational pillar of its engagement with other operators, according to Marshall Choy, Rebellions’ Chief Business Officer (CBO). The company is in conversations with between 10 and 20 operators around the world.

“Our systems have been deployed at SKT for nearly three years,” Choy said. “What does that mean? It means three years of lessons learned, institutional knowledge gain, product improvement and deep engagement with an end user customer working on real problems… It’s three years of blood sweat and tears that has become institutional knowledge,” he added.

The network operators in its pipeline are in “different stages of engagement and deployment” with Rebellions, Choy said, saying there will be “more to come on that.” While SK Telecom has been its most publicized partner to date, Choy said over the next 12 months Rebellions plans to highlight more of what has been going on under cover. That includes work with other telecom operators as well as neocloud operators, enterprises and governments.

According to Choy, the architecture prioritizes low-latency, high-throughput compute infrastructure. From a cost-efficiency perspective, the company targets a price-to-performance ratio that is two to three times more cost-effective than comparable Nvidia hardware. Furthermore, Rebellions delivers significantly higher energy efficiency. While an Nvidia DGX GB200 NVL72 system consumes upwards of 120 kilowatts per rack, Rebellions averages 4 kilowatts per system, or approximately 20 kilowatts per rack.
Choy noted that this power reduction yields a 6x savings in operational expenditure (OpEx). It also enables telecommunications providers to deploy Rebellions infrastructure in edge environments with stringent power constraints, such as legacy central offices. By retrofitting these distributed facilities with modern inference compute to serve LLM tokens, operators can maximize the lifecycle and return on investment (ROI) of their existing physical assets.
“Our goal is to reduce the unit economics of AI inferencing to near zero,” Choy said. While he admitted that sounds strange coming from an AI inferencing chip company, Choy explained that it’s all about making AI accessible for even more use cases – the ones where the math doesn’t work out today.  “If you’re a telephone operator and you have an existing line card of services you provide, I can make you more profitable because I can lower your costs. But more strategically, what I can do is I can enable you to introduce a lower tier of services at a lower cost, which then makes AI inferencing accessible to a whole set of applications where it was previously too expensive,” he added.
It should be noted that Groq and SambaNova (see References below) are similarly working on chips to reduce the cost of inferencing. OpenAI appears to be moving in a similar direction with its Jalapeño chip.
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Through its work with SK Telecom and others (unnamed), Choy said Rebellions has learned that customers aren’t just looking for hardware or software but for fully optimized infrastructure that cuts across both. That’s where Rebellions’ open-source ethos comes into play.  “We didn’t want to have this mainframe model where everything is custom and bespoke and we’re this weird thing off in the side of the data center that doesn’t get touched by anything else,” Choy said. “It’s all about interoperability and integration.”

In conclusion, Choy opined, “Let’s be honest, the telcos don’t necessarily have all the right skills in place.  So, being able to spread that across more of an open-source ecosystem means they can be in service and productive faster.”

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References:

https://rebellions.ai/company/about/

https://rebellions.ai/category/blogs/

https://rebellions.ai/rebellions-product/rebel100/

https://www.fierce-network.com/cloud/rebellions-courts-telcos-cheaper-ai-inference-and-open-source-pitch

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