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Untether AI focuses on speeding up AI inference by using at-memory computing, which places compute close to memory cells to boost density and efficiency. The company ships runAI200 devices and tsunAImi accelerator cards, designed to deliver high performance within a PCI-Express form factor for tasks like vision, natural language processing, and recommendation engines. Unlike traditional accelerators that keep compute separate from memory, Untether AI’s architecture reduces data movement and increases throughput for inference workloads. The main difference from competitors is the hardware design that tightly integrates computation and memory to achieve very high ops-per-card while fitting standard bus interfaces, enabling businesses to run demanding AI tasks more cost-effectively. The goal is to help organizations optimize AI inference workloads by providing powerful, energy- and cost-efficient hardware that accelerates neural networks across various applications.
Industries
Data & Analytics
Hardware
AI & Machine Learning
Company Size
11-50
Company Stage
Series B
Total Funding
$148.7M
Headquarters
Toronto, Canada
Founded
2018
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Total Funding
$148.7M
Above
Industry Average
Funded Over
4 Rounds
Industry standards
Paid Vacation
Health Insurance
Unlimited Paid Time Off
Stock Options
Untether had been developing AI inference chips that it marketed as faster and more energy-efficient than its rivals, claiming to offer "energy-centric AI inference acceleration from the edge to the cloud."
AMD accelerates its AI strategy by acquiring Canadian startup Untether AI. The acquisition aims to enhance AMD's capabilities in high-performance computing, graphics, and AI innovation.
AMD has announced that it has just acquired Toronto-based AI chip company Untether AI.
AMD has acquired the team behind AI chip startup Untether AI, known for developing AI inference chips that are faster and more energy-efficient than competitors for edge environments and data centers.
TORONTO--(BUSINESS WIRE)--Untether AI, the leader in energy-centric AI inference acceleration, today announced a collaboration with Arm to develop best-in-class solutions optimized for next-generation automotive applications. As part of this collaboration, Untether AI will enable its inference acceleration technology to be implemented alongside the latest-generation Automotive Enhanced (AE) technology from Arm, to create solutions that address performance, power, safety, and security requirements for advanced Driver Assistance Systems (ADAS) and autonomous vehicle (AV) applications. Compute workloads radically changed in the past several years with the deployment of AI and the increasing complexity of AI and conventional software algorithms has elevated the demand for heterogeneous computing platforms employing domain-specific architectures. This trend, which is especially true in the automotive sector, results in an ideal computing platform that combines a mix of CPUs, AI accelerators, memory, and networking technologies that have been optimized for neural network acceleration and software-defined vehicles (SDV). “The increase in advanced user experiences, ADAS, and AV applications means more heterogeneous compute is needed in the vehicle,” said Suraj Gajendra, vice president of products and solutions, Automotive Line of Business, Arm. “By collaborating with Untether AI to ensure our leading-edge AE technology can work well alongside Untether AI’s acceleration capability, we are enabling our partners to power cutting edge AI workloads across the vehicle.”
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Industries
Data & Analytics
Hardware
AI & Machine Learning
Company Size
11-50
Company Stage
Series B
Total Funding
$148.7M
Headquarters
Toronto, Canada
Founded
2018
Find jobs on Simplify and start your career today