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At CES 2018: Gyrfalcon Technology Competes with Intel with its Newly-Launched USB Stick

02 January 2018

LaceliTM AI Compute Stick, with a compact dimension and a 4GB free storage space. Source: Business WireLaceliTM AI Compute Stick, with a compact dimension and a 4GB free storage space. Source: Business Wire

Gyrfalcon Technology Inc, an emerging AI chip maker in Silicon Valley, California, has launched its Laceli™ AI Compute Stick after Intel Movidius announced its deep learning Neural Compute Stick in July of last year. The Laceli™ AI Compute Stick will be presented for the first time in January 2018 at CES 2018 in Las Vegas.

With the company’s first ultra-low power, high-performance AI processor Lightspeeur® 2801S, the Laceli™ AI Compute Stick runs a 2.8 TOPS performance within 0.3 watt of power, which is 90 times more efficient than the Movidius USB Stick (0.1 TOPS within 1 watt of power).

Lightspeeur® is based on Gyrfalcon Technology Inc.’s APiM architecture, which uses memory as the AI processing unit. This eliminates the huge data movement that results in high power consumption. The architecture features true, on-chip parallelism, in situ computing and eliminates memory bottlenecks. It has roughly 28,000 parallel computing cores and does not require external memory for AI inference.

The standard USB 3.0 Stick can be connected to a range of devices such as PCs, laptops and mobile phones and can enhance their image-based deep learning capabilities to unprecedented levels without them having to tap into a cloud-based system. With Caffe and TensorFlow support, the Stick enables various application development backgrounds.

Powered by a specialized AI Processor, Laceli™ can be used in many smart applications such as image and video recognition, natural speech understanding, natural language processing and day-to-day AI applications. Lightspeeur® 2810S is in production at the moment and is available today to qualified customers.

To contact the author of this article, email sue.himmelstein@ieeeglobalspec.com


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