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The best way to stay connected to the Android pulse. A few weeks ago, Arm announced its first batch of dedicated machine learning (ML) hardware.

Under the name Project Trillium, the company unveiled a dedicated ML processor for products like smartphones, along with a second chip designed specifically to accelerate object detection (OD) use cases. Let’s delve deeper into Project Trillium and the company’s broader plans for the growing market for machine learning hardware.

It’s important to note that Arm’s announcement relates entirely to inference hardware. Its ML and OD processors are designed to efficiently run trained machine learning tasks on consumer-level hardware, rather than training algorithms on huge datasets.

To start, Arm is focusing on what it sees as the two biggest markets for ML inference hardware — smartphones and internet protocol/surveillance cameras. Despite the new dedicated machine learning hardware announcements with Project Trillium, Arm remains dedicated to supporting these type of tasks on its CPUs and GPUs too, with optimized dot product functions inside its Cortex-A75 and A55 cores. Read more from…

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